2026-07-15T23:35:16 - INFO: Slick 0.0.8a13

🟢 Starting Calibration Pipeline

=== Processing MDC006_W020(6)_2026-07-10 ===
2026-07-15T23:35:16 - INFO: Camera ID: 15091886
2026-07-15T23:35:16 - INFO: Wand ID: 
2026-07-15T23:35:16 - INFO: Recorded At: 2026-07-10T16:46:24Z

-------------------------------------------------------------------
                        Step 1: Digitization                       
-------------------------------------------------------------------

[🔄] Full PTD mode: Processing ALL images then creating calibration subset
[📸] Digitizing ALL images...
[📸] Full dataset mode: Processing ALL images (no debug visualizations)
[INFO] Found 4 las0.zip files to process

Processing Rigs:   0%|          | 0/4 [00:00<?, ?it/s][INFO] Filtered 807 stationary frames, 584 remain


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→ 2000L Phase 2: corners:   9%|▉         | 55/584 [00:00<00:04, 105.99it/s]

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→ 2000L Phase 2: corners:  33%|███▎      | 195/584 [00:01<00:03, 128.44it/s]

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→ 2000L Phase 2: corners:  42%|████▏     | 245/584 [00:02<00:02, 144.45it/s]

→ 2000L Phase 2: corners:  45%|████▌     | 265/584 [00:02<00:02, 159.28it/s]

→ 2000L Phase 2: corners:  49%|████▊     | 284/584 [00:02<00:01, 166.30it/s]

→ 2000L Phase 2: corners:  52%|█████▏    | 301/584 [00:02<00:01, 155.68it/s]

→ 2000L Phase 2: corners:  54%|█████▍    | 317/584 [00:02<00:01, 145.05it/s]

→ 2000L Phase 2: corners:  57%|█████▋    | 335/584 [00:02<00:01, 154.07it/s]

→ 2000L Phase 2: corners:  60%|██████    | 351/584 [00:02<00:01, 142.96it/s]

→ 2000L Phase 2: corners:  63%|██████▎   | 366/584 [00:02<00:01, 141.25it/s]

→ 2000L Phase 2: corners:  65%|██████▌   | 381/584 [00:02<00:01, 143.32it/s]

→ 2000L Phase 2: corners:  68%|██████▊   | 396/584 [00:03<00:01, 140.11it/s]

→ 2000L Phase 2: corners:  70%|███████   | 411/584 [00:03<00:01, 139.52it/s]

→ 2000L Phase 2: corners:  73%|███████▎  | 426/584 [00:03<00:01, 131.46it/s]

→ 2000L Phase 2: corners:  76%|███████▌  | 444/584 [00:03<00:00, 144.47it/s]

→ 2000L Phase 2: corners:  79%|███████▉  | 460/584 [00:03<00:00, 147.22it/s]

→ 2000L Phase 2: corners:  82%|████████▏ | 478/584 [00:03<00:00, 154.53it/s]

→ 2000L Phase 2: corners:  85%|████████▍ | 495/584 [00:03<00:00, 158.11it/s]

→ 2000L Phase 2: corners:  88%|████████▊ | 514/584 [00:03<00:00, 165.57it/s]

→ 2000L Phase 2: corners:  91%|█████████ | 531/584 [00:03<00:00, 165.96it/s]

→ 2000L Phase 2: corners:  94%|█████████▍| 548/584 [00:04<00:00, 166.01it/s]

                                                                            [PASS2] Frame 0000597: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0000609: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0000610: fixed corners {1} (was_fixed=True, trusted=False)
[PASS2] Frame 0000611: fixed corners {1} (was_fixed=True, trusted=True)
[PASS2] Frame 0000627: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0000628: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0000629: fixed corners {1} (was_fixed=True, trusted=False)
[PASS2] Frame 0000630: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0000631: fixed corners {1} (was_fixed=True, trusted=True)
[PASS2] Frame 0000660: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0000661: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0000662: fixed corners {1} (was_fixed=True, trusted=False)
[PASS2] Frame 0000663: fixed corners {1} (was_fixed=True, trusted=True)
[PASS2] Frame 0000876: fixed corners {1} (was_fixed=True, trusted=True)
[PASS2] Frame 0000889: fixed corners {1} (was_fixed=True, trusted=True)
[PASS2] Frame 0000947: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001125: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001126: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001127: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001128: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001129: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001130: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001131: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001132: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001134: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001135: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001136: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001137: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001138: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001139: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001140: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001141: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001142: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001143: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001147: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001148: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001149: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001150: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001163: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001170: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001173: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001176: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001180: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001183: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001184: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001185: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001188: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001191: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001192: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001194: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001200: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001203: fixed corners {2, 3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001288: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001289: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001290: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001291: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001293: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001297: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001298: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001299: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001300: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001301: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001302: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001304: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001305: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001306: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001307: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001308: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001309: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001310: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001311: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001312: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001313: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001322: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001323: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001324: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001325: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001326: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001328: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001329: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001332: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001333: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001334: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001340: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001341: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001342: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001344: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001345: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001346: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001348: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001352: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001353: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001360: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001361: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001362: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001363: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001367: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001368: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001369: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001370: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000610: fixed corners {1} (was_fixed=True, trusted=True)
[PASS2] Frame 0000629: fixed corners {1} (was_fixed=True, trusted=True)
[PASS2] Frame 0000630: fixed corners {1} (was_fixed=True, trusted=True)
[PASS2] Frame 0000662: fixed corners {1} (was_fixed=True, trusted=True)
[PASS2] Frame 0001130: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001131: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001136: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001139: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001142: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001149: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001188: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001191: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001203: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001285: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001286: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001287: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001288: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001296: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001298: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001300: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001301: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001302: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001306: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001307: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001308: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001310: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001311: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001312: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001324: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001326: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001327: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001330: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001331: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001333: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001350: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001351: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001352: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001362: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001369: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001128: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001184: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001295: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001296: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001300: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001301: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001302: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001309: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001310: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001311: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001330: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001331: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001349: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001350: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001351: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Summary: 62 frames fixed, 70 untrusted, 584 total


→ 2000L Phase 3: finalize:   0%|          | 0/584 [00:00<?, ?it/s]

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→ 2000L Phase 3: finalize:   4%|▍         | 23/584 [00:00<00:10, 52.02it/s]

→ 2000L Phase 3: finalize:   5%|▍         | 29/584 [00:00<00:10, 51.89it/s]

→ 2000L Phase 3: finalize:   6%|▌         | 35/584 [00:00<00:10, 52.16it/s]

→ 2000L Phase 3: finalize:   7%|▋         | 41/584 [00:00<00:10, 52.07it/s]

→ 2000L Phase 3: finalize:   8%|▊         | 47/584 [00:00<00:10, 51.87it/s]

→ 2000L Phase 3: finalize:   9%|▉         | 53/584 [00:01<00:10, 51.72it/s]

→ 2000L Phase 3: finalize:  10%|█         | 59/584 [00:01<00:10, 51.61it/s]

→ 2000L Phase 3: finalize:  11%|█         | 65/584 [00:01<00:10, 51.63it/s]

→ 2000L Phase 3: finalize:  12%|█▏        | 71/584 [00:01<00:09, 51.59it/s]

→ 2000L Phase 3: finalize:  13%|█▎        | 77/584 [00:01<00:09, 51.65it/s]

→ 2000L Phase 3: finalize:  14%|█▍        | 83/584 [00:01<00:09, 51.81it/s]

→ 2000L Phase 3: finalize:  15%|█▌        | 89/584 [00:01<00:09, 52.00it/s]

→ 2000L Phase 3: finalize:  16%|█▋        | 95/584 [00:01<00:09, 51.91it/s]

→ 2000L Phase 3: finalize:  17%|█▋        | 101/584 [00:01<00:09, 52.00it/s]

→ 2000L Phase 3: finalize:  18%|█▊        | 107/584 [00:02<00:09, 51.95it/s]

→ 2000L Phase 3: finalize:  19%|█▉        | 113/584 [00:02<00:09, 51.98it/s]

→ 2000L Phase 3: finalize:  20%|██        | 119/584 [00:02<00:08, 51.92it/s]

→ 2000L Phase 3: finalize:  21%|██▏       | 125/584 [00:02<00:08, 51.84it/s]

→ 2000L Phase 3: finalize:  22%|██▏       | 131/584 [00:02<00:08, 51.64it/s]

→ 2000L Phase 3: finalize:  23%|██▎       | 137/584 [00:02<00:08, 51.42it/s]

→ 2000L Phase 3: finalize:  24%|██▍       | 143/584 [00:02<00:08, 51.70it/s]

→ 2000L Phase 3: finalize:  26%|██▌       | 149/584 [00:02<00:08, 52.08it/s]

→ 2000L Phase 3: finalize:  27%|██▋       | 155/584 [00:02<00:08, 52.33it/s]

→ 2000L Phase 3: finalize:  28%|██▊       | 161/584 [00:03<00:08, 52.56it/s]

→ 2000L Phase 3: finalize:  29%|██▊       | 167/584 [00:03<00:07, 52.56it/s]

→ 2000L Phase 3: finalize:  30%|██▉       | 173/584 [00:03<00:07, 52.70it/s]

→ 2000L Phase 3: finalize:  31%|███       | 179/584 [00:03<00:07, 52.78it/s]

→ 2000L Phase 3: finalize:  32%|███▏      | 185/584 [00:03<00:07, 52.86it/s]

→ 2000L Phase 3: finalize:  33%|███▎      | 191/584 [00:03<00:07, 52.82it/s]

→ 2000L Phase 3: finalize:  34%|███▎      | 197/584 [00:03<00:07, 52.89it/s]

→ 2000L Phase 3: finalize:  35%|███▍      | 203/584 [00:03<00:07, 53.00it/s]

→ 2000L Phase 3: finalize:  36%|███▌      | 209/584 [00:04<00:07, 52.97it/s]

→ 2000L Phase 3: finalize:  37%|███▋      | 215/584 [00:04<00:06, 52.90it/s]

→ 2000L Phase 3: finalize:  38%|███▊      | 221/584 [00:04<00:06, 52.90it/s]

→ 2000L Phase 3: finalize:  39%|███▉      | 227/584 [00:04<00:06, 52.91it/s]

→ 2000L Phase 3: finalize:  40%|███▉      | 233/584 [00:04<00:06, 53.05it/s]

→ 2000L Phase 3: finalize:  41%|████      | 239/584 [00:04<00:06, 53.21it/s]

→ 2000L Phase 3: finalize:  42%|████▏     | 245/584 [00:04<00:06, 53.42it/s]

→ 2000L Phase 3: finalize:  43%|████▎     | 251/584 [00:04<00:06, 53.58it/s]

→ 2000L Phase 3: finalize:  44%|████▍     | 257/584 [00:04<00:06, 53.77it/s]

→ 2000L Phase 3: finalize:  45%|████▌     | 263/584 [00:05<00:05, 53.93it/s]

→ 2000L Phase 3: finalize:  46%|████▌     | 269/584 [00:05<00:05, 53.84it/s]

→ 2000L Phase 3: finalize:  47%|████▋     | 275/584 [00:05<00:05, 54.06it/s]

→ 2000L Phase 3: finalize:  48%|████▊     | 281/584 [00:05<00:05, 54.05it/s]

→ 2000L Phase 3: finalize:  49%|████▉     | 287/584 [00:05<00:05, 54.22it/s]

→ 2000L Phase 3: finalize:  50%|█████     | 293/584 [00:05<00:05, 54.21it/s]

→ 2000L Phase 3: finalize:  51%|█████     | 299/584 [00:05<00:05, 54.29it/s]

→ 2000L Phase 3: finalize:  52%|█████▏    | 305/584 [00:05<00:05, 54.49it/s]

→ 2000L Phase 3: finalize:  53%|█████▎    | 311/584 [00:05<00:04, 54.66it/s]

→ 2000L Phase 3: finalize:  54%|█████▍    | 317/584 [00:06<00:04, 54.89it/s]

→ 2000L Phase 3: finalize:  55%|█████▌    | 323/584 [00:06<00:04, 55.04it/s]

→ 2000L Phase 3: finalize:  56%|█████▋    | 329/584 [00:06<00:04, 55.17it/s]

→ 2000L Phase 3: finalize:  57%|█████▋    | 335/584 [00:06<00:04, 55.28it/s]

→ 2000L Phase 3: finalize:  58%|█████▊    | 341/584 [00:06<00:04, 55.50it/s]

→ 2000L Phase 3: finalize:  59%|█████▉    | 347/584 [00:06<00:04, 55.55it/s]

→ 2000L Phase 3: finalize:  60%|██████    | 353/584 [00:06<00:04, 55.52it/s]

→ 2000L Phase 3: finalize:  61%|██████▏   | 359/584 [00:06<00:04, 55.60it/s]

→ 2000L Phase 3: finalize:  62%|██████▎   | 365/584 [00:06<00:03, 55.61it/s]

→ 2000L Phase 3: finalize:  64%|██████▎   | 371/584 [00:06<00:03, 55.63it/s]

→ 2000L Phase 3: finalize:  65%|██████▍   | 377/584 [00:07<00:03, 55.65it/s]

→ 2000L Phase 3: finalize:  66%|██████▌   | 383/584 [00:07<00:03, 55.68it/s]

→ 2000L Phase 3: finalize:  67%|██████▋   | 389/584 [00:07<00:03, 55.53it/s]

→ 2000L Phase 3: finalize:  68%|██████▊   | 395/584 [00:07<00:03, 55.61it/s]

→ 2000L Phase 3: finalize:  69%|██████▊   | 401/584 [00:07<00:03, 55.73it/s]

→ 2000L Phase 3: finalize:  70%|██████▉   | 407/584 [00:07<00:03, 55.95it/s]

→ 2000L Phase 3: finalize:  71%|███████   | 413/584 [00:07<00:03, 56.19it/s]

→ 2000L Phase 3: finalize:  72%|███████▏  | 419/584 [00:07<00:02, 56.15it/s]

→ 2000L Phase 3: finalize:  73%|███████▎  | 425/584 [00:07<00:02, 56.23it/s]

→ 2000L Phase 3: finalize:  74%|███████▍  | 431/584 [00:08<00:02, 56.25it/s]

→ 2000L Phase 3: finalize:  75%|███████▍  | 437/584 [00:08<00:02, 56.26it/s]

→ 2000L Phase 3: finalize:  76%|███████▌  | 443/584 [00:08<00:02, 56.29it/s]

→ 2000L Phase 3: finalize:  77%|███████▋  | 449/584 [00:08<00:02, 56.58it/s]

→ 2000L Phase 3: finalize:  78%|███████▊  | 455/584 [00:08<00:02, 56.52it/s]

→ 2000L Phase 3: finalize:  79%|███████▉  | 461/584 [00:08<00:02, 56.52it/s]

→ 2000L Phase 3: finalize:  80%|███████▉  | 467/584 [00:08<00:02, 56.66it/s]

→ 2000L Phase 3: finalize:  81%|████████  | 473/584 [00:08<00:01, 56.24it/s]

→ 2000L Phase 3: finalize:  82%|████████▏ | 479/584 [00:08<00:01, 55.96it/s]

→ 2000L Phase 3: finalize:  83%|████████▎ | 485/584 [00:09<00:01, 55.63it/s]

→ 2000L Phase 3: finalize:  84%|████████▍ | 491/584 [00:09<00:01, 55.35it/s]

→ 2000L Phase 3: finalize:  85%|████████▌ | 497/584 [00:09<00:01, 55.53it/s]

→ 2000L Phase 3: finalize:  86%|████████▌ | 503/584 [00:09<00:01, 55.71it/s]

→ 2000L Phase 3: finalize:  87%|████████▋ | 509/584 [00:09<00:01, 55.89it/s]

→ 2000L Phase 3: finalize:  88%|████████▊ | 515/584 [00:09<00:01, 55.81it/s]

→ 2000L Phase 3: finalize:  89%|████████▉ | 521/584 [00:09<00:01, 55.85it/s]

→ 2000L Phase 3: finalize:  90%|█████████ | 527/584 [00:09<00:01, 56.00it/s]

→ 2000L Phase 3: finalize:  91%|█████████▏| 533/584 [00:09<00:00, 55.95it/s]

→ 2000L Phase 3: finalize:  92%|█████████▏| 539/584 [00:09<00:00, 55.88it/s]

→ 2000L Phase 3: finalize:  93%|█████████▎| 545/584 [00:10<00:00, 55.76it/s]

→ 2000L Phase 3: finalize:  94%|█████████▍| 551/584 [00:10<00:00, 55.57it/s]

→ 2000L Phase 3: finalize:  95%|█████████▌| 557/584 [00:10<00:00, 55.42it/s]

→ 2000L Phase 3: finalize:  96%|█████████▋| 563/584 [00:10<00:00, 55.23it/s]

→ 2000L Phase 3: finalize:  97%|█████████▋| 569/584 [00:10<00:00, 55.09it/s]

→ 2000L Phase 3: finalize:  98%|█████████▊| 575/584 [00:10<00:00, 55.04it/s]

→ 2000L Phase 3: finalize:  99%|█████████▉| 581/584 [00:10<00:00, 54.79it/s]

                                                                            
[TIMING] 2000L — 584 frames
  Phase 1  radial detect   (parallel)  :   8.48s  (14.5 ms/frame)
  Phase 2a corner detect   (parallel)  :   4.12s  (7.0 ms/frame)
  Phase 2b corner fix      (sequential):   2.50s
  Phase 3  finalize        (sequential):  10.80s  (18.5 ms/frame)
    decode + undistort                 :   5.69s  (9.7 ms/frame)
    corner apply + refinement          :   2.30s  (3.9 ms/frame)
    segment                            :   2.28s  (3.9 ms/frame)
    smooth                             :   0.34s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  25.90s


Processing Rigs:  25%|██▌       | 1/4 [00:32<01:36, 32.04s/it][INFO] Filtered 690 stationary frames, 578 remain


→ 2000R (578 images) Phase 1:   0%|          | 0/578 [00:00<?, ?it/s]

→ 2000R (578 images) Phase 1:   0%|          | 1/578 [00:00<06:12,  1.55it/s]

→ 2000R (578 images) Phase 1:   5%|▌         | 31/578 [00:00<00:09, 55.42it/s]

→ 2000R (578 images) Phase 1:   8%|▊         | 49/578 [00:01<00:10, 50.98it/s]

→ 2000R (578 images) Phase 1:  11%|█         | 64/578 [00:01<00:07, 65.81it/s]

→ 2000R (578 images) Phase 1:  13%|█▎        | 77/578 [00:01<00:09, 55.36it/s]

→ 2000R (578 images) Phase 1:  17%|█▋        | 96/578 [00:01<00:06, 76.28it/s]

→ 2000R (578 images) Phase 1:  19%|█▉        | 109/578 [00:01<00:07, 60.23it/s]

→ 2000R (578 images) Phase 1:  22%|██▏       | 129/578 [00:02<00:07, 62.92it/s]

→ 2000R (578 images) Phase 1:  24%|██▍       | 138/578 [00:02<00:06, 65.15it/s]

→ 2000R (578 images) Phase 1:  28%|██▊       | 159/578 [00:02<00:04, 88.82it/s]

→ 2000R (578 images) Phase 1:  30%|██▉       | 172/578 [00:02<00:06, 66.57it/s]

→ 2000R (578 images) Phase 1:  33%|███▎      | 192/578 [00:02<00:04, 84.92it/s]

→ 2000R (578 images) Phase 1:  35%|███▌      | 204/578 [00:03<00:05, 65.62it/s]

→ 2000R (578 images) Phase 1:  39%|███▊      | 223/578 [00:03<00:04, 84.85it/s]

→ 2000R (578 images) Phase 1:  41%|████      | 236/578 [00:03<00:05, 65.38it/s]

→ 2000R (578 images) Phase 1:  44%|████▍     | 255/578 [00:03<00:03, 83.02it/s]

→ 2000R (578 images) Phase 1:  46%|████▌     | 267/578 [00:04<00:04, 64.30it/s]

→ 2000R (578 images) Phase 1:  49%|████▉     | 286/578 [00:04<00:03, 82.87it/s]

→ 2000R (578 images) Phase 1:  52%|█████▏    | 298/578 [00:04<00:04, 56.37it/s]

→ 2000R (578 images) Phase 1:  55%|█████▌    | 318/578 [00:04<00:03, 76.03it/s]

→ 2000R (578 images) Phase 1:  57%|█████▋    | 331/578 [00:05<00:04, 60.52it/s]

→ 2000R (578 images) Phase 1:  61%|██████    | 351/578 [00:05<00:03, 75.55it/s]

→ 2000R (578 images) Phase 1:  63%|██████▎   | 362/578 [00:05<00:03, 61.71it/s]

→ 2000R (578 images) Phase 1:  66%|██████▋   | 383/578 [00:05<00:02, 78.69it/s]

→ 2000R (578 images) Phase 1:  68%|██████▊   | 394/578 [00:06<00:02, 63.66it/s]

→ 2000R (578 images) Phase 1:  72%|███████▏  | 415/578 [00:06<00:02, 79.80it/s]

→ 2000R (578 images) Phase 1:  74%|███████▎  | 426/578 [00:06<00:02, 64.96it/s]

→ 2000R (578 images) Phase 1:  77%|███████▋  | 447/578 [00:06<00:01, 81.33it/s]

→ 2000R (578 images) Phase 1:  79%|███████▉  | 458/578 [00:06<00:01, 64.67it/s]

→ 2000R (578 images) Phase 1:  83%|████████▎ | 479/578 [00:07<00:01, 82.33it/s]

→ 2000R (578 images) Phase 1:  85%|████████▍ | 490/578 [00:07<00:01, 65.89it/s]

→ 2000R (578 images) Phase 1:  88%|████████▊ | 511/578 [00:07<00:00, 83.25it/s]

→ 2000R (578 images) Phase 1:  90%|█████████ | 522/578 [00:07<00:00, 65.77it/s]

→ 2000R (578 images) Phase 1:  94%|█████████▍| 543/578 [00:07<00:00, 83.45it/s]

→ 2000R (578 images) Phase 1:  96%|█████████▌| 554/578 [00:08<00:00, 66.50it/s]

→ 2000R (578 images) Phase 1: 100%|█████████▉| 577/578 [00:08<00:00, 80.30it/s]

                                                                               

→ 2000R Phase 2: corners:   0%|          | 0/578 [00:00<?, ?it/s]

→ 2000R Phase 2: corners:   0%|          | 1/578 [00:00<02:34,  3.75it/s]

→ 2000R Phase 2: corners:   3%|▎         | 17/578 [00:00<00:09, 57.48it/s]

→ 2000R Phase 2: corners:   6%|▌         | 32/578 [00:00<00:06, 86.88it/s]

→ 2000R Phase 2: corners:   8%|▊         | 45/578 [00:00<00:05, 94.02it/s]

→ 2000R Phase 2: corners:  11%|█         | 63/578 [00:00<00:04, 117.82it/s]

→ 2000R Phase 2: corners:  13%|█▎        | 77/578 [00:00<00:04, 119.85it/s]

→ 2000R Phase 2: corners:  16%|█▌        | 91/578 [00:00<00:03, 121.88it/s]

→ 2000R Phase 2: corners:  19%|█▉        | 109/578 [00:01<00:03, 135.25it/s]

→ 2000R Phase 2: corners:  21%|██▏       | 124/578 [00:01<00:03, 126.97it/s]

→ 2000R Phase 2: corners:  24%|██▍       | 138/578 [00:01<00:03, 128.35it/s]

→ 2000R Phase 2: corners:  26%|██▋       | 152/578 [00:01<00:03, 128.54it/s]

→ 2000R Phase 2: corners:  29%|██▉       | 167/578 [00:01<00:03, 131.99it/s]

→ 2000R Phase 2: corners:  31%|███▏      | 182/578 [00:01<00:02, 135.81it/s]

→ 2000R Phase 2: corners:  34%|███▍      | 198/578 [00:01<00:02, 141.96it/s]

→ 2000R Phase 2: corners:  37%|███▋      | 213/578 [00:01<00:03, 109.66it/s]

→ 2000R Phase 2: corners:  39%|███▉      | 227/578 [00:02<00:03, 115.48it/s]

→ 2000R Phase 2: corners:  42%|████▏     | 241/578 [00:02<00:02, 121.09it/s]

→ 2000R Phase 2: corners:  44%|████▍     | 256/578 [00:02<00:02, 127.45it/s]

→ 2000R Phase 2: corners:  47%|████▋     | 270/578 [00:02<00:02, 130.42it/s]

→ 2000R Phase 2: corners:  49%|████▉     | 286/578 [00:02<00:02, 137.88it/s]

→ 2000R Phase 2: corners:  53%|█████▎    | 306/578 [00:02<00:01, 149.36it/s]

→ 2000R Phase 2: corners:  56%|█████▌    | 323/578 [00:02<00:01, 152.25it/s]

→ 2000R Phase 2: corners:  59%|█████▊    | 339/578 [00:02<00:01, 150.79it/s]

→ 2000R Phase 2: corners:  61%|██████▏   | 355/578 [00:02<00:01, 147.27it/s]

→ 2000R Phase 2: corners:  64%|██████▍   | 371/578 [00:02<00:01, 148.23it/s]

→ 2000R Phase 2: corners:  67%|██████▋   | 387/578 [00:03<00:01, 148.26it/s]

→ 2000R Phase 2: corners:  70%|██████▉   | 404/578 [00:03<00:01, 154.29it/s]

→ 2000R Phase 2: corners:  73%|███████▎  | 422/578 [00:03<00:00, 158.96it/s]

→ 2000R Phase 2: corners:  76%|███████▋  | 442/578 [00:03<00:00, 165.56it/s]

→ 2000R Phase 2: corners:  79%|███████▉  | 459/578 [00:03<00:00, 162.23it/s]

→ 2000R Phase 2: corners:  82%|████████▏ | 476/578 [00:03<00:00, 161.04it/s]

→ 2000R Phase 2: corners:  86%|████████▌ | 495/578 [00:03<00:00, 166.52it/s]

→ 2000R Phase 2: corners:  89%|████████▊ | 512/578 [00:03<00:00, 159.94it/s]

→ 2000R Phase 2: corners:  92%|█████████▏| 529/578 [00:03<00:00, 160.18it/s]

→ 2000R Phase 2: corners:  94%|█████████▍| 546/578 [00:04<00:00, 161.78it/s]

                                                                            [PASS2] Frame 0000379: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000380: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000381: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000382: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000387: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000388: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000389: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000390: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000393: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000394: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000395: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000397: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000398: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000399: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000400: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000401: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000402: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000403: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000404: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000405: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000406: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000408: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000409: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000411: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000413: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000415: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000416: fixed corners {2, 3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000418: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000419: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000420: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000421: fixed corners {2, 3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000424: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000425: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000426: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000427: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000428: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000530: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000531: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000533: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000534: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000539: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000541: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000542: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000548: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000551: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000554: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000557: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000566: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000569: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000575: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000578: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000581: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000584: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000594: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000596: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000597: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000598: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000600: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000601: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000602: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000603: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000605: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000606: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000607: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000610: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000611: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000612: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000613: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000614: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000615: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000617: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000618: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000619: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000621: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000622: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000623: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000624: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000906: fixed corners {0} (was_fixed=True, trusted=True)
[PASS2] Frame 0000925: fixed corners {0} (was_fixed=False, trusted=False)
[PASS2] Frame 0000926: fixed corners {0} (was_fixed=True, trusted=True)
[PASS2] Frame 0000939: fixed corners {0} (was_fixed=False, trusted=False)
[PASS2] Frame 0000940: fixed corners {0} (was_fixed=False, trusted=False)
[PASS2] Frame 0000941: fixed corners {0} (was_fixed=True, trusted=False)
[PASS2] Frame 0000942: fixed corners {0} (was_fixed=True, trusted=False)
[PASS2] Frame 0000943: fixed corners {0} (was_fixed=False, trusted=False)
[PASS2] Frame 0000944: fixed corners {0} (was_fixed=True, trusted=False)
[PASS2] Frame 0000945: fixed corners {0} (was_fixed=True, trusted=True)
[PASS2] Frame 0001020: fixed corners {0} (was_fixed=True, trusted=True)
[PASS2] Frame 0001022: fixed corners {0} (was_fixed=True, trusted=True)
[PASS2] Frame 0001233: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0001234: fixed corners {1} (was_fixed=False, trusted=False)
[PASS2] Frame 0001235: fixed corners {1} (was_fixed=True, trusted=False)
[PASS2] Frame 0001236: fixed corners {1} (was_fixed=True, trusted=True)
[PASS2] Frame 0000381: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000389: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000395: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000396: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000398: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000401: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000402: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000416: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000417: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000421: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000422: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000423: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000425: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000426: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000428: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000530: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000531: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000536: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000541: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000554: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000557: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000560: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000572: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000581: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000597: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000602: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000605: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000606: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000607: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000612: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000613: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000614: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000617: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000618: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000619: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000623: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000941: fixed corners {0} (was_fixed=True, trusted=True)
[PASS2] Frame 0000944: fixed corners {0} (was_fixed=True, trusted=True)
[PASS2] Frame 0001235: fixed corners {1} (was_fixed=True, trusted=True)
[PASS2] Frame 0000413: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000414: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000428: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000530: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000531: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000534: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000536: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000605: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000606: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000607: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000610: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000611: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000612: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000617: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000618: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000619: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Summary: 54 frames fixed, 60 untrusted, 578 total


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→ 2000R Phase 3: finalize:  91%|█████████▏| 528/578 [00:09<00:00, 52.90it/s]

→ 2000R Phase 3: finalize:  92%|█████████▏| 534/578 [00:09<00:00, 52.92it/s]

→ 2000R Phase 3: finalize:  93%|█████████▎| 540/578 [00:09<00:00, 53.03it/s]

→ 2000R Phase 3: finalize:  94%|█████████▍| 546/578 [00:10<00:00, 53.07it/s]

→ 2000R Phase 3: finalize:  96%|█████████▌| 552/578 [00:10<00:00, 53.23it/s]

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→ 2000R Phase 3: finalize:  98%|█████████▊| 564/578 [00:10<00:00, 53.63it/s]

→ 2000R Phase 3: finalize:  99%|█████████▊| 570/578 [00:10<00:00, 53.62it/s]

→ 2000R Phase 3: finalize: 100%|█████████▉| 576/578 [00:10<00:00, 53.77it/s]

                                                                            
[TIMING] 2000R — 578 frames
  Phase 1  radial detect   (parallel)  :   8.52s  (14.7 ms/frame)
  Phase 2a corner detect   (parallel)  :   4.16s  (7.2 ms/frame)
  Phase 2b corner fix      (sequential):   2.37s
  Phase 3  finalize        (sequential):  10.69s  (18.5 ms/frame)
    decode + undistort                 :   5.62s  (9.7 ms/frame)
    corner apply + refinement          :   2.28s  (4.0 ms/frame)
    segment                            :   2.26s  (3.9 ms/frame)
    smooth                             :   0.34s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  25.73s


Processing Rigs:  50%|█████     | 2/4 [01:01<01:01, 30.68s/it][INFO] Filtered 513 stationary frames, 729 remain


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→ 1500 (729 images) Phase 1:  69%|██████▉   | 506/729 [00:07<00:02, 82.46it/s]

→ 1500 (729 images) Phase 1:  71%|███████   | 518/729 [00:07<00:03, 63.63it/s]

→ 1500 (729 images) Phase 1:  74%|███████▎  | 536/729 [00:07<00:02, 81.77it/s]

→ 1500 (729 images) Phase 1:  75%|███████▌  | 548/729 [00:08<00:02, 63.97it/s]

→ 1500 (729 images) Phase 1:  77%|███████▋  | 561/729 [00:08<00:02, 74.23it/s]

→ 1500 (729 images) Phase 1:  79%|███████▉  | 576/729 [00:08<00:01, 84.76it/s]

→ 1500 (729 images) Phase 1:  81%|████████  | 587/729 [00:08<00:02, 67.80it/s]

→ 1500 (729 images) Phase 1:  83%|████████▎ | 605/729 [00:08<00:01, 86.35it/s]

→ 1500 (729 images) Phase 1:  85%|████████▍ | 617/729 [00:09<00:01, 58.41it/s]

→ 1500 (729 images) Phase 1:  87%|████████▋ | 631/729 [00:09<00:01, 70.62it/s]

→ 1500 (729 images) Phase 1:  88%|████████▊ | 642/729 [00:09<00:01, 59.95it/s]

→ 1500 (729 images) Phase 1:  89%|████████▉ | 652/729 [00:09<00:01, 65.53it/s]

→ 1500 (729 images) Phase 1:  92%|█████████▏| 670/729 [00:09<00:00, 83.78it/s]

→ 1500 (729 images) Phase 1:  93%|█████████▎| 681/729 [00:09<00:00, 65.13it/s]

→ 1500 (729 images) Phase 1:  96%|█████████▌| 698/729 [00:10<00:00, 82.27it/s]

→ 1500 (729 images) Phase 1:  97%|█████████▋| 709/729 [00:10<00:00, 70.23it/s]

→ 1500 (729 images) Phase 1: 100%|█████████▉| 726/729 [00:10<00:00, 84.65it/s]

                                                                              

→ 1500 Phase 2: corners:   0%|          | 0/729 [00:00<?, ?it/s]

→ 1500 Phase 2: corners:   0%|          | 1/729 [00:00<03:08,  3.87it/s]

→ 1500 Phase 2: corners:   2%|▏         | 12/729 [00:00<00:17, 39.95it/s]

→ 1500 Phase 2: corners:   3%|▎         | 22/729 [00:00<00:12, 58.09it/s]

→ 1500 Phase 2: corners:   5%|▍         | 34/729 [00:00<00:09, 73.47it/s]

→ 1500 Phase 2: corners:   7%|▋         | 53/729 [00:00<00:06, 105.17it/s]

→ 1500 Phase 2: corners:   9%|▉         | 65/729 [00:00<00:06, 109.15it/s]

→ 1500 Phase 2: corners:  11%|█         | 78/729 [00:00<00:05, 109.37it/s]

→ 1500 Phase 2: corners:  13%|█▎        | 92/729 [00:01<00:05, 118.04it/s]

→ 1500 Phase 2: corners:  15%|█▍        | 106/729 [00:01<00:05, 122.87it/s]

→ 1500 Phase 2: corners:  16%|█▋        | 119/729 [00:01<00:05, 116.46it/s]

→ 1500 Phase 2: corners:  18%|█▊        | 134/729 [00:01<00:04, 124.60it/s]

→ 1500 Phase 2: corners:  20%|██        | 148/729 [00:01<00:04, 125.38it/s]

→ 1500 Phase 2: corners:  22%|██▏       | 163/729 [00:01<00:04, 131.92it/s]

→ 1500 Phase 2: corners:  25%|██▍       | 181/729 [00:01<00:03, 144.36it/s]

→ 1500 Phase 2: corners:  27%|██▋       | 196/729 [00:01<00:03, 135.27it/s]

→ 1500 Phase 2: corners:  29%|██▉       | 210/729 [00:01<00:03, 133.79it/s]

→ 1500 Phase 2: corners:  31%|███       | 227/729 [00:02<00:03, 140.93it/s]

→ 1500 Phase 2: corners:  33%|███▎      | 244/729 [00:02<00:03, 148.54it/s]

→ 1500 Phase 2: corners:  36%|███▌      | 259/729 [00:02<00:03, 143.11it/s]

→ 1500 Phase 2: corners:  38%|███▊      | 274/729 [00:02<00:03, 142.58it/s]

→ 1500 Phase 2: corners:  40%|███▉      | 290/729 [00:02<00:03, 144.95it/s]

→ 1500 Phase 2: corners:  42%|████▏     | 306/729 [00:02<00:02, 147.73it/s]

→ 1500 Phase 2: corners:  44%|████▍     | 323/729 [00:02<00:02, 152.39it/s]

→ 1500 Phase 2: corners:  47%|████▋     | 339/729 [00:02<00:02, 153.96it/s]

→ 1500 Phase 2: corners:  49%|████▉     | 356/729 [00:02<00:02, 156.56it/s]

→ 1500 Phase 2: corners:  51%|█████▏    | 375/729 [00:02<00:02, 161.75it/s]

→ 1500 Phase 2: corners:  54%|█████▍    | 392/729 [00:03<00:02, 156.26it/s]

→ 1500 Phase 2: corners:  56%|█████▌    | 408/729 [00:03<00:02, 148.49it/s]

→ 1500 Phase 2: corners:  59%|█████▊    | 428/729 [00:03<00:01, 160.28it/s]

→ 1500 Phase 2: corners:  61%|██████    | 445/729 [00:03<00:01, 154.28it/s]

→ 1500 Phase 2: corners:  63%|██████▎   | 461/729 [00:03<00:01, 155.46it/s]

→ 1500 Phase 2: corners:  65%|██████▌   | 477/729 [00:03<00:01, 155.65it/s]

→ 1500 Phase 2: corners:  68%|██████▊   | 495/729 [00:03<00:01, 161.27it/s]

→ 1500 Phase 2: corners:  70%|███████   | 512/729 [00:03<00:01, 161.18it/s]

→ 1500 Phase 2: corners:  73%|███████▎  | 529/729 [00:03<00:01, 159.94it/s]

→ 1500 Phase 2: corners:  75%|███████▍  | 546/729 [00:04<00:01, 162.43it/s]

→ 1500 Phase 2: corners:  77%|███████▋  | 563/729 [00:04<00:01, 160.42it/s]

→ 1500 Phase 2: corners:  80%|███████▉  | 581/729 [00:04<00:00, 163.94it/s]

→ 1500 Phase 2: corners:  82%|████████▏ | 599/729 [00:04<00:00, 165.12it/s]

→ 1500 Phase 2: corners:  85%|████████▍ | 617/729 [00:04<00:00, 164.92it/s]

→ 1500 Phase 2: corners:  87%|████████▋ | 636/729 [00:04<00:00, 169.05it/s]

→ 1500 Phase 2: corners:  90%|████████▉ | 653/729 [00:04<00:00, 166.06it/s]

→ 1500 Phase 2: corners:  92%|█████████▏| 670/729 [00:04<00:00, 163.89it/s]

→ 1500 Phase 2: corners:  94%|█████████▍| 688/729 [00:04<00:00, 166.38it/s]

                                                                           [PASS2] Frame 0000355: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000356: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000357: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000358: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000357: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Summary: 2 frames fixed, 3 untrusted, 729 total


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→ 1500 Phase 3: finalize:  21%|██        | 151/729 [00:02<00:10, 54.62it/s]

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→ 1500 Phase 3: finalize:  40%|████      | 295/729 [00:05<00:07, 54.70it/s]

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→ 1500 Phase 3: finalize:  78%|███████▊  | 565/729 [00:10<00:02, 55.23it/s]

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→ 1500 Phase 3: finalize:  85%|████████▍ | 619/729 [00:11<00:01, 55.93it/s]

→ 1500 Phase 3: finalize:  86%|████████▌ | 625/729 [00:11<00:01, 55.82it/s]

→ 1500 Phase 3: finalize:  87%|████████▋ | 631/729 [00:11<00:01, 55.88it/s]

→ 1500 Phase 3: finalize:  87%|████████▋ | 637/729 [00:11<00:01, 55.89it/s]

→ 1500 Phase 3: finalize:  88%|████████▊ | 643/729 [00:11<00:01, 55.98it/s]

→ 1500 Phase 3: finalize:  89%|████████▉ | 649/729 [00:11<00:01, 56.06it/s]

→ 1500 Phase 3: finalize:  90%|████████▉ | 655/729 [00:11<00:01, 56.11it/s]

→ 1500 Phase 3: finalize:  91%|█████████ | 661/729 [00:12<00:01, 56.15it/s]

→ 1500 Phase 3: finalize:  91%|█████████▏| 667/729 [00:12<00:01, 55.98it/s]

→ 1500 Phase 3: finalize:  92%|█████████▏| 673/729 [00:12<00:00, 56.03it/s]

→ 1500 Phase 3: finalize:  93%|█████████▎| 679/729 [00:12<00:00, 56.10it/s]

→ 1500 Phase 3: finalize:  94%|█████████▍| 685/729 [00:12<00:00, 55.88it/s]

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→ 1500 Phase 3: finalize:  96%|█████████▌| 697/729 [00:12<00:00, 55.64it/s]

→ 1500 Phase 3: finalize:  96%|█████████▋| 703/729 [00:12<00:00, 55.58it/s]

→ 1500 Phase 3: finalize:  97%|█████████▋| 709/729 [00:12<00:00, 55.64it/s]

→ 1500 Phase 3: finalize:  98%|█████████▊| 715/729 [00:13<00:00, 55.66it/s]

→ 1500 Phase 3: finalize:  99%|█████████▉| 721/729 [00:13<00:00, 55.74it/s]

→ 1500 Phase 3: finalize: 100%|█████████▉| 727/729 [00:13<00:00, 55.72it/s]

                                                                           
[TIMING] 1500 — 729 frames
  Phase 1  radial detect   (parallel)  :  10.56s  (14.5 ms/frame)
  Phase 2a corner detect   (parallel)  :   5.08s  (7.0 ms/frame)
  Phase 2b corner fix      (sequential):   0.49s
  Phase 3  finalize        (sequential):  13.30s  (18.2 ms/frame)
    decode + undistort                 :   7.09s  (9.7 ms/frame)
    corner apply + refinement          :   2.77s  (3.8 ms/frame)
    segment                            :   2.82s  (3.9 ms/frame)
    smooth                             :   0.40s  (0.5 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  29.43s


Processing Rigs:  75%|███████▌  | 3/4 [01:35<00:31, 31.86s/it][INFO] Filtered 565 stationary frames, 499 remain


→ 1000 (499 images) Phase 1:   0%|          | 0/499 [00:00<?, ?it/s]

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→ 1000 (499 images) Phase 1:   2%|▏         | 9/499 [00:01<01:02,  7.85it/s]

→ 1000 (499 images) Phase 1:   6%|▌         | 29/499 [00:01<00:15, 29.58it/s]

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→ 1000 (499 images) Phase 1:  14%|█▍        | 71/499 [00:02<00:09, 45.96it/s]

→ 1000 (499 images) Phase 1:  18%|█▊        | 91/499 [00:02<00:06, 67.06it/s]

→ 1000 (499 images) Phase 1:  21%|██        | 103/499 [00:02<00:07, 54.40it/s]

→ 1000 (499 images) Phase 1:  25%|██▍       | 124/499 [00:02<00:04, 76.51it/s]

→ 1000 (499 images) Phase 1:  27%|██▋       | 137/499 [00:03<00:05, 60.82it/s]

→ 1000 (499 images) Phase 1:  31%|███▏      | 156/499 [00:03<00:04, 79.52it/s]

→ 1000 (499 images) Phase 1:  34%|███▍      | 169/499 [00:03<00:05, 62.84it/s]

→ 1000 (499 images) Phase 1:  38%|███▊      | 189/499 [00:03<00:03, 83.18it/s]

→ 1000 (499 images) Phase 1:  40%|████      | 202/499 [00:04<00:04, 64.10it/s]

→ 1000 (499 images) Phase 1:  45%|████▍     | 223/499 [00:04<00:03, 84.56it/s]

→ 1000 (499 images) Phase 1:  47%|████▋     | 236/499 [00:04<00:04, 64.83it/s]

→ 1000 (499 images) Phase 1:  51%|█████▏    | 256/499 [00:04<00:03, 80.21it/s]

→ 1000 (499 images) Phase 1:  54%|█████▎    | 268/499 [00:05<00:03, 65.18it/s]

→ 1000 (499 images) Phase 1:  57%|█████▋    | 286/499 [00:05<00:02, 81.90it/s]

→ 1000 (499 images) Phase 1:  60%|█████▉    | 298/499 [00:05<00:03, 64.61it/s]

→ 1000 (499 images) Phase 1:  63%|██████▎   | 316/499 [00:05<00:02, 81.56it/s]

→ 1000 (499 images) Phase 1:  66%|██████▌   | 328/499 [00:05<00:02, 63.35it/s]

→ 1000 (499 images) Phase 1:  69%|██████▉   | 345/499 [00:06<00:01, 79.58it/s]

→ 1000 (499 images) Phase 1:  72%|███████▏  | 357/499 [00:06<00:02, 63.10it/s]

→ 1000 (499 images) Phase 1:  75%|███████▍  | 372/499 [00:06<00:01, 76.68it/s]

→ 1000 (499 images) Phase 1:  77%|███████▋  | 385/499 [00:06<00:01, 67.66it/s]

→ 1000 (499 images) Phase 1:  79%|███████▉  | 395/499 [00:06<00:01, 70.61it/s]

→ 1000 (499 images) Phase 1:  82%|████████▏ | 410/499 [00:06<00:01, 82.45it/s]

→ 1000 (499 images) Phase 1:  84%|████████▍ | 420/499 [00:07<00:01, 67.13it/s]

→ 1000 (499 images) Phase 1:  86%|████████▋ | 431/499 [00:07<00:00, 73.63it/s]

→ 1000 (499 images) Phase 1:  89%|████████▉ | 444/499 [00:07<00:00, 84.18it/s]

→ 1000 (499 images) Phase 1:  91%|█████████ | 454/499 [00:07<00:00, 62.43it/s]

→ 1000 (499 images) Phase 1:  94%|█████████▍| 471/499 [00:07<00:00, 81.17it/s]

→ 1000 (499 images) Phase 1:  97%|█████████▋| 482/499 [00:07<00:00, 78.92it/s]

→ 1000 (499 images) Phase 1:  99%|█████████▉| 494/499 [00:08<00:00, 84.91it/s]

                                                                              

→ 1000 Phase 2: corners:   0%|          | 0/499 [00:00<?, ?it/s]

→ 1000 Phase 2: corners:   0%|          | 1/499 [00:01<09:23,  1.13s/it]

→ 1000 Phase 2: corners:   3%|▎         | 17/499 [00:01<00:26, 18.50it/s]

→ 1000 Phase 2: corners:   7%|▋         | 33/499 [00:01<00:12, 37.46it/s]

→ 1000 Phase 2: corners:  10%|▉         | 48/499 [00:01<00:08, 54.34it/s]

→ 1000 Phase 2: corners:  12%|█▏        | 61/499 [00:01<00:06, 67.06it/s]

→ 1000 Phase 2: corners:  15%|█▌        | 75/499 [00:01<00:05, 81.38it/s]

→ 1000 Phase 2: corners:  18%|█▊        | 89/499 [00:01<00:04, 93.69it/s]

→ 1000 Phase 2: corners:  21%|██        | 104/499 [00:01<00:03, 105.44it/s]

→ 1000 Phase 2: corners:  24%|██▍       | 119/499 [00:01<00:03, 115.19it/s]

→ 1000 Phase 2: corners:  27%|██▋       | 133/499 [00:02<00:03, 116.94it/s]

→ 1000 Phase 2: corners:  30%|██▉       | 149/499 [00:02<00:02, 126.83it/s]

→ 1000 Phase 2: corners:  33%|███▎      | 167/499 [00:02<00:02, 139.34it/s]

→ 1000 Phase 2: corners:  36%|███▋      | 182/499 [00:02<00:02, 135.28it/s]

→ 1000 Phase 2: corners:  39%|███▉      | 197/499 [00:02<00:02, 132.55it/s]

→ 1000 Phase 2: corners:  42%|████▏     | 212/499 [00:02<00:02, 132.20it/s]

→ 1000 Phase 2: corners:  45%|████▌     | 226/499 [00:02<00:02, 125.92it/s]

→ 1000 Phase 2: corners:  48%|████▊     | 239/499 [00:02<00:02, 126.25it/s]

→ 1000 Phase 2: corners:  51%|█████     | 254/499 [00:03<00:01, 129.46it/s]

→ 1000 Phase 2: corners:  54%|█████▎    | 268/499 [00:03<00:01, 119.34it/s]

→ 1000 Phase 2: corners:  58%|█████▊    | 287/499 [00:03<00:01, 135.75it/s]

→ 1000 Phase 2: corners:  61%|██████    | 305/499 [00:03<00:01, 143.65it/s]

→ 1000 Phase 2: corners:  64%|██████▍   | 320/499 [00:03<00:01, 143.08it/s]

→ 1000 Phase 2: corners:  68%|██████▊   | 337/499 [00:03<00:01, 146.57it/s]

→ 1000 Phase 2: corners:  71%|███████   | 355/499 [00:03<00:00, 150.10it/s]

→ 1000 Phase 2: corners:  74%|███████▍  | 371/499 [00:03<00:00, 148.96it/s]

→ 1000 Phase 2: corners:  78%|███████▊  | 390/499 [00:03<00:00, 158.76it/s]

→ 1000 Phase 2: corners:  82%|████████▏ | 408/499 [00:04<00:00, 163.29it/s]

→ 1000 Phase 2: corners:  85%|████████▌ | 426/499 [00:04<00:00, 167.90it/s]

→ 1000 Phase 2: corners:  89%|████████▉ | 444/499 [00:04<00:00, 168.20it/s]

→ 1000 Phase 2: corners:  93%|█████████▎| 462/499 [00:04<00:00, 167.10it/s]

                                                                           [PASS2] Frame 0000865: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000916: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000865: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Summary: 2 frames fixed, 1 untrusted, 499 total


→ 1000 Phase 3: finalize:   0%|          | 0/499 [00:00<?, ?it/s]

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→ 1000 Phase 3: finalize:  13%|█▎        | 63/499 [00:00<00:06, 64.16it/s]

→ 1000 Phase 3: finalize:  14%|█▍        | 70/499 [00:01<00:06, 64.03it/s]

→ 1000 Phase 3: finalize:  15%|█▌        | 77/499 [00:01<00:06, 64.01it/s]

→ 1000 Phase 3: finalize:  17%|█▋        | 84/499 [00:01<00:06, 64.03it/s]

→ 1000 Phase 3: finalize:  18%|█▊        | 91/499 [00:01<00:06, 63.93it/s]

→ 1000 Phase 3: finalize:  20%|█▉        | 98/499 [00:01<00:06, 63.87it/s]

→ 1000 Phase 3: finalize:  21%|██        | 105/499 [00:01<00:06, 63.76it/s]

→ 1000 Phase 3: finalize:  22%|██▏       | 112/499 [00:01<00:06, 63.70it/s]

→ 1000 Phase 3: finalize:  24%|██▍       | 119/499 [00:01<00:05, 63.67it/s]

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→ 1000 Phase 3: finalize:  27%|██▋       | 133/499 [00:02<00:05, 63.00it/s]

→ 1000 Phase 3: finalize:  28%|██▊       | 140/499 [00:02<00:05, 62.88it/s]

→ 1000 Phase 3: finalize:  29%|██▉       | 147/499 [00:02<00:05, 62.91it/s]

→ 1000 Phase 3: finalize:  31%|███       | 154/499 [00:02<00:05, 62.85it/s]

→ 1000 Phase 3: finalize:  32%|███▏      | 161/499 [00:02<00:05, 62.80it/s]

→ 1000 Phase 3: finalize:  34%|███▎      | 168/499 [00:02<00:05, 62.71it/s]

→ 1000 Phase 3: finalize:  35%|███▌      | 175/499 [00:02<00:05, 62.57it/s]

→ 1000 Phase 3: finalize:  36%|███▋      | 182/499 [00:02<00:05, 62.40it/s]

→ 1000 Phase 3: finalize:  38%|███▊      | 189/499 [00:02<00:04, 62.34it/s]

→ 1000 Phase 3: finalize:  39%|███▉      | 196/499 [00:03<00:04, 62.42it/s]

→ 1000 Phase 3: finalize:  41%|████      | 203/499 [00:03<00:04, 62.76it/s]

→ 1000 Phase 3: finalize:  42%|████▏     | 210/499 [00:03<00:04, 62.84it/s]

→ 1000 Phase 3: finalize:  43%|████▎     | 217/499 [00:03<00:04, 62.88it/s]

→ 1000 Phase 3: finalize:  45%|████▍     | 224/499 [00:03<00:04, 62.89it/s]

→ 1000 Phase 3: finalize:  46%|████▋     | 231/499 [00:03<00:04, 62.92it/s]

→ 1000 Phase 3: finalize:  48%|████▊     | 238/499 [00:03<00:04, 62.99it/s]

→ 1000 Phase 3: finalize:  49%|████▉     | 245/499 [00:03<00:04, 63.17it/s]

→ 1000 Phase 3: finalize:  51%|█████     | 252/499 [00:03<00:03, 63.27it/s]

→ 1000 Phase 3: finalize:  52%|█████▏    | 259/499 [00:04<00:03, 63.35it/s]

→ 1000 Phase 3: finalize:  53%|█████▎    | 266/499 [00:04<00:03, 63.38it/s]

→ 1000 Phase 3: finalize:  55%|█████▍    | 273/499 [00:04<00:03, 63.37it/s]

→ 1000 Phase 3: finalize:  56%|█████▌    | 280/499 [00:04<00:03, 63.39it/s]

→ 1000 Phase 3: finalize:  58%|█████▊    | 287/499 [00:04<00:03, 63.33it/s]

→ 1000 Phase 3: finalize:  59%|█████▉    | 294/499 [00:04<00:03, 63.23it/s]

→ 1000 Phase 3: finalize:  60%|██████    | 301/499 [00:04<00:03, 63.16it/s]

→ 1000 Phase 3: finalize:  62%|██████▏   | 308/499 [00:04<00:03, 63.11it/s]

→ 1000 Phase 3: finalize:  63%|██████▎   | 315/499 [00:04<00:02, 63.05it/s]

→ 1000 Phase 3: finalize:  65%|██████▍   | 322/499 [00:05<00:02, 62.95it/s]

→ 1000 Phase 3: finalize:  66%|██████▌   | 329/499 [00:05<00:02, 62.70it/s]

→ 1000 Phase 3: finalize:  67%|██████▋   | 336/499 [00:05<00:02, 62.54it/s]

→ 1000 Phase 3: finalize:  69%|██████▊   | 343/499 [00:05<00:02, 62.57it/s]

→ 1000 Phase 3: finalize:  70%|███████   | 350/499 [00:05<00:02, 62.58it/s]

→ 1000 Phase 3: finalize:  72%|███████▏  | 357/499 [00:05<00:02, 62.78it/s]

→ 1000 Phase 3: finalize:  73%|███████▎  | 364/499 [00:05<00:02, 62.98it/s]

→ 1000 Phase 3: finalize:  74%|███████▍  | 371/499 [00:05<00:02, 63.20it/s]

→ 1000 Phase 3: finalize:  76%|███████▌  | 378/499 [00:05<00:01, 63.31it/s]

→ 1000 Phase 3: finalize:  77%|███████▋  | 385/499 [00:06<00:01, 63.35it/s]

→ 1000 Phase 3: finalize:  79%|███████▊  | 392/499 [00:06<00:01, 63.56it/s]

→ 1000 Phase 3: finalize:  80%|███████▉  | 399/499 [00:06<00:01, 63.76it/s]

→ 1000 Phase 3: finalize:  81%|████████▏ | 406/499 [00:06<00:01, 64.00it/s]

→ 1000 Phase 3: finalize:  83%|████████▎ | 413/499 [00:06<00:01, 64.18it/s]

→ 1000 Phase 3: finalize:  84%|████████▍ | 420/499 [00:06<00:01, 64.35it/s]

→ 1000 Phase 3: finalize:  86%|████████▌ | 427/499 [00:06<00:01, 64.52it/s]

→ 1000 Phase 3: finalize:  87%|████████▋ | 434/499 [00:06<00:01, 64.61it/s]

→ 1000 Phase 3: finalize:  88%|████████▊ | 441/499 [00:06<00:00, 64.64it/s]

→ 1000 Phase 3: finalize:  90%|████████▉ | 448/499 [00:07<00:00, 63.80it/s]

→ 1000 Phase 3: finalize:  91%|█████████ | 455/499 [00:07<00:00, 61.59it/s]

→ 1000 Phase 3: finalize:  93%|█████████▎| 462/499 [00:07<00:00, 60.22it/s]

→ 1000 Phase 3: finalize:  94%|█████████▍| 469/499 [00:07<00:00, 59.19it/s]

→ 1000 Phase 3: finalize:  95%|█████████▌| 475/499 [00:07<00:00, 58.46it/s]

→ 1000 Phase 3: finalize:  96%|█████████▋| 481/499 [00:07<00:00, 57.97it/s]

→ 1000 Phase 3: finalize:  98%|█████████▊| 487/499 [00:07<00:00, 57.51it/s]

→ 1000 Phase 3: finalize:  99%|█████████▉| 493/499 [00:07<00:00, 57.17it/s]

→ 1000 Phase 3: finalize: 100%|██████████| 499/499 [00:07<00:00, 56.86it/s]

                                                                           
[TIMING] 1000 — 499 frames
  Phase 1  radial detect   (parallel)  :   8.23s  (16.5 ms/frame)
  Phase 2a corner detect   (parallel)  :   4.57s  (9.2 ms/frame)
  Phase 2b corner fix      (sequential):   0.31s
  Phase 3  finalize        (sequential):   7.97s  (16.0 ms/frame)
    decode + undistort                 :   4.06s  (8.1 ms/frame)
    corner apply + refinement          :   1.62s  (3.2 ms/frame)
    segment                            :   1.87s  (3.7 ms/frame)
    smooth                             :   0.27s  (0.5 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  21.09s


Processing Rigs: 100%|██████████| 4/4 [01:59<00:00, 28.85s/it]
Processing Rigs: 100%|██████████| 4/4 [01:59<00:00, 29.81s/it]
[💾] Saved RigFrameDataset to /working/MDC006_W020(6)_2026-07-10/calibration/debug/1_digitized_full/rig_frames_full.json
[✅] Saved full dataset: 2390 frames from 4 rigs to /working/MDC006_W020(6)_2026-07-10/calibration/debug/1_digitized_full/rig_frames_full.json
[💾] Saved RigFrameDataset to /working/MDC006_W020(6)_2026-07-10/calibration/debug/1_digitized_full/rig_frames_full.json
[📋] Creating calibration subset (100 frames/rig) with visualizations...
[📋] 2000L: 100 frames selected from 584
[📋] 2000R: 100 frames selected from 578
[📋] 1500: 100 frames selected from 729
[📋] 1000: 100 frames selected from 499
[💾] Saved RigFrameDataset to /working/MDC006_W020(6)_2026-07-10/calibration/debug/1_digitized/rig_frames.json
[INFO] Reloading dataset from disk to ensure clean state for multiprocessing...
[📂] Loaded RigFrameDataset from /working/MDC006_W020(6)_2026-07-10/calibration/debug/1_digitized/rig_frames.json

-------------------------------------------------------------------
                      Step 2: Casing Detection                     
-------------------------------------------------------------------

-> Calculating the casing center ...
[INFO] Using 80 total sampled bright frames

Computing max image from bright frames:   0%|          | 0/80 [00:00<?, ?it/s]
Computing max image from bright frames:   1%|▏         | 1/80 [00:04<05:51,  4.45s/it]
Computing max image from bright frames:   2%|▎         | 2/80 [00:04<02:35,  1.99s/it]
Computing max image from bright frames:   5%|▌         | 4/80 [00:04<01:01,  1.24it/s]
Computing max image from bright frames:   6%|▋         | 5/80 [00:05<00:43,  1.70it/s]
Computing max image from bright frames:   8%|▊         | 6/80 [00:05<00:33,  2.19it/s]
Computing max image from bright frames:   9%|▉         | 7/80 [00:05<00:25,  2.87it/s]
Computing max image from bright frames:  11%|█▏        | 9/80 [00:05<00:21,  3.23it/s]
Computing max image from bright frames:  12%|█▎        | 10/80 [00:05<00:19,  3.58it/s]
Computing max image from bright frames:  14%|█▍        | 11/80 [00:06<00:16,  4.10it/s]
Computing max image from bright frames:  16%|█▋        | 13/80 [00:06<00:11,  5.73it/s]
Computing max image from bright frames:  18%|█▊        | 14/80 [00:06<00:12,  5.37it/s]
Computing max image from bright frames:  19%|█▉        | 15/80 [00:06<00:14,  4.48it/s]
Computing max image from bright frames:  21%|██▏       | 17/80 [00:07<00:09,  6.30it/s]
Computing max image from bright frames:  24%|██▍       | 19/80 [00:07<00:08,  7.42it/s]
Computing max image from bright frames:  25%|██▌       | 20/80 [00:07<00:07,  7.61it/s]
Computing max image from bright frames:  26%|██▋       | 21/80 [00:07<00:07,  7.92it/s]
Computing max image from bright frames:  29%|██▉       | 23/80 [00:07<00:07,  7.41it/s]
Computing max image from bright frames:  31%|███▏      | 25/80 [00:07<00:06,  8.55it/s]
Computing max image from bright frames:  34%|███▍      | 27/80 [00:08<00:05,  8.84it/s]
Computing max image from bright frames:  36%|███▋      | 29/80 [00:08<00:07,  7.21it/s]
Computing max image from bright frames:  39%|███▉      | 31/80 [00:08<00:06,  7.91it/s]
Computing max image from bright frames:  40%|████      | 32/80 [00:08<00:06,  7.23it/s]
Computing max image from bright frames:  41%|████▏     | 33/80 [00:10<00:22,  2.12it/s]
Computing max image from bright frames:  42%|████▎     | 34/80 [00:10<00:17,  2.58it/s]
Computing max image from bright frames:  45%|████▌     | 36/80 [00:10<00:11,  3.85it/s]
Computing max image from bright frames:  46%|████▋     | 37/80 [00:10<00:09,  4.42it/s]
Computing max image from bright frames:  48%|████▊     | 38/80 [00:11<00:08,  4.91it/s]
Computing max image from bright frames:  50%|█████     | 40/80 [00:11<00:06,  6.40it/s]
Computing max image from bright frames:  51%|█████▏    | 41/80 [00:11<00:09,  4.33it/s]
Computing max image from bright frames:  52%|█████▎    | 42/80 [00:11<00:08,  4.64it/s]
Computing max image from bright frames:  55%|█████▌    | 44/80 [00:12<00:06,  5.93it/s]
Computing max image from bright frames:  56%|█████▋    | 45/80 [00:12<00:05,  6.28it/s]
Computing max image from bright frames:  57%|█████▊    | 46/80 [00:12<00:05,  5.74it/s]
Computing max image from bright frames:  59%|█████▉    | 47/80 [00:12<00:06,  4.84it/s]
Computing max image from bright frames:  60%|██████    | 48/80 [00:12<00:06,  5.04it/s]
Computing max image from bright frames:  62%|██████▎   | 50/80 [00:13<00:05,  5.20it/s]
Computing max image from bright frames:  66%|██████▋   | 53/80 [00:13<00:03,  8.14it/s]
Computing max image from bright frames:  70%|███████   | 56/80 [00:13<00:02, 10.87it/s]
Computing max image from bright frames:  72%|███████▎  | 58/80 [00:13<00:01, 11.16it/s]
Computing max image from bright frames:  76%|███████▋  | 61/80 [00:14<00:01, 11.45it/s]
Computing max image from bright frames:  79%|███████▉  | 63/80 [00:14<00:01,  9.59it/s]
Computing max image from bright frames:  81%|████████▏ | 65/80 [00:15<00:02,  5.71it/s]
Computing max image from bright frames:  82%|████████▎ | 66/80 [00:15<00:02,  6.04it/s]
Computing max image from bright frames:  86%|████████▋ | 69/80 [00:15<00:01,  7.78it/s]
Computing max image from bright frames:  89%|████████▉ | 71/80 [00:15<00:01,  7.91it/s]
Computing max image from bright frames:  90%|█████████ | 72/80 [00:15<00:01,  7.71it/s]
Computing max image from bright frames:  91%|█████████▏| 73/80 [00:15<00:00,  8.05it/s]
Computing max image from bright frames:  94%|█████████▍| 75/80 [00:16<00:00,  9.39it/s]
Computing max image from bright frames:  96%|█████████▋| 77/80 [00:16<00:00, 10.91it/s]
Computing max image from bright frames: 100%|██████████| 80/80 [00:16<00:00,  8.92it/s]
                                                                                       
[✅] Casing detection complete: cx=1022.0, cy=791.0

-------------------------------------------------------------------
                        Step 3: Calibration                        
-------------------------------------------------------------------


  0%|          | 0/100 [00:00<?, ?it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   0%|          | 0/100 [00:00<?, ?it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   1%|          | 1/100 [00:00<00:27,  3.55it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   1%|          | 1/100 [00:00<00:27,  3.55it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   2%|▏         | 2/100 [00:00<00:27,  3.55it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 321.212} (0.000):   3%|▎         | 3/100 [00:00<00:27,  3.55it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 328.283} (0.000):   4%|▍         | 4/100 [00:00<00:27,  3.55it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 328.283} (0.000):   5%|▌         | 5/100 [00:00<00:06, 14.25it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 335.354} (0.000):   5%|▌         | 5/100 [00:00<00:06, 14.25it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 342.424} (0.000):   6%|▌         | 6/100 [00:00<00:06, 14.25it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 342.424} (0.000):   7%|▋         | 7/100 [00:00<00:06, 13.78it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.002 | Best: {'fx': 363.636} (0.002):   7%|▋         | 7/100 [00:00<00:06, 13.78it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.003 | Best: {'fx': 370.707} (0.003):   8%|▊         | 8/100 [00:00<00:06, 13.78it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.001 | Best: {'fx': 370.707} (0.003):   9%|▉         | 9/100 [00:00<00:06, 13.78it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.004 | Best: {'fx': 384.848} (0.004):  10%|█         | 10/100 [00:00<00:06, 13.78it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.004 | Best: {'fx': 384.848} (0.004):  11%|█         | 11/100 [00:00<00:04, 19.79it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.001 | Best: {'fx': 384.848} (0.004):  11%|█         | 11/100 [00:00<00:04, 19.79it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.003 | Best: {'fx': 384.848} (0.004):  12%|█▏        | 12/100 [00:00<00:04, 19.79it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.005 | Best: {'fx': 406.061} (0.005):  13%|█▎        | 13/100 [00:00<00:04, 19.79it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.005 | Best: {'fx': 406.061} (0.005):  14%|█▍        | 14/100 [00:00<00:03, 21.95it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.004 | Best: {'fx': 406.061} (0.005):  14%|█▍        | 14/100 [00:00<00:03, 21.95it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.005 | Best: {'fx': 413.131} (0.005):  15%|█▌        | 15/100 [00:00<00:03, 21.95it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.004 | Best: {'fx': 413.131} (0.005):  16%|█▌        | 16/100 [00:00<00:03, 21.95it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.006 | Best: {'fx': 420.202} (0.006):  17%|█▋        | 17/100 [00:00<00:03, 21.95it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.006 | Best: {'fx': 420.202} (0.006):  18%|█▊        | 18/100 [00:00<00:03, 26.48it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.006 | Best: {'fx': 427.273} (0.006):  18%|█▊        | 18/100 [00:01<00:03, 26.48it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.011 | Best: {'fx': 448.485} (0.011):  19%|█▉        | 19/100 [00:01<00:03, 26.48it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.008 | Best: {'fx': 448.485} (0.011):  20%|██        | 20/100 [00:01<00:03, 26.48it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.008 | Best: {'fx': 448.485} (0.011):  21%|██        | 21/100 [00:01<00:03, 20.21it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.017 | Best: {'fx': 469.697} (0.017):  21%|██        | 21/100 [00:01<00:03, 20.21it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.009 | Best: {'fx': 469.697} (0.017):  22%|██▏       | 22/100 [00:01<00:03, 20.21it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.021 | Best: {'fx': 476.768} (0.021):  23%|██▎       | 23/100 [00:01<00:03, 20.21it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.013 | Best: {'fx': 476.768} (0.021):  24%|██▍       | 24/100 [00:01<00:03, 20.21it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.015 | Best: {'fx': 476.768} (0.021):  25%|██▌       | 25/100 [00:01<00:03, 20.21it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.031 | Best: {'fx': 490.909} (0.031):  26%|██▌       | 26/100 [00:01<00:03, 20.21it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.031 | Best: {'fx': 490.909} (0.031):  27%|██▋       | 27/100 [00:01<00:02, 28.18it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.024 | Best: {'fx': 490.909} (0.031):  27%|██▋       | 27/100 [00:01<00:02, 28.18it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.039 | Best: {'fx': 497.98} (0.039):  28%|██▊       | 28/100 [00:01<00:02, 28.18it/s] 
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.049 | Best: {'fx': 505.051} (0.049):  29%|██▉       | 29/100 [00:01<00:02, 28.18it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.058 | Best: {'fx': 512.121} (0.058):  30%|███       | 30/100 [00:01<00:02, 28.18it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.058 | Best: {'fx': 512.121} (0.058):  31%|███       | 31/100 [00:01<00:02, 29.44it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.070 | Best: {'fx': 519.192} (0.070):  31%|███       | 31/100 [00:01<00:02, 29.44it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.085 | Best: {'fx': 526.263} (0.085):  32%|███▏      | 32/100 [00:01<00:02, 29.44it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.092 | Best: {'fx': 533.333} (0.092):  33%|███▎      | 33/100 [00:01<00:02, 29.44it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.077 | Best: {'fx': 533.333} (0.092):  34%|███▍      | 34/100 [00:01<00:02, 29.44it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.077 | Best: {'fx': 533.333} (0.092):  35%|███▌      | 35/100 [00:01<00:03, 18.05it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.058 | Best: {'fx': 533.333} (0.092):  35%|███▌      | 35/100 [00:01<00:03, 18.05it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.068 | Best: {'fx': 533.333} (0.092):  36%|███▌      | 36/100 [00:01<00:03, 18.05it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.041 | Best: {'fx': 533.333} (0.092):  37%|███▋      | 37/100 [00:01<00:03, 18.05it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.041 | Best: {'fx': 533.333} (0.092):  38%|███▊      | 38/100 [00:01<00:03, 19.02it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.048 | Best: {'fx': 533.333} (0.092):  38%|███▊      | 38/100 [00:01<00:03, 19.02it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.052 | Best: {'fx': 533.333} (0.092):  39%|███▉      | 39/100 [00:01<00:03, 19.02it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.038 | Best: {'fx': 533.333} (0.092):  40%|████      | 40/100 [00:02<00:03, 19.02it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.038 | Best: {'fx': 533.333} (0.092):  41%|████      | 41/100 [00:02<00:02, 20.70it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.044 | Best: {'fx': 533.333} (0.092):  41%|████      | 41/100 [00:02<00:02, 20.70it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.035 | Best: {'fx': 533.333} (0.092):  42%|████▏     | 42/100 [00:02<00:02, 20.70it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.037 | Best: {'fx': 533.333} (0.092):  43%|████▎     | 43/100 [00:02<00:02, 20.70it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.034 | Best: {'fx': 533.333} (0.092):  44%|████▍     | 44/100 [00:02<00:02, 20.70it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.031 | Best: {'fx': 533.333} (0.092):  45%|████▌     | 45/100 [00:02<00:02, 20.70it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.031 | Best: {'fx': 533.333} (0.092):  46%|████▌     | 46/100 [00:02<00:02, 23.57it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.029 | Best: {'fx': 533.333} (0.092):  46%|████▌     | 46/100 [00:02<00:02, 23.57it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.028 | Best: {'fx': 533.333} (0.092):  47%|████▋     | 47/100 [00:02<00:02, 23.57it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.032 | Best: {'fx': 533.333} (0.092):  48%|████▊     | 48/100 [00:02<00:02, 23.57it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.032 | Best: {'fx': 533.333} (0.092):  49%|████▉     | 49/100 [00:02<00:02, 22.85it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.030 | Best: {'fx': 533.333} (0.092):  49%|████▉     | 49/100 [00:02<00:02, 22.85it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.028 | Best: {'fx': 533.333} (0.092):  50%|█████     | 50/100 [00:02<00:02, 22.85it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.027 | Best: {'fx': 533.333} (0.092):  51%|█████     | 51/100 [00:02<00:02, 22.85it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.027 | Best: {'fx': 533.333} (0.092):  52%|█████▏    | 52/100 [00:02<00:02, 23.68it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.023 | Best: {'fx': 533.333} (0.092):  52%|█████▏    | 52/100 [00:02<00:02, 23.68it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.023 | Best: {'fx': 533.333} (0.092):  53%|█████▎    | 53/100 [00:02<00:01, 23.68it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.024 | Best: {'fx': 533.333} (0.092):  54%|█████▍    | 54/100 [00:02<00:01, 23.68it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.025 | Best: {'fx': 533.333} (0.092):  55%|█████▌    | 55/100 [00:02<00:01, 23.68it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.025 | Best: {'fx': 533.333} (0.092):  56%|█████▌    | 56/100 [00:02<00:01, 25.50it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.022 | Best: {'fx': 533.333} (0.092):  56%|█████▌    | 56/100 [00:02<00:01, 25.50it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.026 | Best: {'fx': 533.333} (0.092):  57%|█████▋    | 57/100 [00:02<00:01, 25.50it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.026 | Best: {'fx': 533.333} (0.092):  58%|█████▊    | 58/100 [00:02<00:01, 25.50it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.022 | Best: {'fx': 533.333} (0.092):  59%|█████▉    | 59/100 [00:02<00:01, 25.50it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.025 | Best: {'fx': 533.333} (0.092):  60%|██████    | 60/100 [00:02<00:01, 25.50it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.022 | Best: {'fx': 533.333} (0.092):  61%|██████    | 61/100 [00:02<00:01, 25.50it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.024 | Best: {'fx': 533.333} (0.092):  62%|██████▏   | 62/100 [00:02<00:01, 25.50it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.024 | Best: {'fx': 533.333} (0.092):  63%|██████▎   | 63/100 [00:02<00:01, 35.74it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.025 | Best: {'fx': 533.333} (0.092):  63%|██████▎   | 63/100 [00:02<00:01, 35.74it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.023 | Best: {'fx': 533.333} (0.092):  64%|██████▍   | 64/100 [00:02<00:01, 35.74it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.022 | Best: {'fx': 533.333} (0.092):  65%|██████▌   | 65/100 [00:02<00:00, 35.74it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.023 | Best: {'fx': 533.333} (0.092):  66%|██████▌   | 66/100 [00:02<00:00, 35.74it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.021 | Best: {'fx': 533.333} (0.092):  67%|██████▋   | 67/100 [00:02<00:00, 35.74it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.021 | Best: {'fx': 533.333} (0.092):  68%|██████▊   | 68/100 [00:02<00:00, 35.74it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.021 | Best: {'fx': 533.333} (0.092):  69%|██████▉   | 69/100 [00:02<00:00, 41.66it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.021 | Best: {'fx': 533.333} (0.092):  69%|██████▉   | 69/100 [00:02<00:00, 41.66it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.021 | Best: {'fx': 533.333} (0.092):  70%|███████   | 70/100 [00:02<00:00, 41.66it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.021 | Best: {'fx': 533.333} (0.092):  71%|███████   | 71/100 [00:02<00:00, 41.66it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.021 | Best: {'fx': 533.333} (0.092):  72%|███████▏  | 72/100 [00:02<00:00, 41.66it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.023 | Best: {'fx': 533.333} (0.092):  73%|███████▎  | 73/100 [00:02<00:00, 41.66it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.021 | Best: {'fx': 533.333} (0.092):  74%|███████▍  | 74/100 [00:02<00:00, 41.66it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.092):  75%|███████▌  | 75/100 [00:02<00:00, 41.66it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.092):  76%|███████▌  | 76/100 [00:02<00:00, 41.05it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.092):  76%|███████▌  | 76/100 [00:02<00:00, 41.05it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.092):  77%|███████▋  | 77/100 [00:02<00:00, 41.05it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.021 | Best: {'fx': 533.333} (0.092):  78%|███████▊  | 78/100 [00:02<00:00, 41.05it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.092):  79%|███████▉  | 79/100 [00:03<00:00, 41.05it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.092):  80%|████████  | 80/100 [00:03<00:00, 41.05it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.092):  81%|████████  | 81/100 [00:03<00:00, 41.05it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.092):  82%|████████▏ | 82/100 [00:03<00:00, 43.05it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.092):  82%|████████▏ | 82/100 [00:03<00:00, 43.05it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.092):  83%|████████▎ | 83/100 [00:03<00:00, 43.05it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.092):  84%|████████▍ | 84/100 [00:03<00:00, 43.05it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.092):  85%|████████▌ | 85/100 [00:03<00:00, 43.05it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.092):  86%|████████▌ | 86/100 [00:03<00:00, 43.05it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.092):  87%|████████▋ | 87/100 [00:03<00:00, 31.39it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.092):  87%|████████▋ | 87/100 [00:03<00:00, 31.39it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.092):  88%|████████▊ | 88/100 [00:03<00:00, 31.39it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.092):  89%|████████▉ | 89/100 [00:03<00:00, 31.39it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.092):  90%|█████████ | 90/100 [00:03<00:00, 31.39it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.092):  91%|█████████ | 91/100 [00:03<00:00, 29.43it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.092):  91%|█████████ | 91/100 [00:03<00:00, 29.43it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.092):  92%|█████████▏| 92/100 [00:03<00:00, 29.43it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.092):  93%|█████████▎| 93/100 [00:03<00:00, 29.43it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.092):  94%|█████████▍| 94/100 [00:03<00:00, 29.43it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.092):  95%|█████████▌| 95/100 [00:03<00:00, 29.43it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.092):  96%|█████████▌| 96/100 [00:03<00:00, 29.43it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.092):  97%|█████████▋| 97/100 [00:03<00:00, 29.43it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.092):  98%|█████████▊| 98/100 [00:03<00:00, 28.37it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.092):  98%|█████████▊| 98/100 [00:03<00:00, 28.37it/s]
Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.092):  99%|█████████▉| 99/100 [00:03<00:00, 28.37it/s]
                                                                                                                                       

  0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.053 | Best: {'fx': 508.333} (0.053):   0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.053 | Best: {'fx': 508.333} (0.053):   2%|▏         | 1/50 [00:00<00:26,  1.85it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.054 | Best: {'fx': 509.354} (0.054):   2%|▏         | 1/50 [00:00<00:26,  1.85it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.055 | Best: {'fx': 510.374} (0.055):   4%|▍         | 2/50 [00:00<00:25,  1.85it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.055 | Best: {'fx': 510.374} (0.055):   6%|▌         | 3/50 [00:00<00:08,  5.35it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.057 | Best: {'fx': 511.395} (0.057):   6%|▌         | 3/50 [00:00<00:08,  5.35it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.058 | Best: {'fx': 512.415} (0.058):   8%|▊         | 4/50 [00:00<00:08,  5.35it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.060 | Best: {'fx': 513.435} (0.060):  10%|█         | 5/50 [00:00<00:08,  5.35it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.060 | Best: {'fx': 513.435} (0.060):  12%|█▏        | 6/50 [00:00<00:04, 10.47it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.062 | Best: {'fx': 514.456} (0.062):  12%|█▏        | 6/50 [00:00<00:04, 10.47it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.065 | Best: {'fx': 516.497} (0.065):  14%|█▍        | 7/50 [00:00<00:04, 10.47it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.065 | Best: {'fx': 516.497} (0.065):  16%|█▌        | 8/50 [00:00<00:03, 11.71it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.067 | Best: {'fx': 517.517} (0.067):  16%|█▌        | 8/50 [00:00<00:03, 11.71it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.069 | Best: {'fx': 518.537} (0.069):  18%|█▊        | 9/50 [00:01<00:03, 11.71it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.074 | Best: {'fx': 520.578} (0.074):  20%|██        | 10/50 [00:01<00:03, 11.71it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.064 | Best: {'fx': 520.578} (0.074):  22%|██▏       | 11/50 [00:01<00:03, 11.71it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.064 | Best: {'fx': 520.578} (0.074):  24%|██▍       | 12/50 [00:01<00:02, 17.28it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.075 | Best: {'fx': 521.599} (0.075):  24%|██▍       | 12/50 [00:01<00:02, 17.28it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.071 | Best: {'fx': 521.599} (0.075):  26%|██▌       | 13/50 [00:01<00:02, 17.28it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.078 | Best: {'fx': 522.619} (0.078):  28%|██▊       | 14/50 [00:01<00:02, 17.28it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.078 | Best: {'fx': 522.619} (0.078):  30%|███       | 15/50 [00:01<00:01, 19.36it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.080 | Best: {'fx': 523.639} (0.080):  30%|███       | 15/50 [00:01<00:01, 19.36it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.081 | Best: {'fx': 524.66} (0.081):  32%|███▏      | 16/50 [00:01<00:01, 19.36it/s] 
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.083 | Best: {'fx': 525.68} (0.083):  34%|███▍      | 17/50 [00:01<00:01, 19.36it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.083 | Best: {'fx': 525.68} (0.083):  36%|███▌      | 18/50 [00:01<00:01, 17.59it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.085 | Best: {'fx': 526.701} (0.085):  36%|███▌      | 18/50 [00:01<00:01, 17.59it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.090 | Best: {'fx': 528.741} (0.090):  38%|███▊      | 19/50 [00:01<00:01, 17.59it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.092 | Best: {'fx': 529.762} (0.092):  40%|████      | 20/50 [00:01<00:01, 17.59it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.088 | Best: {'fx': 529.762} (0.092):  42%|████▏     | 21/50 [00:01<00:01, 17.59it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.093 | Best: {'fx': 530.782} (0.093):  44%|████▍     | 22/50 [00:01<00:01, 17.59it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.093 | Best: {'fx': 530.782} (0.093):  46%|████▌     | 23/50 [00:01<00:01, 19.87it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.092 | Best: {'fx': 530.782} (0.093):  46%|████▌     | 23/50 [00:01<00:01, 19.87it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.091 | Best: {'fx': 530.782} (0.093):  48%|████▊     | 24/50 [00:01<00:01, 19.87it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.074 | Best: {'fx': 530.782} (0.093):  50%|█████     | 25/50 [00:01<00:01, 19.87it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.072 | Best: {'fx': 530.782} (0.093):  52%|█████▏    | 26/50 [00:01<00:01, 19.87it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.072 | Best: {'fx': 530.782} (0.093):  54%|█████▍    | 27/50 [00:01<00:01, 22.57it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.078 | Best: {'fx': 530.782} (0.093):  54%|█████▍    | 27/50 [00:01<00:01, 22.57it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.091 | Best: {'fx': 530.782} (0.093):  56%|█████▌    | 28/50 [00:01<00:00, 22.57it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.076 | Best: {'fx': 530.782} (0.093):  58%|█████▊    | 29/50 [00:01<00:00, 22.57it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.076 | Best: {'fx': 530.782} (0.093):  60%|██████    | 30/50 [00:01<00:00, 22.57it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.093 | Best: {'fx': 530.782} (0.093):  62%|██████▏   | 31/50 [00:01<00:00, 22.57it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.070 | Best: {'fx': 530.782} (0.093):  64%|██████▍   | 32/50 [00:01<00:00, 22.57it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.067 | Best: {'fx': 530.782} (0.093):  66%|██████▌   | 33/50 [00:01<00:00, 22.57it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.067 | Best: {'fx': 530.782} (0.093):  68%|██████▊   | 34/50 [00:01<00:00, 30.77it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.068 | Best: {'fx': 530.782} (0.093):  68%|██████▊   | 34/50 [00:01<00:00, 30.77it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.089 | Best: {'fx': 530.782} (0.093):  70%|███████   | 35/50 [00:01<00:00, 30.77it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.087 | Best: {'fx': 530.782} (0.093):  72%|███████▏  | 36/50 [00:01<00:00, 30.77it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.072 | Best: {'fx': 530.782} (0.093):  74%|███████▍  | 37/50 [00:01<00:00, 30.77it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.084 | Best: {'fx': 530.782} (0.093):  76%|███████▌  | 38/50 [00:01<00:00, 30.77it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.064 | Best: {'fx': 530.782} (0.093):  78%|███████▊  | 39/50 [00:01<00:00, 30.77it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.062 | Best: {'fx': 530.782} (0.093):  80%|████████  | 40/50 [00:01<00:00, 30.77it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.065 | Best: {'fx': 530.782} (0.093):  82%|████████▏ | 41/50 [00:01<00:00, 30.77it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.081 | Best: {'fx': 530.782} (0.093):  84%|████████▍ | 42/50 [00:01<00:00, 30.77it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.081 | Best: {'fx': 530.782} (0.093):  86%|████████▌ | 43/50 [00:01<00:00, 42.70it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.060 | Best: {'fx': 530.782} (0.093):  86%|████████▌ | 43/50 [00:01<00:00, 42.70it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.058 | Best: {'fx': 530.782} (0.093):  88%|████████▊ | 44/50 [00:02<00:00, 42.70it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.061 | Best: {'fx': 530.782} (0.093):  90%|█████████ | 45/50 [00:02<00:00, 42.70it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.056 | Best: {'fx': 530.782} (0.093):  92%|█████████▏| 46/50 [00:02<00:00, 42.70it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.055 | Best: {'fx': 530.782} (0.093):  94%|█████████▍| 47/50 [00:02<00:00, 42.70it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.055 | Best: {'fx': 530.782} (0.093):  96%|█████████▌| 48/50 [00:02<00:00, 39.24it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.057 | Best: {'fx': 530.782} (0.093):  96%|█████████▌| 48/50 [00:02<00:00, 39.24it/s]
Brute | Start: {'fx': 533.333} (0.092) | Current: 0.054 | Best: {'fx': 530.782} (0.093):  98%|█████████▊| 49/50 [00:02<00:00, 39.24it/s]
                                                                                                                                        
[DEBUG] Parameters after Step 5 (before square optimization):
    fx: 530.7823129251701
    px: 1022.0
    py: 791.0
    k1: 0.0
    k2: 0.0
    k3: 0.0
    k4: 0.0
    p1: 0.0
    p2: 0.0
    p3: 0.0
    p4: 0.0
    scale: 3.0
    rotation: 0.0


[🔲] Square Reference Optimization
    Including tangential distortion parameters (p1, p2, p3, p4) in joint optimization
  Selecting up to 20 frames per rig (excluded 0 incomplete frames): 80 frames will be used for optimization
  Rigs: 2000L(2000mm):20/20, 2000R(2000mm):20/20, 1500(1500mm):20/20, 1000(1000mm):20/20
  Total: 80/80 frames used for optimization

Initial score: 24.9991: 0iter [00:00, ?iter/s][DEBUG] objective(x0) = 24.9991, picklable_objective(x0) = 25.0166

Best score: 25.0166: : 0iter [00:01, ?iter/s] 
Best score: 25.0166: : 1iter [00:01,  2.00s/iter]
Best score: 25.0166: : 1iter [00:02,  2.00s/iter]
Best score: 25.0166: : 2iter [00:02,  2.00s/iter]
Best score: 25.0166: : 3iter [00:02,  1.72iter/s]
Best score: 25.0166: : 3iter [00:02,  1.72iter/s]
Best score: 25.0166: : 4iter [00:02,  1.72iter/s]
Best score: 25.0166: : 5iter [00:02,  3.06iter/s]
Best score: 25.0166: : 5iter [00:02,  3.06iter/s]
Best score: 25.0166: : 6iter [00:02,  3.06iter/s]
Best score: 25.0166: : 7iter [00:02,  4.46iter/s]
Best score: 25.0166: : 7iter [00:02,  4.46iter/s]
Best score: 25.0166: : 8iter [00:02,  4.46iter/s]
Best score: 25.0166: : 9iter [00:02,  5.82iter/s]
Best score: 25.0166: : 9iter [00:02,  5.82iter/s]
Best score: 25.0166: : 10iter [00:02,  5.82iter/s]
Best score: 25.0166: : 11iter [00:02,  7.00iter/s]
Best score: 25.0166: : 11iter [00:02,  7.00iter/s]
Best score: 25.0166: : 12iter [00:03,  7.00iter/s]
Best score: 25.0166: : 13iter [00:03,  8.08iter/s]
Best score: 25.0166: : 13iter [00:03,  8.08iter/s]
Best score: 25.0166: : 14iter [00:03,  8.08iter/s]
Best score: 25.0166: : 15iter [00:03,  9.00iter/s]
Best score: 25.0166: : 15iter [00:03,  9.00iter/s]
Best score: 25.0166: : 16iter [00:03,  9.00iter/s]
Best score: 25.0166: : 17iter [00:03,  9.69iter/s]
Best score: 25.0166: : 17iter [00:03,  9.69iter/s]
Best score: 25.0166: : 18iter [00:03,  9.69iter/s]
Best score: 25.0166: : 19iter [00:03, 10.24iter/s]
Best score: 25.0166: : 19iter [00:03, 10.24iter/s]
Best score: 25.0166: : 20iter [00:03, 10.24iter/s]
Best score: 25.0166: : 21iter [00:03, 10.52iter/s]
Best score: 25.0166: : 21iter [00:03, 10.52iter/s]
Best score: 25.0166: : 22iter [00:03, 10.52iter/s]
Best score: 25.0166: : 23iter [00:03, 10.86iter/s]
Best score: 25.0166: : 23iter [00:03, 10.86iter/s]
Best score: 25.0166: : 24iter [00:04, 10.86iter/s]
Best score: 25.0166: : 25iter [00:04, 11.10iter/s]
Best score: 25.0166: : 25iter [00:04, 11.10iter/s]
Best score: 25.0166: : 26iter [00:04, 11.10iter/s]
Best score: 25.0166: : 27iter [00:04, 11.28iter/s]
Best score: 25.0166: : 27iter [00:04, 11.28iter/s]
Best score: 25.0166: : 28iter [00:04, 11.28iter/s]
Best score: 25.0166: : 29iter [00:04, 11.39iter/s]
Best score: 25.0166: : 29iter [00:04, 11.39iter/s]
Best score: 25.0166: : 30iter [00:04, 11.39iter/s]
Best score: 25.0166: : 31iter [00:04, 11.30iter/s]
Best score: 25.0166: : 31iter [00:04, 11.30iter/s]
Best score: 25.0166: : 32iter [00:04, 11.30iter/s]
Best score: 25.0166: : 33iter [00:04, 11.41iter/s]
Best score: 25.0166: : 33iter [00:04, 11.41iter/s]
Best score: 25.0166: : 34iter [00:04, 11.41iter/s]
Best score: 25.0166: : 35iter [00:04, 11.50iter/s]
Best score: 25.0166: : 35iter [00:05, 11.50iter/s]
Best score: 25.0166: : 36iter [00:05, 11.50iter/s]
Best score: 25.0166: : 37iter [00:05, 11.58iter/s]
Best score: 25.0166: : 37iter [00:05, 11.58iter/s]
Best score: 25.0166: : 38iter [00:05, 11.58iter/s]
Best score: 25.0166: : 39iter [00:05, 11.62iter/s]
Best score: 25.0166: : 39iter [00:05, 11.62iter/s]
Best score: 25.0166: : 40iter [00:05, 11.62iter/s]
Best score: 25.0166: : 41iter [00:05, 11.51iter/s]
Best score: 25.0166: : 41iter [00:05, 11.51iter/s]
Best score: 25.0166: : 42iter [00:05, 11.51iter/s]
Best score: 25.0166: : 43iter [00:05, 11.59iter/s]
Best score: 25.0166: : 43iter [00:05, 11.59iter/s]
Best score: 25.0166: : 44iter [00:05, 11.59iter/s]
Best score: 25.0166: : 45iter [00:05, 11.68iter/s]
Best score: 25.0166: : 45iter [00:05, 11.68iter/s]
Best score: 25.0166: : 46iter [00:05, 11.68iter/s]
Best score: 25.0166: : 47iter [00:05, 11.71iter/s]
Best score: 25.0166: : 47iter [00:06, 11.71iter/s]
Best score: 25.0166: : 48iter [00:06, 11.71iter/s]
Best score: 25.0166: : 49iter [00:06, 11.77iter/s]
[ITER 50] Best: 25.0166
[PARAMS] Current best parameters:
  fx: 530.7823
  fy: 530.7823
  px: 1022.0000
  py: 791.0000
  k1: 0.00000000
  k2: -0.00000000
  k3: 0.00000000
  k4: 0.00000000
  p1: 0.00000000
  p2: 0.00000000
  p3: 0.00000000
  p4: 0.00000000
  s1: 0.0000
  s2: 0.0000
  s3: 0.0000
  s4: 0.0000
  tilt_x: 0.0000
  tilt_y: 0.0000
  scale: 3.0000
  rotation: 0.0000

Best score: 25.0166: : 49iter [00:06, 11.77iter/s]
Best score: 25.0166: : 50iter [00:06, 11.77iter/s]
Best score: 25.0166: : 51iter [00:06, 11.64iter/s]
Best score: 25.0166: : 51iter [00:06, 11.64iter/s]
Best score: 25.0166: : 52iter [00:06, 11.64iter/s]
Best score: 25.0166: : 53iter [00:06, 11.72iter/s]
Best score: 25.0166: : 53iter [00:06, 11.72iter/s]
Best score: 25.0166: : 54iter [00:06, 11.72iter/s]
Best score: 25.0166: : 55iter [00:06, 11.76iter/s]
Best score: 25.0166: : 55iter [00:06, 11.76iter/s]
Best score: 25.0166: : 56iter [00:06, 11.76iter/s]
Best score: 25.0166: : 57iter [00:06, 11.74iter/s]
Best score: 25.0166: : 57iter [00:06, 11.74iter/s]
Best score: 25.0166: : 58iter [00:06, 11.74iter/s]
Best score: 25.0166: : 59iter [00:06, 11.78iter/s]
Best score: 25.0166: : 59iter [00:07, 11.78iter/s]
Best score: 25.0166: : 60iter [00:07, 11.78iter/s]
Best score: 25.0166: : 61iter [00:07, 11.68iter/s]
Best score: 25.0166: : 61iter [00:07, 11.68iter/s]
Best score: 25.0166: : 62iter [00:07, 11.68iter/s]
Best score: 25.0166: : 63iter [00:07, 11.72iter/s]
Best score: 25.0166: : 63iter [00:07, 11.72iter/s]
Best score: 25.0166: : 64iter [00:07, 11.72iter/s]
Best score: 25.0166: : 65iter [00:07, 11.79iter/s]
Best score: 25.0166: : 65iter [00:07, 11.79iter/s]
Best score: 25.0166: : 66iter [00:07, 11.79iter/s]
Best score: 25.0166: : 67iter [00:07, 11.80iter/s]
Best score: 25.0166: : 67iter [00:07, 11.80iter/s]
Best score: 25.0166: : 68iter [00:07, 11.80iter/s]
Best score: 25.0166: : 69iter [00:07, 11.82iter/s]
Best score: 21.6626: : 69iter [00:07, 11.82iter/s]
Best score: 21.6626: : 70iter [00:07, 11.82iter/s]
Best score: 21.6626: : 71iter [00:07, 11.62iter/s]
Best score: 21.6626: : 71iter [00:08, 11.62iter/s]
Best score: 21.6626: : 72iter [00:08, 11.62iter/s]
Best score: 21.6626: : 73iter [00:08, 11.73iter/s]
Best score: 21.6626: : 73iter [00:08, 11.73iter/s]
Best score: 21.6626: : 74iter [00:08, 11.73iter/s]
Best score: 21.6626: : 75iter [00:08, 11.80iter/s]
Best score: 21.6626: : 75iter [00:08, 11.80iter/s]
Best score: 21.6626: : 76iter [00:08, 11.80iter/s]
Best score: 21.6626: : 77iter [00:08, 11.81iter/s]
Best score: 21.6626: : 77iter [00:08, 11.81iter/s]
Best score: 21.6626: : 78iter [00:08, 11.81iter/s]
Best score: 21.6626: : 79iter [00:08, 11.84iter/s]
Best score: 21.6626: : 79iter [00:08, 11.84iter/s]
Best score: 21.6626: : 80iter [00:08, 11.84iter/s]
Best score: 21.6626: : 81iter [00:08, 11.56iter/s]
Best score: 21.6626: : 81iter [00:08, 11.56iter/s]
Best score: 21.6626: : 82iter [00:09, 11.56iter/s]
Best score: 21.6626: : 83iter [00:09, 11.64iter/s]
Best score: 21.6626: : 83iter [00:09, 11.64iter/s]
Best score: 21.6626: : 84iter [00:09, 11.64iter/s]
Best score: 21.6626: : 85iter [00:09, 11.68iter/s]
Best score: 21.6626: : 85iter [00:09, 11.68iter/s]
Best score: 21.6626: : 86iter [00:09, 11.68iter/s]
Best score: 21.6626: : 87iter [00:09, 11.70iter/s]
Best score: 21.6626: : 87iter [00:09, 11.70iter/s]
Best score: 21.6626: : 88iter [00:09, 11.70iter/s]
Best score: 21.6626: : 89iter [00:09, 11.75iter/s]
Best score: 19.3953: : 89iter [00:09, 11.75iter/s]
Best score: 19.3953: : 90iter [00:09, 11.75iter/s]
Best score: 19.3953: : 91iter [00:09, 11.64iter/s]
Best score: 19.3953: : 91iter [00:09, 11.64iter/s]
Best score: 19.3953: : 92iter [00:09, 11.64iter/s]
Best score: 19.3953: : 93iter [00:09, 11.71iter/s]
Best score: 19.3953: : 93iter [00:09, 11.71iter/s]
Best score: 19.3953: : 94iter [00:10, 11.71iter/s]
Best score: 19.3953: : 95iter [00:10, 11.72iter/s]
Best score: 19.3953: : 95iter [00:10, 11.72iter/s]
Best score: 19.3953: : 96iter [00:10, 11.72iter/s]
Best score: 19.3953: : 97iter [00:10, 11.79iter/s]
Best score: 19.3953: : 97iter [00:10, 11.79iter/s]
Best score: 19.3953: : 98iter [00:10, 11.79iter/s]
Best score: 19.3953: : 99iter [00:10, 11.83iter/s]
[ITER 100] Best: 10.2878
[PARAMS] Current best parameters:
  fx: 545.7359
  fy: 538.8590
  px: 1007.8910
  py: 801.4114
  k1: -0.07428369
  k2: 0.07809420
  k3: -0.03458410
  k4: 0.00578062
  p1: -0.00825926
  p2: -0.00743420
  p3: -0.00924215
  p4: -0.00300221
  s1: -0.0107
  s2: 0.0075
  s3: 0.0072
  s4: 0.0210
  tilt_x: 0.0551
  tilt_y: 0.0864
  scale: 3.0723
  rotation: 0.3381

Best score: 10.2878: : 99iter [00:10, 11.83iter/s]
Best score: 10.2878: : 100iter [00:10, 11.83iter/s]
Best score: 10.2878: : 101iter [00:10, 10.13iter/s]
Best score: 10.2878: : 101iter [00:10, 10.13iter/s]
Best score: 10.2878: : 102iter [00:10, 10.13iter/s]
Best score: 10.2878: : 103iter [00:10, 10.55iter/s]
Best score: 10.2878: : 103iter [00:10, 10.55iter/s]
Best score: 10.2878: : 104iter [00:11, 10.55iter/s]
Best score: 10.2878: : 105iter [00:11, 10.14iter/s]
Best score: 10.2878: : 105iter [00:11, 10.14iter/s]
Best score: 10.2878: : 106iter [00:11, 10.14iter/s]
Best score: 10.2878: : 107iter [00:11, 10.52iter/s]
Best score: 10.2878: : 107iter [00:11, 10.52iter/s]
Best score: 10.2878: : 108iter [00:11, 10.52iter/s]
Best score: 10.2878: : 109iter [00:11, 10.82iter/s]
Best score: 10.2878: : 109iter [00:11, 10.82iter/s]
Best score: 10.2878: : 110iter [00:11, 10.82iter/s]
Best score: 10.2878: : 111iter [00:11, 10.85iter/s]
Best score: 10.2878: : 111iter [00:11, 10.85iter/s]
Best score: 10.2878: : 112iter [00:11, 10.85iter/s]
Best score: 10.2878: : 113iter [00:11, 11.11iter/s]
Best score: 10.2878: : 113iter [00:11, 11.11iter/s]
Best score: 10.2878: : 114iter [00:11, 11.11iter/s]
Best score: 10.2878: : 115iter [00:11, 11.29iter/s]
Best score: 10.2878: : 115iter [00:11, 11.29iter/s]
Best score: 10.2878: : 116iter [00:12, 11.29iter/s]
Best score: 10.2878: : 117iter [00:12, 11.41iter/s]
Best score: 10.2878: : 117iter [00:12, 11.41iter/s]
Best score: 10.2878: : 118iter [00:12, 11.41iter/s]
Best score: 10.2878: : 119iter [00:12, 11.49iter/s]
Best score: 10.2878: : 119iter [00:12, 11.49iter/s]
Best score: 10.2878: : 120iter [00:12, 11.49iter/s]
Best score: 10.2878: : 121iter [00:12, 11.38iter/s]
Best score: 10.2878: : 121iter [00:12, 11.38iter/s]
Best score: 10.2878: : 122iter [00:12, 11.38iter/s]
Best score: 10.2878: : 123iter [00:12, 11.48iter/s]
Best score: 10.2878: : 123iter [00:12, 11.48iter/s]
Best score: 10.2878: : 124iter [00:12, 11.48iter/s]
Best score: 10.2878: : 125iter [00:12, 11.53iter/s]
Best score: 10.2878: : 125iter [00:12, 11.53iter/s]
Best score: 10.2878: : 126iter [00:12, 11.53iter/s]
Best score: 10.2878: : 127iter [00:12, 11.58iter/s]
Best score: 10.2878: : 127iter [00:13, 11.58iter/s]
Best score: 10.2878: : 128iter [00:13, 11.58iter/s]
Best score: 10.2878: : 129iter [00:13, 11.62iter/s]
Best score: 10.2878: : 129iter [00:13, 11.62iter/s]
Best score: 10.2878: : 130iter [00:13, 11.62iter/s]
Best score: 10.2878: : 131iter [00:13, 11.44iter/s]
Best score: 10.2878: : 131iter [00:13, 11.44iter/s]
Best score: 10.2878: : 132iter [00:13, 11.44iter/s]
Best score: 10.2878: : 133iter [00:13, 11.55iter/s]
Best score: 10.2878: : 133iter [00:13, 11.55iter/s]
Best score: 10.2878: : 134iter [00:13, 11.55iter/s]
Best score: 10.2878: : 135iter [00:13, 11.67iter/s]
Best score: 10.2878: : 135iter [00:13, 11.67iter/s]
Best score: 10.2878: : 136iter [00:13, 11.67iter/s]
Best score: 10.2878: : 137iter [00:13, 11.74iter/s]
Best score: 10.2878: : 137iter [00:13, 11.74iter/s]
Best score: 10.2878: : 138iter [00:13, 11.74iter/s]
Best score: 10.2878: : 139iter [00:13, 11.76iter/s]
Best score: 10.2878: : 139iter [00:14, 11.76iter/s]
Best score: 10.2878: : 140iter [00:14, 11.76iter/s]
Best score: 10.2878: : 141iter [00:14, 11.64iter/s]
Best score: 10.2878: : 141iter [00:14, 11.64iter/s]
Best score: 10.2878: : 142iter [00:14, 11.64iter/s]
Best score: 10.2878: : 143iter [00:14, 11.72iter/s]
Best score: 10.2878: : 143iter [00:14, 11.72iter/s]
Best score: 10.2878: : 144iter [00:14, 11.72iter/s]
Best score: 10.2878: : 145iter [00:14, 11.78iter/s]
Best score: 10.2878: : 145iter [00:14, 11.78iter/s]
Best score: 10.2878: : 146iter [00:14, 11.78iter/s]
Best score: 10.2878: : 147iter [00:14, 11.79iter/s]
Best score: 10.2878: : 147iter [00:14, 11.79iter/s]
Best score: 10.2878: : 148iter [00:14, 11.79iter/s]
Best score: 10.2878: : 149iter [00:14, 11.76iter/s]
[ITER 150] Best: 10.2878
[PARAMS] Current best parameters:
  fx: 545.7359
  fy: 538.8590
  px: 1007.8910
  py: 801.4114
  k1: -0.07428369
  k2: 0.07809420
  k3: -0.03458410
  k4: 0.00578062
  p1: -0.00825926
  p2: -0.00743420
  p3: -0.00924215
  p4: -0.00300221
  s1: -0.0107
  s2: 0.0075
  s3: 0.0072
  s4: 0.0210
  tilt_x: 0.0551
  tilt_y: 0.0864
  scale: 3.0723
  rotation: 0.3381

Best score: 10.2878: : 149iter [00:14, 11.76iter/s]
Best score: 10.2878: : 150iter [00:15, 11.76iter/s]
Best score: 10.2878: : 151iter [00:15,  7.54iter/s]
Best score: 10.2878: : 151iter [00:15,  7.54iter/s]
Best score: 10.2878: : 152iter [00:15,  7.54iter/s]
Best score: 10.2878: : 153iter [00:15,  8.46iter/s]
Best score: 10.2878: : 153iter [00:15,  8.46iter/s]
Best score: 10.2878: : 154iter [00:15,  8.46iter/s]
Best score: 10.2878: : 155iter [00:15,  9.28iter/s]
Best score: 10.2878: : 155iter [00:15,  9.28iter/s]
Best score: 10.2878: : 156iter [00:15,  9.28iter/s]
Best score: 10.2878: : 157iter [00:15,  9.93iter/s]
Best score: 10.2878: : 157iter [00:15,  9.93iter/s]
Best score: 10.2878: : 158iter [00:15,  9.93iter/s]
Best score: 10.2878: : 159iter [00:15, 10.47iter/s]
Best score: 10.2878: : 159iter [00:16, 10.47iter/s]
Best score: 10.2878: : 160iter [00:16, 10.47iter/s]
Best score: 10.2878: : 161iter [00:16, 10.69iter/s]
Best score: 10.2878: : 161iter [00:16, 10.69iter/s]
Best score: 10.2878: : 162iter [00:16, 10.69iter/s]
Best score: 10.2878: : 163iter [00:16, 11.02iter/s]
Best score: 10.2878: : 163iter [00:16, 11.02iter/s]
Best score: 10.2878: : 164iter [00:16, 11.02iter/s]
Best score: 10.2878: : 165iter [00:16, 11.24iter/s]
Best score: 10.2878: : 165iter [00:16, 11.24iter/s]
Best score: 10.2878: : 166iter [00:16, 11.24iter/s]
Best score: 10.2878: : 167iter [00:16, 11.42iter/s]
Best score: 10.2878: : 167iter [00:16, 11.42iter/s]
Best score: 10.2878: : 168iter [00:16, 11.42iter/s]
Best score: 10.2878: : 169iter [00:16, 11.51iter/s]
Best score: 10.2878: : 169iter [00:16, 11.51iter/s]
Best score: 10.2878: : 170iter [00:17, 11.51iter/s]
Best score: 10.2878: : 171iter [00:17, 11.45iter/s]
Best score: 10.2878: : 171iter [00:17, 11.45iter/s]
Best score: 10.2878: : 172iter [00:17, 11.45iter/s]
Best score: 10.2878: : 173iter [00:17, 11.61iter/s]
Best score: 10.2878: : 173iter [00:17, 11.61iter/s]
Best score: 10.2878: : 174iter [00:17, 11.61iter/s]
Best score: 10.2878: : 175iter [00:17, 11.67iter/s]
Best score: 10.2878: : 175iter [00:17, 11.67iter/s]
Best score: 10.2878: : 176iter [00:17, 11.67iter/s]
Best score: 10.2878: : 177iter [00:17, 11.69iter/s]
Best score: 10.2878: : 177iter [00:17, 11.69iter/s]
Best score: 10.2878: : 178iter [00:17, 11.69iter/s]
Best score: 10.2878: : 179iter [00:17, 11.78iter/s]
Best score: 4.5911: : 179iter [00:17, 11.78iter/s] 
Best score: 4.5911: : 180iter [00:17, 11.78iter/s]
Best score: 4.5911: : 181iter [00:17, 11.62iter/s]
Best score: 4.5911: : 181iter [00:17, 11.62iter/s]
Best score: 4.5911: : 182iter [00:18, 11.62iter/s]
Best score: 4.5911: : 183iter [00:18, 11.69iter/s]
Best score: 4.5911: : 183iter [00:18, 11.69iter/s]
Best score: 4.5911: : 184iter [00:18, 11.69iter/s]
Best score: 4.5911: : 185iter [00:18, 11.74iter/s]
Best score: 4.5911: : 185iter [00:18, 11.74iter/s]
Best score: 4.5911: : 186iter [00:18, 11.74iter/s]
Best score: 4.5911: : 187iter [00:18, 11.77iter/s]
Best score: 4.5911: : 187iter [00:18, 11.77iter/s]
Best score: 4.5911: : 188iter [00:18, 11.77iter/s]
Best score: 4.5911: : 189iter [00:18, 11.77iter/s]
Best score: 3.5732: : 189iter [00:18, 11.77iter/s]
Best score: 3.5732: : 190iter [00:18, 11.77iter/s]
Best score: 3.5732: : 191iter [00:18, 11.60iter/s]
Best score: 3.5732: : 191iter [00:18, 11.60iter/s]
Best score: 3.5732: : 192iter [00:18, 11.60iter/s]
Best score: 3.5732: : 193iter [00:18, 11.61iter/s]
Best score: 3.5732: : 193iter [00:18, 11.61iter/s]
Best score: 3.5732: : 194iter [00:19, 11.61iter/s]
Best score: 3.5732: : 195iter [00:19, 11.63iter/s]
Best score: 3.5732: : 195iter [00:19, 11.63iter/s]
Best score: 3.5732: : 196iter [00:19, 11.63iter/s]
Best score: 3.5732: : 197iter [00:19, 11.64iter/s]
Best score: 3.5732: : 197iter [00:19, 11.64iter/s]
Best score: 3.5732: : 198iter [00:19, 11.64iter/s]
Best score: 3.5732: : 199iter [00:19, 11.69iter/s]
Best score: 2.6418: : 199iter [00:19, 11.69iter/s]
[ITER 200] Best: 2.6418
[PARAMS] Current best parameters:
  fx: 550.0944
  fy: 548.0582
  px: 1013.6767
  py: 801.9574
  k1: -0.07937242
  k2: 0.08052997
  k3: -0.03696073
  k4: 0.00583066
  p1: 0.00282674
  p2: -0.00037508
  p3: -0.02799859
  p4: 0.00528164
  s1: 0.0076
  s2: 0.0057
  s3: 0.0165
  s4: 0.0172
  tilt_x: 0.0217
  tilt_y: 0.0890
  scale: 3.0895
  rotation: -0.2550

Best score: 2.6418: : 200iter [00:19, 11.69iter/s]
Best score: 2.6418: : 201iter [00:19,  7.55iter/s]
Best score: 2.6418: : 201iter [00:19,  7.55iter/s]
Best score: 2.6418: : 202iter [00:20,  7.55iter/s]
Best score: 2.6418: : 203iter [00:20,  8.47iter/s]
Best score: 2.6418: : 203iter [00:20,  8.47iter/s]
Best score: 2.6418: : 204iter [00:20,  8.47iter/s]
Best score: 2.6418: : 205iter [00:20,  9.28iter/s]
Best score: 2.6418: : 205iter [00:20,  9.28iter/s]
Best score: 2.6418: : 206iter [00:20,  9.28iter/s]
Best score: 2.6418: : 207iter [00:20,  9.87iter/s]
Best score: 2.6418: : 207iter [00:20,  9.87iter/s]
Best score: 2.6418: : 208iter [00:20,  9.87iter/s]
Best score: 2.6418: : 209iter [00:20, 10.38iter/s]
Best score: 1.9135: : 209iter [00:20, 10.38iter/s]
Best score: 1.9135: : 210iter [00:20, 10.38iter/s]
Best score: 1.9135: : 211iter [00:20, 10.57iter/s]
Best score: 1.9135: : 211iter [00:20, 10.57iter/s]
Best score: 1.9135: : 212iter [00:20, 10.57iter/s]
Best score: 1.9135: : 213iter [00:20, 10.87iter/s]
Best score: 1.9135: : 213iter [00:20, 10.87iter/s]
Best score: 1.9135: : 214iter [00:21, 10.87iter/s]
Best score: 1.9135: : 215iter [00:21, 11.12iter/s]
Best score: 1.9135: : 215iter [00:21, 11.12iter/s]
Best score: 1.9135: : 216iter [00:21, 11.12iter/s]
Best score: 1.9135: : 217iter [00:21, 11.31iter/s]
Best score: 1.9135: : 217iter [00:21, 11.31iter/s]
Best score: 1.9135: : 218iter [00:21, 11.31iter/s]
Best score: 1.9135: : 219iter [00:21, 11.48iter/s]
Best score: 1.9135: : 219iter [00:21, 11.48iter/s]
Best score: 1.9135: : 220iter [00:21, 11.48iter/s]
Best score: 1.9135: : 221iter [00:21, 11.42iter/s]
Best score: 1.9135: : 221iter [00:21, 11.42iter/s]
Best score: 1.9135: : 222iter [00:21, 11.42iter/s]
Best score: 1.9135: : 223iter [00:21, 11.45iter/s]
Best score: 1.9135: : 223iter [00:21, 11.45iter/s]
Best score: 1.9135: : 224iter [00:21, 11.45iter/s]
Best score: 1.9135: : 225iter [00:21, 11.52iter/s]
Best score: 1.9135: : 225iter [00:22, 11.52iter/s]
Best score: 1.9135: : 226iter [00:22, 11.52iter/s]
Best score: 1.9135: : 227iter [00:22, 11.60iter/s]
Best score: 1.9135: : 227iter [00:22, 11.60iter/s]
Best score: 1.9135: : 228iter [00:22, 11.60iter/s]
Best score: 1.9135: : 229iter [00:22, 11.61iter/s]
Best score: 1.7122: : 229iter [00:22, 11.61iter/s]
Best score: 1.7122: : 230iter [00:22, 11.61iter/s]
Best score: 1.7122: : 231iter [00:22, 11.42iter/s]
Best score: 1.7122: : 231iter [00:22, 11.42iter/s]
Best score: 1.7122: : 232iter [00:22, 11.42iter/s]
Best score: 1.7122: : 233iter [00:22, 11.54iter/s]
Best score: 1.7122: : 233iter [00:22, 11.54iter/s]
Best score: 1.7122: : 234iter [00:22, 11.54iter/s]
Best score: 1.7122: : 235iter [00:22, 11.58iter/s]
Best score: 1.7122: : 235iter [00:22, 11.58iter/s]
Best score: 1.7122: : 236iter [00:22, 11.58iter/s]
Best score: 1.7122: : 237iter [00:22, 11.59iter/s]
Best score: 1.7122: : 237iter [00:23, 11.59iter/s]
Best score: 1.7122: : 238iter [00:23, 11.59iter/s]
Best score: 1.7122: : 239iter [00:23, 11.64iter/s]
Best score: 1.3039: : 239iter [00:23, 11.64iter/s]
Best score: 1.3039: : 240iter [00:23, 11.64iter/s]
Best score: 1.3039: : 241iter [00:23, 11.49iter/s]
Best score: 1.3039: : 241iter [00:23, 11.49iter/s]
Best score: 1.3039: : 242iter [00:23, 11.49iter/s]
Best score: 1.3039: : 243iter [00:23, 11.55iter/s]
Best score: 1.3039: : 243iter [00:23, 11.55iter/s]
Best score: 1.3039: : 244iter [00:23, 11.55iter/s]
Best score: 1.3039: : 245iter [00:23, 11.60iter/s]
Best score: 1.3039: : 245iter [00:23, 11.60iter/s]
Best score: 1.3039: : 246iter [00:23, 11.60iter/s]
Best score: 1.3039: : 247iter [00:23, 11.68iter/s]
Best score: 1.3039: : 247iter [00:23, 11.68iter/s]
Best score: 1.3039: : 248iter [00:23, 11.68iter/s]
Best score: 1.3039: : 249iter [00:23, 11.75iter/s]
[ITER 250] Best: 1.0139
[PARAMS] Current best parameters:
  fx: 550.1996
  fy: 551.1679
  px: 1005.9662
  py: 801.5456
  k1: -0.04579751
  k2: 0.07063835
  k3: -0.05911282
  k4: 0.01589392
  p1: 0.00111024
  p2: -0.01634136
  p3: -0.01558807
  p4: -0.00184659
  s1: 0.0107
  s2: 0.0084
  s3: 0.0167
  s4: 0.0076
  tilt_x: 0.0317
  tilt_y: 0.0924
  scale: 3.0133
  rotation: 0.0828

Best score: 1.0139: : 249iter [00:24, 11.75iter/s]
Best score: 1.0139: : 250iter [00:24, 11.75iter/s]
Best score: 1.0139: : 251iter [00:24,  7.55iter/s]
Best score: 1.0139: : 251iter [00:24,  7.55iter/s]
Best score: 1.0139: : 252iter [00:24,  7.55iter/s]
Best score: 1.0139: : 253iter [00:24,  8.50iter/s]
Best score: 1.0139: : 253iter [00:24,  8.50iter/s]
Best score: 1.0139: : 254iter [00:24,  8.50iter/s]
Best score: 1.0139: : 255iter [00:24,  9.30iter/s]
Best score: 1.0139: : 255iter [00:24,  9.30iter/s]
Best score: 1.0139: : 256iter [00:24,  9.30iter/s]
Best score: 1.0139: : 257iter [00:24,  9.98iter/s]
Best score: 1.0139: : 257iter [00:25,  9.98iter/s]
Best score: 1.0139: : 258iter [00:25,  9.98iter/s]
Best score: 1.0139: : 259iter [00:25, 10.47iter/s]
Best score: 1.0139: : 259iter [00:25, 10.47iter/s]
Best score: 1.0139: : 260iter [00:25, 10.47iter/s]
Best score: 1.0139: : 261iter [00:25, 10.69iter/s]
Best score: 1.0139: : 261iter [00:25, 10.69iter/s]
Best score: 1.0139: : 262iter [00:25, 10.69iter/s]
Best score: 1.0139: : 263iter [00:25, 11.01iter/s]
Best score: 1.0139: : 263iter [00:25, 11.01iter/s]
Best score: 1.0139: : 264iter [00:25, 11.01iter/s]
Best score: 1.0139: : 265iter [00:25,  8.57iter/s]
Best score: 1.0139: : 265iter [00:25,  8.57iter/s]
Best score: 1.0139: : 266iter [00:26,  8.57iter/s]
Best score: 1.0139: : 267iter [00:26,  9.36iter/s]
Best score: 1.0139: : 267iter [00:26,  9.36iter/s]
Best score: 1.0139: : 268iter [00:26,  9.36iter/s]
Best score: 1.0139: : 269iter [00:26,  9.94iter/s]
Best score: 0.8030: : 269iter [00:26,  9.94iter/s]
Best score: 0.8030: : 270iter [00:26,  9.94iter/s]
Best score: 0.8030: : 271iter [00:26, 10.24iter/s]
Best score: 0.8030: : 271iter [00:26, 10.24iter/s]
Best score: 0.8030: : 272iter [00:26, 10.24iter/s]
Best score: 0.8030: : 273iter [00:26, 10.70iter/s]
Best score: 0.8030: : 273iter [00:26, 10.70iter/s]
Best score: 0.8030: : 274iter [00:26, 10.70iter/s]
Best score: 0.8030: : 275iter [00:26, 10.97iter/s]
Best score: 0.8030: : 275iter [00:26, 10.97iter/s]
Best score: 0.8030: : 276iter [00:26, 10.97iter/s]
Best score: 0.8030: : 277iter [00:26, 11.25iter/s]
Best score: 0.8030: : 277iter [00:26, 11.25iter/s]
Best score: 0.8030: : 278iter [00:27, 11.25iter/s]
Best score: 0.8030: : 279iter [00:27, 11.45iter/s]
Best score: 0.6812: : 279iter [00:27, 11.45iter/s]
Best score: 0.6812: : 280iter [00:27, 11.45iter/s]
Best score: 0.6812: : 281iter [00:27, 11.41iter/s]
Best score: 0.6812: : 281iter [00:27, 11.41iter/s]
Best score: 0.6812: : 282iter [00:27, 11.41iter/s]
Best score: 0.6812: : 283iter [00:27, 11.53iter/s]
Best score: 0.6812: : 283iter [00:27, 11.53iter/s]
Best score: 0.6812: : 284iter [00:27, 11.53iter/s]
Best score: 0.6812: : 285iter [00:27, 11.67iter/s]
Best score: 0.6812: : 285iter [00:27, 11.67iter/s]
Best score: 0.6812: : 286iter [00:27, 11.67iter/s]
Best score: 0.6812: : 287iter [00:27, 11.66iter/s]
Best score: 0.6812: : 287iter [00:27, 11.66iter/s]
Best score: 0.6812: : 288iter [00:27, 11.66iter/s]
Best score: 0.6812: : 289iter [00:27, 11.66iter/s]
Best score: 0.5364: : 289iter [00:28, 11.66iter/s]
Best score: 0.5364: : 290iter [00:28, 11.66iter/s]
Best score: 0.5364: : 291iter [00:28, 11.49iter/s]
Best score: 0.5364: : 291iter [00:28, 11.49iter/s]
Best score: 0.5364: : 292iter [00:28, 11.49iter/s]
Best score: 0.5364: : 293iter [00:28, 11.56iter/s]
Best score: 0.5364: : 293iter [00:28, 11.56iter/s]
Best score: 0.5364: : 294iter [00:28, 11.56iter/s]
Best score: 0.5364: : 295iter [00:28, 11.56iter/s]
Best score: 0.5364: : 295iter [00:28, 11.56iter/s]
Best score: 0.5364: : 296iter [00:28, 11.56iter/s]
Best score: 0.5364: : 297iter [00:28, 11.59iter/s]
Best score: 0.5364: : 297iter [00:28, 11.59iter/s]
Best score: 0.5364: : 298iter [00:28, 11.59iter/s]
Best score: 0.5364: : 299iter [00:28, 11.60iter/s]
[ITER 300] Best: 0.5245
[PARAMS] Current best parameters:
  fx: 561.0910
  fy: 560.9436
  px: 1009.5646
  py: 793.2175
  k1: -0.07488238
  k2: 0.07492423
  k3: -0.04483104
  k4: 0.00981938
  p1: 0.00149950
  p2: -0.01641462
  p3: -0.01734725
  p4: 0.00497992
  s1: 0.0130
  s2: 0.0056
  s3: 0.0122
  s4: 0.0027
  tilt_x: -0.0140
  tilt_y: 0.0802
  scale: 3.0473
  rotation: -0.1256

Best score: 0.5245: : 299iter [00:28, 11.60iter/s]
Best score: 0.5245: : 300iter [00:29, 11.60iter/s]
Best score: 0.5245: : 301iter [00:29,  7.35iter/s]
Best score: 0.5245: : 301iter [00:29,  7.35iter/s]
Best score: 0.5245: : 302iter [00:29,  7.35iter/s]
Best score: 0.5245: : 303iter [00:29,  8.30iter/s]
Best score: 0.5245: : 303iter [00:29,  8.30iter/s]
Best score: 0.5245: : 304iter [00:29,  8.30iter/s]
Best score: 0.5245: : 305iter [00:29,  9.11iter/s]
Best score: 0.5245: : 305iter [00:29,  9.11iter/s]
Best score: 0.5245: : 306iter [00:29,  9.11iter/s]
Best score: 0.5245: : 307iter [00:29,  9.82iter/s]
Best score: 0.5245: : 307iter [00:29,  9.82iter/s]
Best score: 0.5245: : 308iter [00:29,  9.82iter/s]
Best score: 0.5245: : 309iter [00:29, 10.37iter/s]
Best score: 0.4921: : 309iter [00:30, 10.37iter/s]
Best score: 0.4921: : 310iter [00:30, 10.37iter/s]
Best score: 0.4921: : 311iter [00:30, 10.58iter/s]
Best score: 0.4921: : 311iter [00:30, 10.58iter/s]
Best score: 0.4921: : 312iter [00:30, 10.58iter/s]
Best score: 0.4921: : 313iter [00:30, 10.91iter/s]
Best score: 0.4921: : 313iter [00:30, 10.91iter/s]
Best score: 0.4921: : 314iter [00:30, 10.91iter/s]
Best score: 0.4921: : 315iter [00:30, 11.18iter/s]
Best score: 0.4921: : 315iter [00:30, 11.18iter/s]
Best score: 0.4921: : 316iter [00:30, 11.18iter/s]
Best score: 0.4921: : 317iter [00:30, 11.36iter/s]
Best score: 0.4921: : 317iter [00:30, 11.36iter/s]
Best score: 0.4921: : 318iter [00:30, 11.36iter/s]
Best score: 0.4921: : 319iter [00:30, 11.48iter/s]
Best score: 0.4474: : 319iter [00:30, 11.48iter/s]
Best score: 0.4474: : 320iter [00:30, 11.48iter/s]
Best score: 0.4474: : 321iter [00:30, 11.39iter/s]
Best score: 0.4474: : 321iter [00:31, 11.39iter/s]
Best score: 0.4474: : 322iter [00:31, 11.39iter/s]
Best score: 0.4474: : 323iter [00:31, 11.53iter/s]
Best score: 0.4474: : 323iter [00:31, 11.53iter/s]
Best score: 0.4474: : 324iter [00:31, 11.53iter/s]
Best score: 0.4474: : 325iter [00:31, 11.61iter/s]
Best score: 0.4474: : 325iter [00:31, 11.61iter/s]
Best score: 0.4474: : 326iter [00:31, 11.61iter/s]
Best score: 0.4474: : 327iter [00:31, 11.65iter/s]
Best score: 0.4474: : 327iter [00:31, 11.65iter/s]
Best score: 0.4474: : 328iter [00:31, 11.65iter/s]
Best score: 0.4474: : 329iter [00:31, 11.70iter/s]
Best score: 0.4474: : 329iter [00:31, 11.70iter/s]
Best score: 0.4474: : 330iter [00:31, 11.70iter/s]
Best score: 0.4474: : 331iter [00:31, 11.53iter/s]
Best score: 0.4474: : 331iter [00:31, 11.53iter/s]
Best score: 0.4474: : 332iter [00:32, 11.53iter/s]
Best score: 0.4474: : 333iter [00:32, 11.62iter/s]
Best score: 0.4474: : 333iter [00:32, 11.62iter/s]
Best score: 0.4474: : 334iter [00:32, 11.62iter/s]
Best score: 0.4474: : 335iter [00:32, 11.67iter/s]
Best score: 0.4474: : 335iter [00:32, 11.67iter/s]
Best score: 0.4474: : 336iter [00:32, 11.67iter/s]
Best score: 0.4474: : 337iter [00:32, 11.74iter/s]
Best score: 0.4474: : 337iter [00:32, 11.74iter/s]
Best score: 0.4474: : 338iter [00:32, 11.74iter/s]
Best score: 0.4474: : 339iter [00:32, 11.72iter/s]
Best score: 0.4036: : 339iter [00:32, 11.72iter/s]
Best score: 0.4036: : 340iter [00:32, 11.72iter/s]
Best score: 0.4036: : 341iter [00:32, 11.53iter/s]
Best score: 0.4036: : 341iter [00:32, 11.53iter/s]
Best score: 0.4036: : 342iter [00:32, 11.53iter/s]
Best score: 0.4036: : 343iter [00:32, 11.61iter/s]
Best score: 0.4036: : 343iter [00:32, 11.61iter/s]
Best score: 0.4036: : 344iter [00:33, 11.61iter/s]
Best score: 0.4036: : 345iter [00:33, 11.63iter/s]
Best score: 0.4036: : 345iter [00:33, 11.63iter/s]
Best score: 0.4036: : 346iter [00:33, 11.63iter/s]
Best score: 0.4036: : 347iter [00:33, 11.63iter/s]
Best score: 0.4036: : 347iter [00:33, 11.63iter/s]
Best score: 0.4036: : 348iter [00:33, 11.63iter/s]
Best score: 0.4036: : 349iter [00:33, 11.69iter/s]
[ITER 350] Best: 0.4036
[PARAMS] Current best parameters:
  fx: 558.7142
  fy: 558.3609
  px: 1010.2480
  py: 789.5543
  k1: -0.07775439
  k2: 0.09125985
  k3: -0.05982773
  k4: 0.01404181
  p1: 0.00194400
  p2: -0.01431879
  p3: -0.01544027
  p4: 0.00308911
  s1: 0.0108
  s2: 0.0037
  s3: 0.0124
  s4: 0.0001
  tilt_x: -0.0358
  tilt_y: 0.0780
  scale: 3.0492
  rotation: -0.1725

Best score: 0.4036: : 349iter [00:33, 11.69iter/s]
Best score: 0.4036: : 350iter [00:33, 11.69iter/s]
Best score: 0.4036: : 351iter [00:33,  7.52iter/s]
Best score: 0.4036: : 351iter [00:33,  7.52iter/s]
Best score: 0.4036: : 352iter [00:34,  7.52iter/s]
Best score: 0.4036: : 353iter [00:34,  8.45iter/s]
Best score: 0.4036: : 353iter [00:34,  8.45iter/s]
Best score: 0.4036: : 354iter [00:34,  8.45iter/s]
Best score: 0.4036: : 355iter [00:34,  9.23iter/s]
Best score: 0.4036: : 355iter [00:34,  9.23iter/s]
Best score: 0.4036: : 356iter [00:34,  9.23iter/s]
Best score: 0.4036: : 357iter [00:34,  9.86iter/s]
Best score: 0.4036: : 357iter [00:34,  9.86iter/s]
Best score: 0.4036: : 358iter [00:34,  9.86iter/s]
Best score: 0.4036: : 359iter [00:34, 10.37iter/s]
Best score: 0.3732: : 359iter [00:34, 10.37iter/s]
Best score: 0.3732: : 360iter [00:34, 10.37iter/s]
Best score: 0.3732: : 361iter [00:34, 10.55iter/s]
Best score: 0.3732: : 361iter [00:34, 10.55iter/s]
Best score: 0.3732: : 362iter [00:34, 10.55iter/s]
Best score: 0.3732: : 363iter [00:34, 10.88iter/s]
Best score: 0.3732: : 363iter [00:34, 10.88iter/s]
Best score: 0.3732: : 364iter [00:35, 10.88iter/s]
Best score: 0.3732: : 365iter [00:35, 11.13iter/s]
Best score: 0.3732: : 365iter [00:35, 11.13iter/s]
Best score: 0.3732: : 366iter [00:35, 11.13iter/s]
Best score: 0.3732: : 367iter [00:35, 11.29iter/s]
Best score: 0.3732: : 367iter [00:35, 11.29iter/s]
Best score: 0.3732: : 368iter [00:35, 11.29iter/s]
Best score: 0.3732: : 369iter [00:35, 11.37iter/s]
Best score: 0.3732: : 369iter [00:35, 11.37iter/s]
Best score: 0.3732: : 370iter [00:35, 11.37iter/s]
Best score: 0.3732: : 371iter [00:35, 11.28iter/s]
Best score: 0.3732: : 371iter [00:35, 11.28iter/s]
Best score: 0.3732: : 372iter [00:35, 11.28iter/s]
Best score: 0.3732: : 373iter [00:35, 11.43iter/s]
Best score: 0.3732: : 373iter [00:35, 11.43iter/s]
Best score: 0.3732: : 374iter [00:35, 11.43iter/s]
Best score: 0.3732: : 375iter [00:35, 11.55iter/s]
Best score: 0.3732: : 375iter [00:36, 11.55iter/s]
Best score: 0.3732: : 376iter [00:36, 11.55iter/s]
Best score: 0.3732: : 377iter [00:36, 11.66iter/s]
Best score: 0.3732: : 377iter [00:36, 11.66iter/s]
Best score: 0.3732: : 378iter [00:36, 11.66iter/s]
Best score: 0.3732: : 379iter [00:36, 11.73iter/s]
Best score: 0.3597: : 379iter [00:36, 11.73iter/s]
Best score: 0.3597: : 380iter [00:36, 11.73iter/s]
Best score: 0.3597: : 381iter [00:36, 11.50iter/s]
Best score: 0.3597: : 381iter [00:36, 11.50iter/s]
Best score: 0.3597: : 382iter [00:36, 11.50iter/s]
Best score: 0.3597: : 383iter [00:36, 11.55iter/s]
Best score: 0.3597: : 383iter [00:36, 11.55iter/s]
Best score: 0.3597: : 384iter [00:36, 11.55iter/s]
Best score: 0.3597: : 385iter [00:36, 11.61iter/s]
Best score: 0.3597: : 385iter [00:36, 11.61iter/s]
Best score: 0.3597: : 386iter [00:36, 11.61iter/s]
Best score: 0.3597: : 387iter [00:36, 11.65iter/s]
Best score: 0.3597: : 387iter [00:37, 11.65iter/s]
Best score: 0.3597: : 388iter [00:37, 11.65iter/s]
Best score: 0.3597: : 389iter [00:37, 11.67iter/s]
Best score: 0.3294: : 389iter [00:37, 11.67iter/s]
Best score: 0.3294: : 390iter [00:37, 11.67iter/s]
Best score: 0.3294: : 391iter [00:37, 11.54iter/s]
Best score: 0.3294: : 391iter [00:37, 11.54iter/s]
Best score: 0.3294: : 392iter [00:37, 11.54iter/s]
Best score: 0.3294: : 393iter [00:37, 11.63iter/s]
Best score: 0.3294: : 393iter [00:37, 11.63iter/s]
Best score: 0.3294: : 394iter [00:37, 11.63iter/s]
Best score: 0.3294: : 395iter [00:37, 11.74iter/s]
Best score: 0.3294: : 395iter [00:37, 11.74iter/s]
Best score: 0.3294: : 396iter [00:37, 11.74iter/s]
Best score: 0.3294: : 397iter [00:37, 11.72iter/s]
Best score: 0.3294: : 397iter [00:37, 11.72iter/s]
Best score: 0.3294: : 398iter [00:37, 11.72iter/s]
Best score: 0.3294: : 399iter [00:37, 11.76iter/s]
[ITER 400] Best: 0.3252
[PARAMS] Current best parameters:
  fx: 550.5179
  fy: 549.7926
  px: 1017.2710
  py: 789.4450
  k1: -0.07346424
  k2: 0.09375089
  k3: -0.05806924
  k4: 0.01260433
  p1: 0.00098541
  p2: -0.00351096
  p3: -0.00304478
  p4: 0.00360809
  s1: 0.0033
  s2: -0.0033
  s3: 0.0035
  s4: -0.0059
  tilt_x: -0.0302
  tilt_y: 0.0641
  scale: 3.0520
  rotation: -0.2137

Best score: 0.3252: : 399iter [00:38, 11.76iter/s]
Best score: 0.3252: : 400iter [00:38, 11.76iter/s]
Best score: 0.3252: : 401iter [00:38,  7.53iter/s]
Best score: 0.3252: : 401iter [00:38,  7.53iter/s]
Best score: 0.3252: : 402iter [00:38,  7.53iter/s]
Best score: 0.3252: : 403iter [00:38,  8.46iter/s]
Best score: 0.3252: : 403iter [00:38,  8.46iter/s]
Best score: 0.3252: : 404iter [00:38,  8.46iter/s]
Best score: 0.3252: : 405iter [00:38,  9.24iter/s]
Best score: 0.3252: : 405iter [00:38,  9.24iter/s]
Best score: 0.3252: : 406iter [00:38,  9.24iter/s]
Best score: 0.3252: : 407iter [00:38,  9.87iter/s]
Best score: 0.3252: : 407iter [00:39,  9.87iter/s]
Best score: 0.3252: : 408iter [00:39,  9.87iter/s]
Best score: 0.3252: : 409iter [00:39, 10.33iter/s]
Best score: 0.3080: : 409iter [00:39, 10.33iter/s]
Best score: 0.3080: : 410iter [00:39, 10.33iter/s]
Best score: 0.3080: : 411iter [00:39, 10.57iter/s]
Best score: 0.3080: : 411iter [00:39, 10.57iter/s]
Best score: 0.3080: : 412iter [00:39, 10.57iter/s]
Best score: 0.3080: : 413iter [00:39, 10.88iter/s]
Best score: 0.3080: : 413iter [00:39, 10.88iter/s]
Best score: 0.3080: : 414iter [00:39, 10.88iter/s]
Best score: 0.3080: : 415iter [00:39, 11.16iter/s]
Best score: 0.3080: : 415iter [00:39, 11.16iter/s]
Best score: 0.3080: : 416iter [00:39, 11.16iter/s]
Best score: 0.3080: : 417iter [00:39, 11.38iter/s]
Best score: 0.3080: : 417iter [00:39, 11.38iter/s]
Best score: 0.3080: : 418iter [00:40, 11.38iter/s]
Best score: 0.3080: : 419iter [00:40, 11.50iter/s]
Best score: 0.2985: : 419iter [00:40, 11.50iter/s]
Best score: 0.2985: : 420iter [00:40, 11.50iter/s]
Best score: 0.2985: : 421iter [00:40, 11.40iter/s]
Best score: 0.2985: : 421iter [00:40, 11.40iter/s]
Best score: 0.2985: : 422iter [00:40, 11.40iter/s]
Best score: 0.2985: : 423iter [00:40, 11.02iter/s]
Best score: 0.2985: : 423iter [00:40, 11.02iter/s]
Best score: 0.2985: : 424iter [00:40, 11.02iter/s]
Best score: 0.2985: : 425iter [00:40, 11.07iter/s]
Best score: 0.2985: : 425iter [00:40, 11.07iter/s]
Best score: 0.2985: : 426iter [00:40, 11.07iter/s]
Best score: 0.2985: : 427iter [00:40, 10.79iter/s]
Best score: 0.2985: : 427iter [00:40, 10.79iter/s]
Best score: 0.2985: : 428iter [00:40, 10.79iter/s]
Best score: 0.2985: : 429iter [00:40, 11.04iter/s]
Best score: 0.2950: : 429iter [00:41, 11.04iter/s]
Best score: 0.2950: : 430iter [00:41, 11.04iter/s]
Best score: 0.2950: : 431iter [00:41, 11.11iter/s]
Best score: 0.2950: : 431iter [00:41, 11.11iter/s]
Best score: 0.2950: : 432iter [00:41, 11.11iter/s]
Best score: 0.2950: : 433iter [00:41, 11.32iter/s]
Best score: 0.2950: : 433iter [00:41, 11.32iter/s]
Best score: 0.2950: : 434iter [00:41, 11.32iter/s]
Best score: 0.2950: : 435iter [00:41, 11.50iter/s]
Best score: 0.2950: : 435iter [00:41, 11.50iter/s]
Best score: 0.2950: : 436iter [00:41, 11.50iter/s]
Best score: 0.2950: : 437iter [00:41, 11.60iter/s]
Best score: 0.2950: : 437iter [00:41, 11.60iter/s]
Best score: 0.2950: : 438iter [00:41, 11.60iter/s]
Best score: 0.2950: : 439iter [00:41, 11.63iter/s]
Best score: 0.2950: : 439iter [00:41, 11.63iter/s]
Best score: 0.2950: : 440iter [00:41, 11.63iter/s]
Best score: 0.2950: : 441iter [00:41, 11.01iter/s]
Best score: 0.2950: : 441iter [00:42, 11.01iter/s]
Best score: 0.2950: : 442iter [00:42, 11.01iter/s]
Best score: 0.2950: : 443iter [00:42, 11.19iter/s]
Best score: 0.2950: : 443iter [00:42, 11.19iter/s]
Best score: 0.2950: : 444iter [00:42, 11.19iter/s]
Best score: 0.2950: : 445iter [00:42, 11.34iter/s]
Best score: 0.2950: : 445iter [00:42, 11.34iter/s]
Best score: 0.2950: : 446iter [00:42, 11.34iter/s]
Best score: 0.2950: : 447iter [00:42, 11.46iter/s]
Best score: 0.2950: : 447iter [00:42, 11.46iter/s]
Best score: 0.2950: : 448iter [00:42, 11.46iter/s]
Best score: 0.2950: : 449iter [00:42, 11.56iter/s]
[ITER 450] Best: 0.2890
[PARAMS] Current best parameters:
  fx: 560.6300
  fy: 560.1099
  px: 1013.7457
  py: 789.0309
  k1: -0.07224480
  k2: 0.07275371
  k3: -0.04334209
  k4: 0.00934343
  p1: -0.00199329
  p2: -0.01129162
  p3: -0.00713318
  p4: 0.00413071
  s1: 0.0086
  s2: -0.0015
  s3: 0.0082
  s4: -0.0038
  tilt_x: -0.0274
  tilt_y: 0.0668
  scale: 3.0392
  rotation: -0.1520

Best score: 0.2890: : 449iter [00:42, 11.56iter/s]
Best score: 0.2890: : 450iter [00:43, 11.56iter/s]
Best score: 0.2890: : 451iter [00:43,  7.51iter/s]
Best score: 0.2890: : 451iter [00:43,  7.51iter/s]
Best score: 0.2890: : 452iter [00:43,  7.51iter/s]
Best score: 0.2890: : 453iter [00:43,  8.44iter/s]
Best score: 0.2890: : 453iter [00:43,  8.44iter/s]
Best score: 0.2890: : 454iter [00:43,  8.44iter/s]
Best score: 0.2890: : 455iter [00:43,  9.25iter/s]
Best score: 0.2890: : 455iter [00:43,  9.25iter/s]
Best score: 0.2890: : 456iter [00:43,  9.25iter/s]
Best score: 0.2890: : 457iter [00:43,  9.87iter/s]
Best score: 0.2890: : 457iter [00:43,  9.87iter/s]
Best score: 0.2890: : 458iter [00:43,  9.87iter/s]
Best score: 0.2890: : 459iter [00:43, 10.39iter/s]
Best score: 0.2823: : 459iter [00:43, 10.39iter/s]
Best score: 0.2823: : 460iter [00:44, 10.39iter/s]
Best score: 0.2823: : 461iter [00:44, 10.60iter/s]
Best score: 0.2823: : 461iter [00:44, 10.60iter/s]
Best score: 0.2823: : 462iter [00:44, 10.60iter/s]
Best score: 0.2823: : 463iter [00:44, 10.92iter/s]
Best score: 0.2823: : 463iter [00:44, 10.92iter/s]
Best score: 0.2823: : 464iter [00:44, 10.92iter/s]
Best score: 0.2823: : 465iter [00:44, 11.19iter/s]
Best score: 0.2823: : 465iter [00:44, 11.19iter/s]
Best score: 0.2823: : 466iter [00:44, 11.19iter/s]
Best score: 0.2823: : 467iter [00:44, 11.36iter/s]
Best score: 0.2823: : 467iter [00:44, 11.36iter/s]
Best score: 0.2823: : 468iter [00:44, 11.36iter/s]
Best score: 0.2823: : 469iter [00:44, 11.54iter/s]
Best score: 0.2740: : 469iter [00:44, 11.54iter/s]
Best score: 0.2740: : 470iter [00:44, 11.54iter/s]
Best score: 0.2740: : 471iter [00:44, 11.44iter/s]
Best score: 0.2740: : 471iter [00:44, 11.44iter/s]
Best score: 0.2740: : 472iter [00:45, 11.44iter/s]
Best score: 0.2740: : 473iter [00:45, 11.60iter/s]
Best score: 0.2740: : 473iter [00:45, 11.60iter/s]
Best score: 0.2740: : 474iter [00:45, 11.60iter/s]
Best score: 0.2740: : 475iter [00:45, 11.72iter/s]
Best score: 0.2740: : 475iter [00:45, 11.72iter/s]
Best score: 0.2740: : 476iter [00:45, 11.72iter/s]
Best score: 0.2740: : 477iter [00:45, 11.80iter/s]
Best score: 0.2740: : 477iter [00:45, 11.80iter/s]
Best score: 0.2740: : 478iter [00:45, 11.80iter/s]
Best score: 0.2740: : 479iter [00:45, 11.81iter/s]
Best score: 0.2730: : 479iter [00:45, 11.81iter/s]
Best score: 0.2730: : 480iter [00:45, 11.81iter/s]
Best score: 0.2730: : 481iter [00:45, 11.62iter/s]
Best score: 0.2730: : 481iter [00:45, 11.62iter/s]
Best score: 0.2730: : 482iter [00:45, 11.62iter/s]
Best score: 0.2730: : 483iter [00:45, 11.72iter/s]
Best score: 0.2730: : 483iter [00:45, 11.72iter/s]
Best score: 0.2730: : 484iter [00:46, 11.72iter/s]
Best score: 0.2730: : 485iter [00:46, 11.72iter/s]
Best score: 0.2730: : 485iter [00:46, 11.72iter/s]
Best score: 0.2730: : 486iter [00:46, 11.72iter/s]
Best score: 0.2730: : 487iter [00:46,  9.93iter/s]
Best score: 0.2730: : 487iter [00:46,  9.93iter/s]
Best score: 0.2730: : 488iter [00:46,  9.93iter/s]
Best score: 0.2730: : 489iter [00:46,  9.28iter/s]
Best score: 0.2730: : 489iter [00:46,  9.28iter/s]
Best score: 0.2730: : 490iter [00:46,  8.58iter/s]
Best score: 0.2730: : 490iter [00:46,  8.58iter/s]
Best score: 0.2730: : 491iter [00:46,  8.20iter/s]
Best score: 0.2730: : 491iter [00:47,  8.20iter/s]
Best score: 0.2730: : 492iter [00:47,  7.64iter/s]
Best score: 0.2730: : 492iter [00:47,  7.64iter/s]
Best score: 0.2730: : 493iter [00:47,  7.41iter/s]
Best score: 0.2730: : 493iter [00:47,  7.41iter/s]
Best score: 0.2730: : 494iter [00:47,  7.23iter/s]
Best score: 0.2730: : 494iter [00:47,  7.23iter/s]
Best score: 0.2730: : 495iter [00:47,  7.20iter/s]
Best score: 0.2730: : 495iter [00:47,  7.20iter/s]
Best score: 0.2730: : 496iter [00:47,  7.11iter/s]
Best score: 0.2730: : 496iter [00:47,  7.11iter/s]
Best score: 0.2730: : 497iter [00:47,  7.05iter/s]
Best score: 0.2730: : 497iter [00:47,  7.05iter/s]
Best score: 0.2730: : 498iter [00:47,  6.94iter/s]
Best score: 0.2730: : 498iter [00:48,  6.94iter/s]
Best score: 0.2730: : 499iter [00:48,  6.91iter/s]
[ITER 500] Best: 0.2730
[PARAMS] Current best parameters:
  fx: 561.5826
  fy: 561.3488
  px: 1016.1024
  py: 783.6201
  k1: -0.07320353
  k2: 0.07042621
  k3: -0.04055896
  k4: 0.00848166
  p1: -0.00622948
  p2: -0.01040401
  p3: -0.00331638
  p4: 0.00582478
  s1: 0.0102
  s2: -0.0078
  s3: 0.0039
  s4: -0.0064
  tilt_x: -0.0466
  tilt_y: 0.0572
  scale: 3.0421
  rotation: -0.1647

Best score: 0.2730: : 499iter [00:48,  6.91iter/s]
Best score: 0.2730: : 500iter [00:48,  6.41iter/s]
Best score: 0.2730: : 500iter [00:48,  6.41iter/s]
Best score: 0.2730: : 501iter [00:48,  3.45iter/s]
Best score: 0.2730: : 501iter [00:49,  3.45iter/s]
Best score: 0.2730: : 502iter [00:49,  3.97iter/s]
Best score: 0.2730: : 502iter [00:49,  3.97iter/s]
Best score: 0.2730: : 503iter [00:49,  4.55iter/s]
Best score: 0.2730: : 503iter [00:49,  4.55iter/s]
Best score: 0.2730: : 504iter [00:49,  5.02iter/s]
Best score: 0.2730: : 504iter [00:49,  5.02iter/s]
Best score: 0.2730: : 505iter [00:49,  5.51iter/s]
Best score: 0.2730: : 505iter [00:49,  5.51iter/s]
Best score: 0.2730: : 506iter [00:49,  5.96iter/s]
Best score: 0.2730: : 506iter [00:49,  5.96iter/s]
Best score: 0.2730: : 507iter [00:49,  6.26iter/s]
Best score: 0.2730: : 507iter [00:49,  6.26iter/s]
Best score: 0.2730: : 508iter [00:49,  6.41iter/s]
Best score: 0.2730: : 508iter [00:50,  6.41iter/s]
Best score: 0.2730: : 509iter [00:50,  6.51iter/s]
Best score: 0.2730: : 509iter [00:50,  6.51iter/s]
Best score: 0.2730: : 510iter [00:50,  6.52iter/s]
Best score: 0.2730: : 510iter [00:50,  6.52iter/s]
Best score: 0.2730: : 511iter [00:50,  6.78iter/s]
Best score: 0.2730: : 511iter [00:50,  6.78iter/s]
Best score: 0.2730: : 512iter [00:50,  6.75iter/s]
Best score: 0.2730: : 512iter [00:50,  6.75iter/s]
Best score: 0.2730: : 513iter [00:50,  6.95iter/s]
Best score: 0.2730: : 513iter [00:50,  6.95iter/s]
Best score: 0.2730: : 514iter [00:50,  7.05iter/s]
Best score: 0.2730: : 514iter [00:50,  7.05iter/s]
Best score: 0.2730: : 515iter [00:50,  7.14iter/s]
Best score: 0.2730: : 515iter [00:51,  7.14iter/s]
Best score: 0.2730: : 516iter [00:51,  7.16iter/s]
Best score: 0.2730: : 516iter [00:51,  7.16iter/s]
Best score: 0.2730: : 517iter [00:51,  7.16iter/s]
Best score: 0.2730: : 517iter [00:51,  7.16iter/s]
Best score: 0.2730: : 518iter [00:51,  7.16iter/s]
Best score: 0.2730: : 518iter [00:51,  7.16iter/s]
Best score: 0.2730: : 519iter [00:51,  7.28iter/s]
Best score: 0.2724: : 519iter [00:51,  7.28iter/s]
Best score: 0.2724: : 520iter [00:51,  7.18iter/s]
Best score: 0.2724: : 520iter [00:51,  7.18iter/s]
Best score: 0.2724: : 521iter [00:51,  7.43iter/s]
Best score: 0.2724: : 521iter [00:51,  7.43iter/s]
Best score: 0.2724: : 522iter [00:51,  7.20iter/s]
Best score: 0.2724: : 522iter [00:51,  7.20iter/s]
Best score: 0.2724: : 523iter [00:51,  7.09iter/s]
Best score: 0.2724: : 523iter [00:52,  7.09iter/s]
Best score: 0.2724: : 524iter [00:52,  7.14iter/s]
Best score: 0.2724: : 524iter [00:52,  7.14iter/s]
Best score: 0.2724: : 525iter [00:52,  7.08iter/s]
Best score: 0.2724: : 525iter [00:52,  7.08iter/s]
Best score: 0.2724: : 526iter [00:52,  7.00iter/s]
Best score: 0.2724: : 526iter [00:52,  7.00iter/s]
Best score: 0.2724: : 527iter [00:52,  6.89iter/s]
Best score: 0.2724: : 527iter [00:52,  6.89iter/s]
Best score: 0.2724: : 528iter [00:52,  6.81iter/s]
Best score: 0.2724: : 528iter [00:52,  6.81iter/s]
Best score: 0.2724: : 529iter [00:52,  6.98iter/s]
Best score: 0.2608: : 529iter [00:52,  6.98iter/s]
Best score: 0.2608: : 530iter [00:52,  6.94iter/s]
Best score: 0.2608: : 530iter [00:53,  6.94iter/s]
Best score: 0.2608: : 531iter [00:53,  7.15iter/s]
Best score: 0.2608: : 531iter [00:53,  7.15iter/s]
Best score: 0.2608: : 532iter [00:53,  7.26iter/s]
Best score: 0.2608: : 532iter [00:53,  7.26iter/s]
Best score: 0.2608: : 533iter [00:53,  7.20iter/s]
Best score: 0.2608: : 533iter [00:53,  7.20iter/s]
Best score: 0.2608: : 534iter [00:53,  7.14iter/s]
Best score: 0.2608: : 534iter [00:53,  7.14iter/s]
Best score: 0.2608: : 535iter [00:53,  7.21iter/s]
Best score: 0.2608: : 535iter [00:53,  7.21iter/s]
Best score: 0.2608: : 536iter [00:53,  7.24iter/s]
Best score: 0.2608: : 536iter [00:53,  7.24iter/s]
Best score: 0.2608: : 537iter [00:53,  7.34iter/s]
Best score: 0.2608: : 537iter [00:54,  7.34iter/s]
Best score: 0.2608: : 538iter [00:54,  7.25iter/s]
Best score: 0.2608: : 538iter [00:54,  7.25iter/s]
Best score: 0.2608: : 539iter [00:54,  7.19iter/s]
Best score: 0.2605: : 539iter [00:54,  7.19iter/s]
Best score: 0.2605: : 540iter [00:54,  6.90iter/s]
Best score: 0.2605: : 540iter [00:54,  6.90iter/s]
Best score: 0.2605: : 541iter [00:54,  6.99iter/s]
Best score: 0.2605: : 541iter [00:54,  6.99iter/s]
Best score: 0.2605: : 542iter [00:54,  7.05iter/s]
Best score: 0.2605: : 542iter [00:54,  7.05iter/s]
Best score: 0.2605: : 543iter [00:54,  7.19iter/s]
Best score: 0.2605: : 543iter [00:54,  7.19iter/s]
Best score: 0.2605: : 544iter [00:54,  7.33iter/s]
Best score: 0.2605: : 544iter [00:55,  7.33iter/s]
Best score: 0.2605: : 545iter [00:55,  7.60iter/s]
Best score: 0.2605: : 545iter [00:55,  7.60iter/s]
Best score: 0.2605: : 546iter [00:55,  7.60iter/s]
Best score: 0.2605: : 547iter [00:55,  7.83iter/s]
Best score: 0.2605: : 547iter [00:55,  7.83iter/s]
Best score: 0.2605: : 548iter [00:55,  7.64iter/s]
Best score: 0.2605: : 548iter [00:55,  7.64iter/s]
Best score: 0.2605: : 549iter [00:55,  7.56iter/s]
[ITER 550] Best: 0.2575
[PARAMS] Current best parameters:
  fx: 563.2689
  fy: 562.7843
  px: 1018.8236
  py: 783.0140
  k1: -0.06138894
  k2: 0.04872184
  k3: -0.02804532
  k4: 0.00607558
  p1: -0.01450059
  p2: -0.01010543
  p3: 0.00686654
  p4: 0.00840381
  s1: 0.0014
  s2: -0.0094
  s3: 0.0002
  s4: -0.0070
  tilt_x: -0.0338
  tilt_y: 0.0434
  scale: 3.0244
  rotation: -0.1311

Best score: 0.2575: : 549iter [00:55,  7.56iter/s]
Best score: 0.2575: : 550iter [00:55,  6.98iter/s]
Best score: 0.2575: : 550iter [00:56,  6.98iter/s]
Best score: 0.2575: : 551iter [00:56,  3.76iter/s]
Best score: 0.2575: : 551iter [00:56,  3.76iter/s]
Best score: 0.2575: : 552iter [00:56,  4.23iter/s]
Best score: 0.2575: : 552iter [00:56,  4.23iter/s]
Best score: 0.2575: : 553iter [00:56,  4.75iter/s]
Best score: 0.2575: : 553iter [00:56,  4.75iter/s]
Best score: 0.2575: : 554iter [00:56,  5.38iter/s]
Best score: 0.2575: : 554iter [00:56,  5.38iter/s]
Best score: 0.2575: : 555iter [00:56,  5.81iter/s]
Best score: 0.2575: : 555iter [00:57,  5.81iter/s]
Best score: 0.2575: : 556iter [00:57,  6.16iter/s]
Best score: 0.2575: : 556iter [00:57,  6.16iter/s]
Best score: 0.2575: : 557iter [00:57,  6.41iter/s]
Best score: 0.2575: : 557iter [00:57,  6.41iter/s]
Best score: 0.2575: : 558iter [00:57,  6.60iter/s]
Best score: 0.2575: : 558iter [00:57,  6.60iter/s]
Best score: 0.2575: : 559iter [00:57,  6.68iter/s]
Best score: 0.2534: : 559iter [00:57,  6.68iter/s]
Best score: 0.2534: : 560iter [00:57,  6.62iter/s]
Best score: 0.2534: : 560iter [00:57,  6.62iter/s]
Best score: 0.2534: : 561iter [00:57,  6.63iter/s]
Best score: 0.2534: : 561iter [00:57,  6.63iter/s]
Best score: 0.2534: : 562iter [00:57,  6.72iter/s]
Best score: 0.2534: : 562iter [00:58,  6.72iter/s]
Best score: 0.2534: : 563iter [00:58,  6.77iter/s]
Best score: 0.2534: : 563iter [00:58,  6.77iter/s]
Best score: 0.2534: : 564iter [00:58,  6.74iter/s]
Best score: 0.2534: : 564iter [00:58,  6.74iter/s]
Best score: 0.2534: : 565iter [00:58,  7.01iter/s]
Best score: 0.2534: : 565iter [00:58,  7.01iter/s]
Best score: 0.2534: : 566iter [00:58,  7.26iter/s]
Best score: 0.2534: : 566iter [00:58,  7.26iter/s]
Best score: 0.2534: : 567iter [00:58,  7.35iter/s]
Best score: 0.2534: : 567iter [00:58,  7.35iter/s]
Best score: 0.2534: : 568iter [00:58,  7.56iter/s]
Best score: 0.2534: : 568iter [00:58,  7.56iter/s]
Best score: 0.2534: : 569iter [00:58,  7.58iter/s]
Best score: 0.2517: : 569iter [00:58,  7.58iter/s]
Best score: 0.2517: : 570iter [00:58,  7.40iter/s]
Best score: 0.2517: : 570iter [00:59,  7.40iter/s]
Best score: 0.2517: : 571iter [00:59,  7.31iter/s]
Best score: 0.2517: : 571iter [00:59,  7.31iter/s]
Best score: 0.2517: : 572iter [00:59,  7.10iter/s]
Best score: 0.2517: : 572iter [00:59,  7.10iter/s]
Best score: 0.2517: : 573iter [00:59,  7.02iter/s]
Best score: 0.2517: : 573iter [00:59,  7.02iter/s]
Best score: 0.2517: : 574iter [00:59,  7.09iter/s]
Best score: 0.2517: : 574iter [00:59,  7.09iter/s]
Best score: 0.2517: : 575iter [00:59,  7.04iter/s]
Best score: 0.2517: : 575iter [00:59,  7.04iter/s]
Best score: 0.2517: : 576iter [00:59,  7.19iter/s]
Best score: 0.2517: : 576iter [00:59,  7.19iter/s]
Best score: 0.2517: : 577iter [00:59,  7.18iter/s]
Best score: 0.2517: : 577iter [01:00,  7.18iter/s]
Best score: 0.2517: : 578iter [01:00,  7.26iter/s]
Best score: 0.2517: : 578iter [01:00,  7.26iter/s]
Best score: 0.2517: : 579iter [01:00,  7.39iter/s]
Best score: 0.2517: : 579iter [01:00,  7.39iter/s]
Best score: 0.2517: : 580iter [01:00,  7.30iter/s]
Best score: 0.2517: : 580iter [01:00,  7.30iter/s]
Best score: 0.2517: : 581iter [01:00,  7.19iter/s]
Best score: 0.2517: : 581iter [01:00,  7.19iter/s]
Best score: 0.2517: : 582iter [01:00,  7.20iter/s]
Best score: 0.2517: : 582iter [01:00,  7.20iter/s]
Best score: 0.2517: : 583iter [01:00,  7.24iter/s]
Best score: 0.2517: : 583iter [01:00,  7.24iter/s]
Best score: 0.2517: : 584iter [01:00,  7.05iter/s]
Best score: 0.2517: : 584iter [01:01,  7.05iter/s]
Best score: 0.2517: : 585iter [01:01,  7.07iter/s]
Best score: 0.2517: : 585iter [01:01,  7.07iter/s]
Best score: 0.2517: : 586iter [01:01,  7.05iter/s]
Best score: 0.2517: : 586iter [01:01,  7.05iter/s]
Best score: 0.2517: : 587iter [01:01,  6.87iter/s]
Best score: 0.2517: : 587iter [01:01,  6.87iter/s]
Best score: 0.2517: : 588iter [01:01,  6.86iter/s]
Best score: 0.2517: : 588iter [01:01,  6.86iter/s]
Best score: 0.2517: : 589iter [01:01,  7.04iter/s]
Best score: 0.2517: : 589iter [01:01,  7.04iter/s]
Best score: 0.2517: : 590iter [01:01,  6.91iter/s]
Best score: 0.2517: : 590iter [01:01,  6.91iter/s]
Best score: 0.2517: : 591iter [01:01,  7.13iter/s]
Best score: 0.2517: : 591iter [01:02,  7.13iter/s]
Best score: 0.2517: : 592iter [01:02,  7.29iter/s]
Best score: 0.2517: : 592iter [01:02,  7.29iter/s]
Best score: 0.2517: : 593iter [01:02,  7.32iter/s]
Best score: 0.2517: : 593iter [01:02,  7.32iter/s]
Best score: 0.2517: : 594iter [01:02,  7.33iter/s]
Best score: 0.2517: : 594iter [01:02,  7.33iter/s]
Best score: 0.2517: : 595iter [01:02,  7.44iter/s]
Best score: 0.2517: : 595iter [01:02,  7.44iter/s]
Best score: 0.2517: : 596iter [01:02,  7.41iter/s]
Best score: 0.2517: : 596iter [01:02,  7.41iter/s]
Best score: 0.2517: : 597iter [01:02,  7.34iter/s]
Best score: 0.2517: : 597iter [01:02,  7.34iter/s]
Best score: 0.2517: : 598iter [01:02,  7.38iter/s]
Best score: 0.2517: : 598iter [01:03,  7.38iter/s]
Best score: 0.2517: : 599iter [01:03,  7.49iter/s]
[ITER 600] Best: 0.2517
[PARAMS] Current best parameters:
  fx: 563.5046
  fy: 563.0299
  px: 1017.4230
  py: 783.7469
  k1: -0.06442149
  k2: 0.05668712
  k3: -0.03488916
  k4: 0.00793818
  p1: -0.01290782
  p2: -0.01142247
  p3: 0.00534191
  p4: 0.00666053
  s1: 0.0023
  s2: -0.0068
  s3: 0.0013
  s4: -0.0058
  tilt_x: -0.0333
  tilt_y: 0.0479
  scale: 3.0245
  rotation: -0.1488

Best score: 0.2517: : 599iter [01:03,  7.49iter/s]
Best score: 0.2517: : 600iter [01:03,  7.98iter/s]
Best score: 0.2517: : 600iter [01:03,  7.98iter/s]
Best score: 0.2517: : 601iter [01:03,  4.87iter/s]
Best score: 0.2517: : 601iter [01:03,  4.87iter/s]
Best score: 0.2517: : 602iter [01:03,  4.87iter/s]
Best score: 0.2517: : 603iter [01:03,  6.68iter/s]
Best score: 0.2517: : 603iter [01:03,  6.68iter/s]
Best score: 0.2517: : 604iter [01:03,  6.68iter/s]
Best score: 0.2517: : 605iter [01:03,  8.08iter/s]
Best score: 0.2517: : 605iter [01:03,  8.08iter/s]
Best score: 0.2517: : 606iter [01:04,  8.08iter/s]
Best score: 0.2517: : 607iter [01:04,  9.09iter/s]
Best score: 0.2517: : 607iter [01:04,  9.09iter/s]
Best score: 0.2517: : 608iter [01:04,  9.09iter/s]
Best score: 0.2517: : 609iter [01:04,  9.88iter/s]
Best score: 0.2463: : 609iter [01:04,  9.88iter/s]
Best score: 0.2463: : 610iter [01:04,  9.88iter/s]
Best score: 0.2463: : 611iter [01:04, 10.30iter/s]
Best score: 0.2463: : 611iter [01:04, 10.30iter/s]
Best score: 0.2463: : 612iter [01:04, 10.30iter/s]
Best score: 0.2463: : 613iter [01:04, 10.77iter/s]
Best score: 0.2463: : 613iter [01:04, 10.77iter/s]
Best score: 0.2463: : 614iter [01:04, 10.77iter/s]
Best score: 0.2463: : 615iter [01:04, 11.03iter/s]
Best score: 0.2463: : 615iter [01:04, 11.03iter/s]
Best score: 0.2463: : 616iter [01:04, 11.03iter/s]
Best score: 0.2463: : 617iter [01:04, 11.23iter/s]
Best score: 0.2463: : 617iter [01:04, 11.23iter/s]
Best score: 0.2463: : 618iter [01:05, 11.23iter/s]
Best score: 0.2463: : 619iter [01:05, 11.38iter/s]
Best score: 0.2463: : 619iter [01:05, 11.38iter/s]
Best score: 0.2463: : 620iter [01:05, 11.38iter/s]
Best score: 0.2463: : 621iter [01:05, 11.31iter/s]
Best score: 0.2463: : 621iter [01:05, 11.31iter/s]
Best score: 0.2463: : 622iter [01:05, 11.31iter/s]
Best score: 0.2463: : 623iter [01:05, 11.45iter/s]
Best score: 0.2463: : 623iter [01:05, 11.45iter/s]
Best score: 0.2463: : 624iter [01:05, 11.45iter/s]
Best score: 0.2463: : 625iter [01:05, 11.53iter/s]
Best score: 0.2463: : 625iter [01:05, 11.53iter/s]
Best score: 0.2463: : 626iter [01:05, 11.53iter/s]
Best score: 0.2463: : 627iter [01:05, 10.24iter/s]
Best score: 0.2463: : 627iter [01:05, 10.24iter/s]
Best score: 0.2463: : 628iter [01:05, 10.24iter/s]
Best score: 0.2463: : 629iter [01:05, 10.65iter/s]
Best score: 0.2444: : 629iter [01:06, 10.65iter/s]
Best score: 0.2444: : 630iter [01:06, 10.65iter/s]
Best score: 0.2444: : 631iter [01:06, 10.80iter/s]
Best score: 0.2444: : 631iter [01:06, 10.80iter/s]
Best score: 0.2444: : 632iter [01:06, 10.80iter/s]
Best score: 0.2444: : 633iter [01:06, 11.13iter/s]
Best score: 0.2444: : 633iter [01:06, 11.13iter/s]
Best score: 0.2444: : 634iter [01:06, 11.13iter/s]
Best score: 0.2444: : 635iter [01:06, 11.37iter/s]
Best score: 0.2444: : 635iter [01:06, 11.37iter/s]
Best score: 0.2444: : 636iter [01:06, 11.37iter/s]
Best score: 0.2444: : 637iter [01:06, 10.95iter/s]
Best score: 0.2444: : 637iter [01:06, 10.95iter/s]
Best score: 0.2444: : 638iter [01:06, 10.95iter/s]
Best score: 0.2444: : 639iter [01:06, 11.16iter/s]
Best score: 0.2439: : 639iter [01:06, 11.16iter/s]
Best score: 0.2439: : 640iter [01:07, 11.16iter/s]
Best score: 0.2439: : 641iter [01:07, 10.79iter/s]
Best score: 0.2439: : 641iter [01:07, 10.79iter/s]
Best score: 0.2439: : 642iter [01:07, 10.79iter/s]
Best score: 0.2439: : 643iter [01:07, 11.07iter/s]
Best score: 0.2439: : 643iter [01:07, 11.07iter/s]
Best score: 0.2439: : 644iter [01:07, 11.07iter/s]
Best score: 0.2439: : 645iter [01:07, 11.32iter/s]
Best score: 0.2439: : 645iter [01:07, 11.32iter/s]
Best score: 0.2439: : 646iter [01:07, 11.32iter/s]
Best score: 0.2439: : 647iter [01:07, 11.47iter/s]
Best score: 0.2439: : 647iter [01:07, 11.47iter/s]
Best score: 0.2439: : 648iter [01:07, 11.47iter/s]
Best score: 0.2439: : 649iter [01:07, 11.56iter/s]
[ITER 650] Best: 0.2439
[PARAMS] Current best parameters:
  fx: 562.5543
  fy: 562.1115
  px: 1019.8623
  py: 781.9774
  k1: -0.05764595
  k2: 0.04496770
  k3: -0.02678763
  k4: 0.00602199
  p1: -0.01685671
  p2: -0.00977642
  p3: 0.01186134
  p4: 0.00882803
  s1: -0.0038
  s2: -0.0085
  s3: -0.0031
  s4: -0.0080
  tilt_x: -0.0341
  tilt_y: 0.0386
  scale: 3.0208
  rotation: -0.1673

Best score: 0.2439: : 649iter [01:07, 11.56iter/s]
Best score: 0.2439: : 650iter [01:08, 11.56iter/s]
Best score: 0.2439: : 651iter [01:08,  7.35iter/s]
Best score: 0.2439: : 651iter [01:08,  7.35iter/s]
Best score: 0.2439: : 652iter [01:08,  7.35iter/s]
Best score: 0.2439: : 653iter [01:08,  8.31iter/s]
Best score: 0.2439: : 653iter [01:08,  8.31iter/s]
Best score: 0.2439: : 654iter [01:08,  8.31iter/s]
Best score: 0.2439: : 655iter [01:08,  9.11iter/s]
Best score: 0.2439: : 655iter [01:08,  9.11iter/s]
Best score: 0.2439: : 656iter [01:08,  9.11iter/s]
Best score: 0.2439: : 657iter [01:08,  9.81iter/s]
Best score: 0.2439: : 657iter [01:08,  9.81iter/s]
Best score: 0.2439: : 658iter [01:08,  9.81iter/s]
Best score: 0.2439: : 659iter [01:08, 10.38iter/s]
Best score: 0.2439: : 659iter [01:09, 10.38iter/s]
Best score: 0.2439: : 660iter [01:09, 10.38iter/s]
Best score: 0.2439: : 661iter [01:09, 10.58iter/s]
Best score: 0.2439: : 661iter [01:09, 10.58iter/s]
Best score: 0.2439: : 662iter [01:09, 10.58iter/s]
Best score: 0.2439: : 663iter [01:09, 10.94iter/s]
Best score: 0.2439: : 663iter [01:09, 10.94iter/s]
Best score: 0.2439: : 664iter [01:09, 10.94iter/s]
Best score: 0.2439: : 665iter [01:09, 11.16iter/s]
Best score: 0.2439: : 665iter [01:09, 11.16iter/s]
Best score: 0.2439: : 666iter [01:09, 11.16iter/s]
Best score: 0.2439: : 667iter [01:09, 11.32iter/s]
Best score: 0.2439: : 667iter [01:09, 11.32iter/s]
Best score: 0.2439: : 668iter [01:09, 11.32iter/s]
Best score: 0.2439: : 669iter [01:09, 11.44iter/s]
Best score: 0.2439: : 669iter [01:09, 11.44iter/s]
Best score: 0.2439: : 670iter [01:09, 11.44iter/s]
Best score: 0.2439: : 671iter [01:09, 11.32iter/s]
Best score: 0.2439: : 671iter [01:10, 11.32iter/s]
Best score: 0.2439: : 672iter [01:10, 11.32iter/s]
Best score: 0.2439: : 673iter [01:10, 11.44iter/s]
Best score: 0.2439: : 673iter [01:10, 11.44iter/s]
Best score: 0.2439: : 674iter [01:10, 11.44iter/s]
Best score: 0.2439: : 675iter [01:10, 11.59iter/s]
Best score: 0.2439: : 675iter [01:10, 11.59iter/s]
Best score: 0.2439: : 676iter [01:10, 11.59iter/s]
Best score: 0.2439: : 677iter [01:10, 11.69iter/s]
Best score: 0.2439: : 677iter [01:10, 11.69iter/s]
Best score: 0.2439: : 678iter [01:10, 11.69iter/s]
Best score: 0.2439: : 679iter [01:10, 11.75iter/s]
Best score: 0.2430: : 679iter [01:10, 11.75iter/s]
Best score: 0.2430: : 680iter [01:10, 11.75iter/s]
Best score: 0.2430: : 681iter [01:10, 11.56iter/s]
Best score: 0.2430: : 681iter [01:10, 11.56iter/s]
Best score: 0.2430: : 682iter [01:10, 11.56iter/s]
Best score: 0.2430: : 683iter [01:10, 11.64iter/s]
Best score: 0.2430: : 683iter [01:11, 11.64iter/s]
Best score: 0.2430: : 684iter [01:11, 11.64iter/s]
Best score: 0.2430: : 685iter [01:11, 11.66iter/s]
Best score: 0.2430: : 685iter [01:11, 11.66iter/s]
Best score: 0.2430: : 686iter [01:11, 11.66iter/s]
Best score: 0.2430: : 687iter [01:11, 11.65iter/s]
Best score: 0.2430: : 687iter [01:11, 11.65iter/s]
Best score: 0.2430: : 688iter [01:11, 11.65iter/s]
Best score: 0.2430: : 689iter [01:11, 11.67iter/s]
Best score: 0.2425: : 689iter [01:11, 11.67iter/s]
Best score: 0.2425: : 690iter [01:11, 11.67iter/s]
Best score: 0.2425: : 691iter [01:11, 11.45iter/s]
Best score: 0.2425: : 691iter [01:11, 11.45iter/s]
Best score: 0.2425: : 692iter [01:11, 11.45iter/s]
Best score: 0.2425: : 693iter [01:11, 11.61iter/s]
Best score: 0.2425: : 693iter [01:11, 11.61iter/s]
Best score: 0.2425: : 694iter [01:12, 11.61iter/s]
Best score: 0.2425: : 695iter [01:12, 10.61iter/s]
Best score: 0.2425: : 695iter [01:12, 10.61iter/s]
Best score: 0.2425: : 696iter [01:12, 10.61iter/s]
Best score: 0.2425: : 697iter [01:12,  9.15iter/s]
Best score: 0.2425: : 697iter [01:12,  9.15iter/s]
Best score: 0.2425: : 698iter [01:12,  8.96iter/s]
Best score: 0.2425: : 698iter [01:12,  8.96iter/s]
Best score: 0.2425: : 699iter [01:12,  8.51iter/s]
[ITER 700] Best: 0.2403
[PARAMS] Current best parameters:
  fx: 564.2724
  fy: 563.8662
  px: 1019.2037
  py: 782.9423
  k1: -0.05557559
  k2: 0.03596603
  k3: -0.01954364
  k4: 0.00416079
  p1: -0.01525897
  p2: -0.00994807
  p3: 0.00851387
  p4: 0.00904726
  s1: -0.0007
  s2: -0.0090
  s3: -0.0006
  s4: -0.0084
  tilt_x: -0.0324
  tilt_y: 0.0420
  scale: 3.0201
  rotation: -0.1667

Best score: 0.2403: : 699iter [01:12,  8.51iter/s]
Best score: 0.2403: : 700iter [01:12,  7.92iter/s]
Best score: 0.2403: : 700iter [01:13,  7.92iter/s]
Best score: 0.2403: : 701iter [01:13,  4.39iter/s]
Best score: 0.2403: : 701iter [01:13,  4.39iter/s]
Best score: 0.2403: : 702iter [01:13,  4.87iter/s]
Best score: 0.2403: : 702iter [01:13,  4.87iter/s]
Best score: 0.2403: : 703iter [01:13,  5.31iter/s]
Best score: 0.2403: : 703iter [01:13,  5.31iter/s]
Best score: 0.2403: : 704iter [01:13,  5.49iter/s]
Best score: 0.2403: : 704iter [01:13,  5.49iter/s]
Best score: 0.2403: : 705iter [01:13,  5.75iter/s]
Best score: 0.2403: : 705iter [01:14,  5.75iter/s]
Best score: 0.2403: : 706iter [01:14,  6.05iter/s]
Best score: 0.2403: : 706iter [01:14,  6.05iter/s]
Best score: 0.2403: : 707iter [01:14,  6.16iter/s]
Best score: 0.2403: : 707iter [01:14,  6.16iter/s]
Best score: 0.2403: : 708iter [01:14,  6.40iter/s]
Best score: 0.2403: : 708iter [01:14,  6.40iter/s]
Best score: 0.2403: : 709iter [01:14,  6.59iter/s]
Best score: 0.2400: : 709iter [01:14,  6.59iter/s]
Best score: 0.2400: : 710iter [01:14,  6.57iter/s]
Best score: 0.2400: : 710iter [01:14,  6.57iter/s]
Best score: 0.2400: : 711iter [01:14,  6.58iter/s]
Best score: 0.2400: : 711iter [01:14,  6.58iter/s]
Best score: 0.2400: : 712iter [01:14,  6.73iter/s]
Best score: 0.2400: : 712iter [01:15,  6.73iter/s]
Best score: 0.2400: : 713iter [01:15,  4.68iter/s]
Best score: 0.2400: : 713iter [01:15,  4.68iter/s]
Best score: 0.2400: : 714iter [01:15,  5.20iter/s]
Best score: 0.2400: : 714iter [01:15,  5.20iter/s]
Best score: 0.2400: : 715iter [01:15,  5.63iter/s]
Best score: 0.2400: : 715iter [01:15,  5.63iter/s]
Best score: 0.2400: : 716iter [01:15,  5.95iter/s]
Best score: 0.2400: : 716iter [01:15,  5.95iter/s]
Best score: 0.2400: : 717iter [01:15,  6.23iter/s]
Best score: 0.2400: : 717iter [01:16,  6.23iter/s]
Best score: 0.2400: : 718iter [01:16,  6.43iter/s]
Best score: 0.2400: : 718iter [01:16,  6.43iter/s]
Best score: 0.2400: : 719iter [01:16,  6.76iter/s]
Best score: 0.2395: : 719iter [01:16,  6.76iter/s]
Best score: 0.2395: : 720iter [01:16,  6.72iter/s]
Best score: 0.2395: : 720iter [01:16,  6.72iter/s]
Best score: 0.2395: : 721iter [01:16,  6.72iter/s]
Best score: 0.2395: : 721iter [01:16,  6.72iter/s]
Best score: 0.2395: : 722iter [01:16,  6.84iter/s]
Best score: 0.2395: : 722iter [01:16,  6.84iter/s]
Best score: 0.2395: : 723iter [01:16,  6.87iter/s]
Best score: 0.2395: : 723iter [01:16,  6.87iter/s]
Best score: 0.2395: : 724iter [01:16,  6.99iter/s]
Best score: 0.2395: : 724iter [01:17,  6.99iter/s]
Best score: 0.2395: : 725iter [01:17,  6.99iter/s]
Best score: 0.2395: : 725iter [01:17,  6.99iter/s]
Best score: 0.2395: : 726iter [01:17,  7.06iter/s]
Best score: 0.2395: : 726iter [01:17,  7.06iter/s]
Best score: 0.2395: : 727iter [01:17,  7.08iter/s]
Best score: 0.2395: : 727iter [01:17,  7.08iter/s]
Best score: 0.2395: : 728iter [01:17,  7.11iter/s]
Best score: 0.2395: : 728iter [01:17,  7.11iter/s]
Best score: 0.2395: : 729iter [01:17,  7.11iter/s]
Best score: 0.2377: : 729iter [01:17,  7.11iter/s]
Best score: 0.2377: : 730iter [01:17,  7.09iter/s]
Best score: 0.2377: : 730iter [01:17,  7.09iter/s]
Best score: 0.2377: : 731iter [01:17,  7.14iter/s]
Best score: 0.2377: : 731iter [01:18,  7.14iter/s]
Best score: 0.2377: : 732iter [01:18,  7.16iter/s]
Best score: 0.2377: : 732iter [01:18,  7.16iter/s]
Best score: 0.2377: : 733iter [01:18,  7.18iter/s]
Best score: 0.2377: : 733iter [01:18,  7.18iter/s]
Best score: 0.2377: : 734iter [01:18,  7.20iter/s]
Best score: 0.2377: : 734iter [01:18,  7.20iter/s]
Best score: 0.2377: : 735iter [01:18,  7.23iter/s]
Best score: 0.2377: : 735iter [01:18,  7.23iter/s]
Best score: 0.2377: : 736iter [01:18,  7.11iter/s]
Best score: 0.2377: : 736iter [01:18,  7.11iter/s]
Best score: 0.2377: : 737iter [01:18,  7.20iter/s]
Best score: 0.2377: : 737iter [01:18,  7.20iter/s]
Best score: 0.2377: : 738iter [01:18,  7.17iter/s]
Best score: 0.2377: : 738iter [01:18,  7.17iter/s]
Best score: 0.2377: : 739iter [01:18,  7.21iter/s]
Best score: 0.2364: : 739iter [01:19,  7.21iter/s]
Best score: 0.2364: : 740iter [01:19,  7.19iter/s]
Best score: 0.2364: : 740iter [01:19,  7.19iter/s]
Best score: 0.2364: : 741iter [01:19,  7.27iter/s]
Best score: 0.2364: : 741iter [01:19,  7.27iter/s]
Best score: 0.2364: : 742iter [01:19,  7.19iter/s]
Best score: 0.2364: : 742iter [01:19,  7.19iter/s]
Best score: 0.2364: : 743iter [01:19,  7.35iter/s]
Best score: 0.2364: : 743iter [01:19,  7.35iter/s]
Best score: 0.2364: : 744iter [01:19,  7.41iter/s]
Best score: 0.2364: : 744iter [01:19,  7.41iter/s]
Best score: 0.2364: : 745iter [01:19,  7.46iter/s]
Best score: 0.2364: : 745iter [01:19,  7.46iter/s]
Best score: 0.2364: : 746iter [01:19,  7.48iter/s]
Best score: 0.2364: : 746iter [01:20,  7.48iter/s]
Best score: 0.2364: : 747iter [01:20,  7.55iter/s]
Best score: 0.2364: : 747iter [01:20,  7.55iter/s]
Best score: 0.2364: : 748iter [01:20,  7.66iter/s]
Best score: 0.2364: : 748iter [01:20,  7.66iter/s]
Best score: 0.2364: : 749iter [01:20,  7.54iter/s]
[ITER 750] Best: 0.2361
[PARAMS] Current best parameters:
  fx: 564.1833
  fy: 563.8576
  px: 1021.1018
  py: 784.8254
  k1: -0.04734130
  k2: 0.02194526
  k3: -0.01058027
  k4: 0.00211352
  p1: -0.01197879
  p2: -0.00809459
  p3: 0.01281261
  p4: 0.00826258
  s1: -0.0048
  s2: -0.0080
  s3: -0.0056
  s4: -0.0084
  tilt_x: -0.0293
  tilt_y: 0.0362
  scale: 3.0117
  rotation: -0.1665

Best score: 0.2361: : 749iter [01:20,  7.54iter/s]
Best score: 0.2361: : 750iter [01:20,  7.19iter/s]
Best score: 0.2361: : 750iter [01:21,  7.19iter/s]
Best score: 0.2361: : 751iter [01:21,  3.60iter/s]
Best score: 0.2361: : 751iter [01:21,  3.60iter/s]
Best score: 0.2361: : 752iter [01:21,  4.25iter/s]
Best score: 0.2361: : 752iter [01:21,  4.25iter/s]
Best score: 0.2361: : 753iter [01:21,  4.91iter/s]
Best score: 0.2361: : 753iter [01:21,  4.91iter/s]
Best score: 0.2361: : 754iter [01:21,  5.54iter/s]
Best score: 0.2361: : 754iter [01:21,  5.54iter/s]
Best score: 0.2361: : 755iter [01:21,  5.92iter/s]
Best score: 0.2361: : 755iter [01:21,  5.92iter/s]
Best score: 0.2361: : 756iter [01:21,  6.27iter/s]
Best score: 0.2361: : 756iter [01:21,  6.27iter/s]
Best score: 0.2361: : 757iter [01:21,  6.57iter/s]
Best score: 0.2361: : 757iter [01:22,  6.57iter/s]
Best score: 0.2361: : 758iter [01:22,  6.92iter/s]
Best score: 0.2361: : 758iter [01:22,  6.92iter/s]
Best score: 0.2361: : 759iter [01:22,  7.00iter/s]
Best score: 0.2361: : 759iter [01:22,  7.00iter/s]
Best score: 0.2361: : 760iter [01:22,  6.77iter/s]
Best score: 0.2361: : 760iter [01:22,  6.77iter/s]
Best score: 0.2361: : 761iter [01:22,  6.95iter/s]
Best score: 0.2361: : 761iter [01:22,  6.95iter/s]
Best score: 0.2361: : 762iter [01:22,  6.88iter/s]
Best score: 0.2361: : 762iter [01:22,  6.88iter/s]
Best score: 0.2361: : 763iter [01:22,  6.83iter/s]
Best score: 0.2361: : 763iter [01:22,  6.83iter/s]
Best score: 0.2361: : 764iter [01:22,  6.84iter/s]
Best score: 0.2361: : 764iter [01:23,  6.84iter/s]
Best score: 0.2361: : 765iter [01:23,  6.89iter/s]
Best score: 0.2361: : 765iter [01:23,  6.89iter/s]
Best score: 0.2361: : 766iter [01:23,  6.86iter/s]
Best score: 0.2361: : 766iter [01:23,  6.86iter/s]
Best score: 0.2361: : 767iter [01:23,  6.86iter/s]
Best score: 0.2361: : 767iter [01:23,  6.86iter/s]
Best score: 0.2361: : 768iter [01:23,  6.91iter/s]
Best score: 0.2361: : 768iter [01:23,  6.91iter/s]
Best score: 0.2361: : 769iter [01:23,  6.98iter/s]
Best score: 0.2360: : 769iter [01:23,  6.98iter/s]
Best score: 0.2360: : 770iter [01:23,  6.89iter/s]
Best score: 0.2360: : 770iter [01:23,  6.89iter/s]
Best score: 0.2360: : 771iter [01:23,  7.05iter/s]
Best score: 0.2360: : 771iter [01:24,  7.05iter/s]
Best score: 0.2360: : 772iter [01:24,  7.05iter/s]
Best score: 0.2360: : 772iter [01:24,  7.05iter/s]
Best score: 0.2360: : 773iter [01:24,  7.12iter/s]
Best score: 0.2360: : 773iter [01:24,  7.12iter/s]
Best score: 0.2360: : 774iter [01:24,  7.15iter/s]
Best score: 0.2360: : 774iter [01:24,  7.15iter/s]
Best score: 0.2360: : 775iter [01:24,  7.22iter/s]
Best score: 0.2360: : 775iter [01:24,  7.22iter/s]
Best score: 0.2360: : 776iter [01:24,  7.40iter/s]
Best score: 0.2360: : 776iter [01:24,  7.40iter/s]
Best score: 0.2360: : 777iter [01:24,  7.34iter/s]
Best score: 0.2360: : 777iter [01:24,  7.34iter/s]
Best score: 0.2360: : 778iter [01:24,  7.40iter/s]
Best score: 0.2360: : 778iter [01:24,  7.40iter/s]
Best score: 0.2360: : 779iter [01:24,  7.28iter/s]
Best score: 0.2352: : 779iter [01:25,  7.28iter/s]
Best score: 0.2352: : 780iter [01:25,  7.11iter/s]
Best score: 0.2352: : 780iter [01:25,  7.11iter/s]
Best score: 0.2352: : 781iter [01:25,  7.17iter/s]
Best score: 0.2352: : 781iter [01:25,  7.17iter/s]
Best score: 0.2352: : 782iter [01:25,  7.31iter/s]
Best score: 0.2352: : 782iter [01:25,  7.31iter/s]
Best score: 0.2352: : 783iter [01:25,  7.37iter/s]
Best score: 0.2352: : 783iter [01:25,  7.37iter/s]
Best score: 0.2352: : 784iter [01:25,  7.30iter/s]
Best score: 0.2352: : 784iter [01:25,  7.30iter/s]
Best score: 0.2352: : 785iter [01:25,  7.31iter/s]
Best score: 0.2352: : 785iter [01:25,  7.31iter/s]
Best score: 0.2352: : 786iter [01:25,  7.38iter/s]
Best score: 0.2352: : 786iter [01:26,  7.38iter/s]
Best score: 0.2352: : 787iter [01:26,  7.40iter/s]
Best score: 0.2352: : 787iter [01:26,  7.40iter/s]
Best score: 0.2352: : 788iter [01:26,  7.36iter/s]
Best score: 0.2352: : 788iter [01:26,  7.36iter/s]
Best score: 0.2352: : 789iter [01:26,  7.38iter/s]
Best score: 0.2348: : 789iter [01:26,  7.38iter/s]
Best score: 0.2348: : 790iter [01:26,  7.18iter/s]
Best score: 0.2348: : 790iter [01:26,  7.18iter/s]
Best score: 0.2348: : 791iter [01:26,  7.12iter/s]
Best score: 0.2348: : 791iter [01:26,  7.12iter/s]
Best score: 0.2348: : 792iter [01:26,  7.10iter/s]
Best score: 0.2348: : 792iter [01:26,  7.10iter/s]
Best score: 0.2348: : 793iter [01:26,  7.10iter/s]
Best score: 0.2348: : 793iter [01:27,  7.10iter/s]
Best score: 0.2348: : 794iter [01:27,  6.98iter/s]
Best score: 0.2348: : 794iter [01:27,  6.98iter/s]
Best score: 0.2348: : 795iter [01:27,  7.04iter/s]
Best score: 0.2348: : 795iter [01:27,  7.04iter/s]
Best score: 0.2348: : 796iter [01:27,  7.15iter/s]
Best score: 0.2348: : 796iter [01:27,  7.15iter/s]
Best score: 0.2348: : 797iter [01:27,  7.18iter/s]
Best score: 0.2348: : 797iter [01:27,  7.18iter/s]
Best score: 0.2348: : 798iter [01:27,  7.18iter/s]
Best score: 0.2348: : 798iter [01:27,  7.18iter/s]
Best score: 0.2348: : 799iter [01:27,  7.29iter/s]
Best score: 0.2348: : 799iter [01:27,  7.29iter/s]
Best score: 0.2348: : 800iter [01:27,  7.01iter/s]
[ITER 800] Best: 0.2348
[PARAMS] Current best parameters:
  fx: 564.1252
  fy: 563.8761
  px: 1021.4353
  py: 784.3262
  k1: -0.04675875
  k2: 0.02063255
  k3: -0.00948298
  k4: 0.00179599
  p1: -0.01071292
  p2: -0.00753649
  p3: 0.01397411
  p4: 0.00632314
  s1: -0.0065
  s2: -0.0060
  s3: -0.0083
  s4: -0.0066
  tilt_x: -0.0345
  tilt_y: 0.0357
  scale: 3.0123
  rotation: -0.1662

Best score: 0.2348: : 800iter [01:28,  7.01iter/s]
Best score: 0.2348: : 801iter [01:28,  3.36iter/s]
Best score: 0.2348: : 801iter [01:28,  3.36iter/s]
Best score: 0.2348: : 802iter [01:28,  4.06iter/s]
Best score: 0.2348: : 802iter [01:28,  4.06iter/s]
Best score: 0.2348: : 803iter [01:28,  4.65iter/s]
Best score: 0.2348: : 803iter [01:28,  4.65iter/s]
Best score: 0.2348: : 804iter [01:28,  5.20iter/s]
Best score: 0.2348: : 804iter [01:29,  5.20iter/s]
Best score: 0.2348: : 805iter [01:29,  5.63iter/s]
Best score: 0.2348: : 805iter [01:29,  5.63iter/s]
Best score: 0.2348: : 806iter [01:29,  6.05iter/s]
Best score: 0.2348: : 806iter [01:29,  6.05iter/s]
Best score: 0.2348: : 807iter [01:29,  6.42iter/s]
Best score: 0.2348: : 807iter [01:29,  6.42iter/s]
Best score: 0.2348: : 808iter [01:29,  6.58iter/s]
Best score: 0.2348: : 808iter [01:29,  6.58iter/s]
Best score: 0.2348: : 809iter [01:29,  6.84iter/s]
Best score: 0.2348: : 809iter [01:29,  6.84iter/s]
Best score: 0.2348: : 810iter [01:29,  6.74iter/s]
Best score: 0.2348: : 810iter [01:29,  6.74iter/s]
Best score: 0.2348: : 811iter [01:29,  6.99iter/s]
Best score: 0.2348: : 811iter [01:30,  6.99iter/s]
Best score: 0.2348: : 812iter [01:30,  7.23iter/s]
Best score: 0.2348: : 812iter [01:30,  7.23iter/s]
Best score: 0.2348: : 813iter [01:30,  7.24iter/s]
Best score: 0.2348: : 813iter [01:30,  7.24iter/s]
Best score: 0.2348: : 814iter [01:30,  7.44iter/s]
Best score: 0.2348: : 814iter [01:30,  7.44iter/s]
Best score: 0.2348: : 815iter [01:30,  7.53iter/s]
Best score: 0.2348: : 815iter [01:30,  7.53iter/s]
Best score: 0.2348: : 816iter [01:30,  7.92iter/s]
Best score: 0.2348: : 816iter [01:30,  7.92iter/s]
Best score: 0.2348: : 817iter [01:30,  7.92iter/s]
Best score: 0.2348: : 818iter [01:30,  9.22iter/s]
Best score: 0.2348: : 818iter [01:30,  9.22iter/s]
Best score: 0.2345: : 819iter [01:30,  9.22iter/s]
Best score: 0.2345: : 820iter [01:30,  9.88iter/s]
Best score: 0.2345: : 820iter [01:31,  9.88iter/s]
Best score: 0.2345: : 821iter [01:31,  9.88iter/s]
Best score: 0.2345: : 822iter [01:31, 10.48iter/s]
Best score: 0.2345: : 822iter [01:31, 10.48iter/s]
Best score: 0.2345: : 823iter [01:31, 10.48iter/s]
Best score: 0.2345: : 824iter [01:31, 10.88iter/s]
Best score: 0.2345: : 824iter [01:31, 10.88iter/s]
Best score: 0.2345: : 825iter [01:31, 10.88iter/s]
Best score: 0.2345: : 826iter [01:31, 11.18iter/s]
Best score: 0.2345: : 826iter [01:31, 11.18iter/s]
Best score: 0.2345: : 827iter [01:31, 11.18iter/s]
Best score: 0.2345: : 828iter [01:31, 11.40iter/s]
Best score: 0.2345: : 828iter [01:31, 11.40iter/s]
Best score: 0.2345: : 829iter [01:31, 11.40iter/s]
Best score: 0.2345: : 830iter [01:31, 11.33iter/s]
Best score: 0.2345: : 830iter [01:31, 11.33iter/s]
Best score: 0.2345: : 831iter [01:31, 11.33iter/s]
Best score: 0.2345: : 832iter [01:31, 11.48iter/s]
Best score: 0.2345: : 832iter [01:32, 11.48iter/s]
Best score: 0.2345: : 833iter [01:32, 11.48iter/s]
Best score: 0.2345: : 834iter [01:32, 11.53iter/s]
Best score: 0.2345: : 834iter [01:32, 11.53iter/s]
Best score: 0.2345: : 835iter [01:32, 11.53iter/s]
Best score: 0.2345: : 836iter [01:32, 11.58iter/s]
Best score: 0.2345: : 836iter [01:32, 11.58iter/s]
Best score: 0.2345: : 837iter [01:32, 11.58iter/s]
Best score: 0.2345: : 838iter [01:32, 11.63iter/s]
Best score: 0.2345: : 838iter [01:32, 11.63iter/s]
Best score: 0.2345: : 839iter [01:32, 11.63iter/s]
Best score: 0.2345: : 840iter [01:32, 11.48iter/s]
Best score: 0.2345: : 840iter [01:32, 11.48iter/s]
Best score: 0.2345: : 841iter [01:32, 11.48iter/s]
Best score: 0.2345: : 842iter [01:32, 11.57iter/s]
Best score: 0.2345: : 842iter [01:32, 11.57iter/s]
Best score: 0.2345: : 843iter [01:32, 11.57iter/s]
Best score: 0.2345: : 844iter [01:32, 11.61iter/s]
Best score: 0.2345: : 844iter [01:33, 11.61iter/s]
Best score: 0.2345: : 845iter [01:33, 11.61iter/s]
Best score: 0.2345: : 846iter [01:33, 10.47iter/s]
Best score: 0.2345: : 846iter [01:33, 10.47iter/s]
Best score: 0.2345: : 847iter [01:33, 10.47iter/s]
Best score: 0.2345: : 848iter [01:33, 10.60iter/s]
Best score: 0.2345: : 848iter [01:33, 10.60iter/s]
[ITER 850] Best: 0.2344
[PARAMS] Current best parameters:
  fx: 564.2623
  fy: 564.0221
  px: 1021.1142
  py: 784.7280
  k1: -0.04275361
  k2: 0.01375370
  k3: -0.00524644
  k4: 0.00086599
  p1: -0.01114730
  p2: -0.00922971
  p3: 0.01536915
  p4: 0.00878606
  s1: -0.0058
  s2: -0.0090
  s3: -0.0091
  s4: -0.0088
  tilt_x: -0.0316
  tilt_y: 0.0340
  scale: 3.0075
  rotation: -0.1524

Best score: 0.2344: : 849iter [01:33, 10.60iter/s]
Best score: 0.2344: : 850iter [01:33, 10.79iter/s]
Best score: 0.2344: : 850iter [01:33, 10.79iter/s]
Best score: 0.2344: : 851iter [01:34, 10.79iter/s]
Best score: 0.2344: : 852iter [01:34,  7.32iter/s]
Best score: 0.2344: : 852iter [01:34,  7.32iter/s]
Best score: 0.2344: : 853iter [01:34,  7.32iter/s]
Best score: 0.2344: : 854iter [01:34,  8.31iter/s]
Best score: 0.2344: : 854iter [01:34,  8.31iter/s]
Best score: 0.2344: : 855iter [01:34,  8.31iter/s]
Best score: 0.2344: : 856iter [01:34,  9.17iter/s]
Best score: 0.2344: : 856iter [01:34,  9.17iter/s]
Best score: 0.2344: : 857iter [01:34,  9.17iter/s]
Best score: 0.2344: : 858iter [01:34,  9.88iter/s]
Best score: 0.2344: : 858iter [01:34,  9.88iter/s]
Best score: 0.2342: : 859iter [01:34,  9.88iter/s]
Best score: 0.2342: : 860iter [01:34, 10.30iter/s]
Best score: 0.2342: : 860iter [01:34, 10.30iter/s]
Best score: 0.2342: : 861iter [01:34, 10.30iter/s]
Best score: 0.2342: : 862iter [01:34, 10.77iter/s]
Best score: 0.2342: : 862iter [01:34, 10.77iter/s]
Best score: 0.2342: : 863iter [01:35, 10.77iter/s]
Best score: 0.2342: : 864iter [01:35, 11.10iter/s]
Best score: 0.2342: : 864iter [01:35, 11.10iter/s]
Best score: 0.2342: : 865iter [01:35, 11.10iter/s]
Best score: 0.2342: : 866iter [01:35, 11.28iter/s]
Best score: 0.2342: : 866iter [01:35, 11.28iter/s]
Best score: 0.2342: : 867iter [01:35, 11.28iter/s]
Best score: 0.2342: : 868iter [01:35, 11.50iter/s]
Best score: 0.2342: : 868iter [01:35, 11.50iter/s]
Best score: 0.2341: : 869iter [01:35, 11.50iter/s]
Best score: 0.2341: : 870iter [01:35, 11.48iter/s]
Best score: 0.2341: : 870iter [01:35, 11.48iter/s]
Best score: 0.2341: : 871iter [01:35, 11.48iter/s]
Best score: 0.2341: : 872iter [01:35, 11.60iter/s]
Best score: 0.2341: : 872iter [01:35, 11.60iter/s]
Best score: 0.2341: : 873iter [01:35, 11.60iter/s]
Best score: 0.2341: : 874iter [01:35, 11.63iter/s]
Best score: 0.2341: : 874iter [01:36, 11.63iter/s]
Best score: 0.2341: : 875iter [01:36, 11.63iter/s]
Best score: 0.2341: : 876iter [01:36, 11.67iter/s]
Best score: 0.2341: : 876iter [01:36, 11.67iter/s]
Best score: 0.2341: : 877iter [01:36, 11.67iter/s]
Best score: 0.2341: : 878iter [01:36, 11.72iter/s]
Best score: 0.2341: : 878iter [01:36, 11.72iter/s]
Best score: 0.2341: : 879iter [01:36, 11.72iter/s]
Best score: 0.2341: : 880iter [01:36, 11.61iter/s]
Best score: 0.2341: : 880iter [01:36, 11.61iter/s]
Best score: 0.2341: : 881iter [01:36, 11.61iter/s]
Best score: 0.2341: : 882iter [01:36, 11.74iter/s]
Best score: 0.2341: : 882iter [01:36, 11.74iter/s]
Best score: 0.2341: : 883iter [01:36, 11.74iter/s]
Best score: 0.2341: : 884iter [01:36, 11.82iter/s]
Best score: 0.2341: : 884iter [01:36, 11.82iter/s]
Best score: 0.2341: : 885iter [01:36, 11.82iter/s]
Best score: 0.2341: : 886iter [01:36, 11.89iter/s]
Best score: 0.2341: : 886iter [01:37, 11.89iter/s]
Best score: 0.2341: : 887iter [01:37, 11.89iter/s]
Best score: 0.2341: : 888iter [01:37, 11.94iter/s]
Best score: 0.2341: : 888iter [01:37, 11.94iter/s]
Best score: 0.2341: : 889iter [01:37, 11.94iter/s]
Best score: 0.2341: : 890iter [01:37, 11.77iter/s]
Best score: 0.2341: : 890iter [01:37, 11.77iter/s]
Best score: 0.2341: : 891iter [01:37, 11.77iter/s]
Best score: 0.2341: : 892iter [01:37, 11.85iter/s]
Best score: 0.2341: : 892iter [01:37, 11.85iter/s]
Best score: 0.2341: : 893iter [01:37, 11.85iter/s]
Best score: 0.2341: : 894iter [01:37, 11.90iter/s]
Best score: 0.2341: : 894iter [01:37, 11.90iter/s]
Best score: 0.2341: : 895iter [01:37, 11.90iter/s]
Best score: 0.2341: : 896iter [01:37, 11.90iter/s]
Best score: 0.2341: : 896iter [01:37, 11.90iter/s]
Best score: 0.2341: : 897iter [01:37, 11.90iter/s]
Best score: 0.2341: : 898iter [01:37, 11.89iter/s]
Best score: 0.2341: : 898iter [01:38, 11.89iter/s]
[ITER 900] Best: 0.2339
[PARAMS] Current best parameters:
  fx: 564.7676
  fy: 564.4721
  px: 1022.0561
  py: 784.9332
  k1: -0.04408139
  k2: 0.01520568
  k3: -0.00617358
  k4: 0.00110658
  p1: -0.00981606
  p2: -0.00680897
  p3: 0.01377251
  p4: 0.00562353
  s1: -0.0057
  s2: -0.0058
  s3: -0.0087
  s4: -0.0057
  tilt_x: -0.0332
  tilt_y: 0.0342
  scale: 3.0087
  rotation: -0.1563

Best score: 0.2339: : 899iter [01:38, 11.89iter/s]
Best score: 0.2339: : 900iter [01:38, 11.68iter/s]
Best score: 0.2339: : 900iter [01:38, 11.68iter/s]
Best score: 0.2339: : 901iter [01:38, 11.68iter/s]
Best score: 0.2339: : 902iter [01:38,  7.64iter/s]
Best score: 0.2339: : 902iter [01:38,  7.64iter/s]
Best score: 0.2339: : 903iter [01:38,  7.64iter/s]
Best score: 0.2339: : 904iter [01:38,  8.53iter/s]
Best score: 0.2339: : 904iter [01:38,  8.53iter/s]
Best score: 0.2339: : 905iter [01:38,  8.53iter/s]
Best score: 0.2339: : 906iter [01:38,  9.35iter/s]
Best score: 0.2339: : 906iter [01:39,  9.35iter/s]
Best score: 0.2339: : 907iter [01:39,  9.35iter/s]
Best score: 0.2339: : 908iter [01:39,  9.96iter/s]
Best score: 0.2339: : 908iter [01:39,  9.96iter/s]
Best score: 0.2338: : 909iter [01:39,  9.96iter/s]
Best score: 0.2338: : 910iter [01:39, 10.28iter/s]
Best score: 0.2338: : 910iter [01:39, 10.28iter/s]
Best score: 0.2338: : 911iter [01:39, 10.28iter/s]
Best score: 0.2338: : 912iter [01:39, 10.74iter/s]
Best score: 0.2338: : 912iter [01:39, 10.74iter/s]
Best score: 0.2338: : 913iter [01:39, 10.74iter/s]
Best score: 0.2338: : 914iter [01:39, 11.07iter/s]
Best score: 0.2338: : 914iter [01:39, 11.07iter/s]
Best score: 0.2338: : 915iter [01:39, 11.07iter/s]
Best score: 0.2338: : 916iter [01:39, 11.34iter/s]
Best score: 0.2338: : 916iter [01:39, 11.34iter/s]
Best score: 0.2338: : 917iter [01:39, 11.34iter/s]
Best score: 0.2338: : 918iter [01:39, 11.56iter/s]
Best score: 0.2338: : 918iter [01:40, 11.56iter/s]
Best score: 0.2336: : 919iter [01:40, 11.56iter/s]
Best score: 0.2336: : 920iter [01:40, 11.49iter/s]
Best score: 0.2336: : 920iter [01:40, 11.49iter/s]
Best score: 0.2336: : 921iter [01:40, 11.49iter/s]
Best score: 0.2336: : 922iter [01:40, 11.67iter/s]
Best score: 0.2336: : 922iter [01:40, 11.67iter/s]
Best score: 0.2336: : 923iter [01:40, 11.67iter/s]
Best score: 0.2336: : 924iter [01:40, 11.79iter/s]
Best score: 0.2336: : 924iter [01:40, 11.79iter/s]
Best score: 0.2336: : 925iter [01:40, 11.79iter/s]
Best score: 0.2336: : 926iter [01:40, 11.87iter/s]
Best score: 0.2336: : 926iter [01:40, 11.87iter/s]
Best score: 0.2336: : 927iter [01:40, 11.87iter/s]
Best score: 0.2336: : 928iter [01:40, 11.87iter/s]
Best score: 0.2336: : 928iter [01:40, 11.87iter/s]
Best score: 0.2336: : 929iter [01:40, 11.87iter/s]
Best score: 0.2336: : 930iter [01:40, 11.72iter/s]
Best score: 0.2336: : 930iter [01:41, 11.72iter/s]
Best score: 0.2336: : 931iter [01:41, 11.72iter/s]
Best score: 0.2336: : 932iter [01:41, 11.82iter/s]
Best score: 0.2336: : 932iter [01:41, 11.82iter/s]
Best score: 0.2336: : 933iter [01:41, 11.82iter/s]
Best score: 0.2336: : 934iter [01:41, 11.88iter/s]
Best score: 0.2336: : 934iter [01:41, 11.88iter/s]
Best score: 0.2336: : 935iter [01:41, 11.88iter/s]
Best score: 0.2336: : 936iter [01:41, 11.95iter/s]
Best score: 0.2336: : 936iter [01:41, 11.95iter/s]
Best score: 0.2336: : 937iter [01:41, 11.95iter/s]
Best score: 0.2336: : 938iter [01:41, 11.99iter/s]
Best score: 0.2336: : 938iter [01:41, 11.99iter/s]
Best score: 0.2335: : 939iter [01:41, 11.99iter/s]
Best score: 0.2335: : 940iter [01:41, 11.81iter/s]
Best score: 0.2335: : 940iter [01:41, 11.81iter/s]
Best score: 0.2335: : 941iter [01:41, 11.81iter/s]
Best score: 0.2335: : 942iter [01:41, 11.87iter/s]
Best score: 0.2335: : 942iter [01:42, 11.87iter/s]
Best score: 0.2335: : 943iter [01:42, 11.87iter/s]
Best score: 0.2335: : 944iter [01:42, 11.92iter/s]
Best score: 0.2335: : 944iter [01:42, 11.92iter/s]
Best score: 0.2335: : 945iter [01:42, 11.92iter/s]
Best score: 0.2335: : 946iter [01:42, 11.94iter/s]
Best score: 0.2335: : 946iter [01:42, 11.94iter/s]
Best score: 0.2335: : 947iter [01:42, 11.94iter/s]
Best score: 0.2335: : 948iter [01:42, 11.99iter/s]
Best score: 0.2335: : 948iter [01:42, 11.99iter/s]
[ITER 950] Best: 0.2335
[PARAMS] Current best parameters:
  fx: 563.4897
  fy: 563.2785
  px: 1021.4417
  py: 784.6299
  k1: -0.04144761
  k2: 0.01240460
  k3: -0.00410237
  k4: 0.00051970
  p1: -0.00869209
  p2: -0.00838407
  p3: 0.01508465
  p4: 0.00766396
  s1: -0.0064
  s2: -0.0077
  s3: -0.0116
  s4: -0.0074
  tilt_x: -0.0368
  tilt_y: 0.0339
  scale: 3.0081
  rotation: -0.1571

Best score: 0.2335: : 949iter [01:42, 11.99iter/s]
Best score: 0.2335: : 950iter [01:42, 11.79iter/s]
Best score: 0.2335: : 950iter [01:43, 11.79iter/s]
Best score: 0.2335: : 951iter [01:43, 11.79iter/s]
Best score: 0.2335: : 952iter [01:43,  7.65iter/s]
Best score: 0.2335: : 952iter [01:43,  7.65iter/s]
Best score: 0.2335: : 953iter [01:43,  7.65iter/s]
Best score: 0.2335: : 954iter [01:43,  8.60iter/s]
Best score: 0.2335: : 954iter [01:43,  8.60iter/s]
Best score: 0.2335: : 955iter [01:43,  8.60iter/s]
Best score: 0.2335: : 956iter [01:43,  9.41iter/s]
Best score: 0.2335: : 956iter [01:43,  9.41iter/s]
Best score: 0.2335: : 957iter [01:43,  9.41iter/s]
Best score: 0.2335: : 958iter [01:43, 10.08iter/s]
Best score: 0.2335: : 958iter [01:43, 10.08iter/s]
Best score: 0.2334: : 959iter [01:43, 10.08iter/s]
Best score: 0.2334: : 960iter [01:43, 10.41iter/s]
Best score: 0.2334: : 960iter [01:43, 10.41iter/s]
Best score: 0.2334: : 961iter [01:43, 10.41iter/s]
Best score: 0.2334: : 962iter [01:43, 10.85iter/s]
Best score: 0.2334: : 962iter [01:44, 10.85iter/s]
Best score: 0.2334: : 963iter [01:44, 10.85iter/s]
Best score: 0.2334: : 964iter [01:44, 11.15iter/s]
Best score: 0.2334: : 964iter [01:44, 11.15iter/s]
Best score: 0.2334: : 965iter [01:44, 11.15iter/s]
Best score: 0.2334: : 966iter [01:44, 11.38iter/s]
Best score: 0.2334: : 966iter [01:44, 11.38iter/s]
Best score: 0.2334: : 967iter [01:44, 11.38iter/s]
Best score: 0.2334: : 968iter [01:44, 11.54iter/s]
Best score: 0.2334: : 968iter [01:44, 11.54iter/s]
Best score: 0.2332: : 969iter [01:44, 11.54iter/s]
Best score: 0.2332: : 970iter [01:44, 11.50iter/s]
Best score: 0.2332: : 970iter [01:44, 11.50iter/s]
Best score: 0.2332: : 971iter [01:44, 11.50iter/s]
Best score: 0.2332: : 972iter [01:44, 11.67iter/s]
Best score: 0.2332: : 972iter [01:44, 11.67iter/s]
Best score: 0.2332: : 973iter [01:44, 11.67iter/s]
Best score: 0.2332: : 974iter [01:44, 11.69iter/s]
Best score: 0.2332: : 974iter [01:45, 11.69iter/s]
Best score: 0.2332: : 975iter [01:45, 11.69iter/s]
Best score: 0.2332: : 976iter [01:45, 11.78iter/s]
Best score: 0.2332: : 976iter [01:45, 11.78iter/s]
Best score: 0.2332: : 977iter [01:45, 11.78iter/s]
Best score: 0.2332: : 978iter [01:45, 11.87iter/s]
Best score: 0.2332: : 978iter [01:45, 11.87iter/s]
Best score: 0.2332: : 979iter [01:45, 11.87iter/s]
Best score: 0.2332: : 980iter [01:45, 11.75iter/s]
Best score: 0.2332: : 980iter [01:45, 11.75iter/s]
Best score: 0.2332: : 981iter [01:45, 11.75iter/s]
Best score: 0.2332: : 982iter [01:45, 11.79iter/s]
Best score: 0.2332: : 982iter [01:45, 11.79iter/s]
Best score: 0.2332: : 983iter [01:45, 11.79iter/s]
Best score: 0.2332: : 984iter [01:45, 11.87iter/s]
Best score: 0.2332: : 984iter [01:45, 11.87iter/s]
Best score: 0.2332: : 985iter [01:45, 11.87iter/s]
Best score: 0.2332: : 986iter [01:45, 11.93iter/s]
Best score: 0.2332: : 986iter [01:46, 11.93iter/s]
Best score: 0.2332: : 987iter [01:46, 11.93iter/s]
Best score: 0.2332: : 988iter [01:46, 11.99iter/s]
Best score: 0.2332: : 988iter [01:46, 11.99iter/s]
Best score: 0.2331: : 989iter [01:46, 11.99iter/s]
Best score: 0.2331: : 990iter [01:46, 11.81iter/s]
Best score: 0.2331: : 990iter [01:46, 11.81iter/s]
Best score: 0.2331: : 991iter [01:46, 11.81iter/s]
Best score: 0.2331: : 992iter [01:46, 11.87iter/s]
Best score: 0.2331: : 992iter [01:46, 11.87iter/s]
Best score: 0.2331: : 993iter [01:46, 11.87iter/s]
Best score: 0.2331: : 994iter [01:46, 11.88iter/s]
Best score: 0.2331: : 994iter [01:46, 11.88iter/s]
Best score: 0.2331: : 995iter [01:46, 11.88iter/s]
Best score: 0.2331: : 996iter [01:46, 11.93iter/s]
Best score: 0.2331: : 996iter [01:46, 11.93iter/s]
Best score: 0.2331: : 997iter [01:46, 11.93iter/s]
Best score: 0.2331: : 998iter [01:46, 11.97iter/s]
Best score: 0.2331: : 998iter [01:47, 11.97iter/s]
[ITER 1000] Best: 0.2330
[PARAMS] Current best parameters:
  fx: 563.1214
  fy: 562.8621
  px: 1021.0256
  py: 785.2003
  k1: -0.04146186
  k2: 0.01308344
  k3: -0.00466186
  k4: 0.00067859
  p1: -0.00815093
  p2: -0.00810025
  p3: 0.01381625
  p4: 0.00804535
  s1: -0.0056
  s2: -0.0083
  s3: -0.0101
  s4: -0.0079
  tilt_x: -0.0350
  tilt_y: 0.0365
  scale: 3.0091
  rotation: -0.1568

Best score: 0.2330: : 999iter [01:47, 11.97iter/s]
Best score: 0.2330: : 1000iter [01:47, 11.79iter/s]
Best score: 0.2330: : 1000iter [01:47, 11.79iter/s]
Best score: 0.2330: : 1001iter [01:47, 11.79iter/s]
Best score: 0.2330: : 1002iter [01:47,  7.65iter/s]
Best score: 0.2330: : 1002iter [01:47,  7.65iter/s]
Best score: 0.2330: : 1003iter [01:47,  7.65iter/s]
Best score: 0.2330: : 1004iter [01:47,  8.55iter/s]
Best score: 0.2330: : 1004iter [01:47,  8.55iter/s]
Best score: 0.2330: : 1005iter [01:47,  8.55iter/s]
Best score: 0.2330: : 1006iter [01:47,  9.34iter/s]
Best score: 0.2330: : 1006iter [01:48,  9.34iter/s]
Best score: 0.2330: : 1007iter [01:48,  9.34iter/s]
Best score: 0.2330: : 1008iter [01:48, 10.01iter/s]
Best score: 0.2330: : 1008iter [01:48, 10.01iter/s]
Best score: 0.2330: : 1009iter [01:48, 10.01iter/s]
Best score: 0.2330: : 1010iter [01:48, 10.39iter/s]
Best score: 0.2330: : 1010iter [01:48, 10.39iter/s]
Best score: 0.2330: : 1011iter [01:48, 10.39iter/s]
Best score: 0.2330: : 1012iter [01:48, 10.80iter/s]
Best score: 0.2330: : 1012iter [01:48, 10.80iter/s]
Best score: 0.2330: : 1013iter [01:48, 10.80iter/s]
Best score: 0.2330: : 1014iter [01:48, 11.12iter/s]
Best score: 0.2330: : 1014iter [01:48, 11.12iter/s]
Best score: 0.2330: : 1015iter [01:48, 11.12iter/s]
Best score: 0.2330: : 1016iter [01:48, 11.36iter/s]
Best score: 0.2330: : 1016iter [01:48, 11.36iter/s]
Best score: 0.2330: : 1017iter [01:48, 11.36iter/s]
Best score: 0.2330: : 1018iter [01:48, 11.56iter/s]
Best score: 0.2330: : 1018iter [01:49, 11.56iter/s]
Best score: 0.2330: : 1019iter [01:49, 11.56iter/s]
Best score: 0.2330: : 1020iter [01:49, 11.50iter/s]
Best score: 0.2330: : 1020iter [01:49, 11.50iter/s]
Best score: 0.2330: : 1021iter [01:49, 11.50iter/s]
Best score: 0.2330: : 1022iter [01:49, 11.68iter/s]
Best score: 0.2330: : 1022iter [01:49, 11.68iter/s]
Best score: 0.2330: : 1023iter [01:49, 11.68iter/s]
Best score: 0.2330: : 1024iter [01:49, 11.79iter/s]
Best score: 0.2330: : 1024iter [01:49, 11.79iter/s]
Best score: 0.2330: : 1025iter [01:49, 11.79iter/s]
Best score: 0.2330: : 1026iter [01:49, 11.83iter/s]
Best score: 0.2330: : 1026iter [01:49, 11.83iter/s]
Best score: 0.2330: : 1027iter [01:49, 11.83iter/s]
Best score: 0.2330: : 1028iter [01:49, 11.90iter/s]
Best score: 0.2330: : 1028iter [01:49, 11.90iter/s]
Best score: 0.2330: : 1029iter [01:50, 11.90iter/s]
Best score: 0.2330: : 1030iter [01:50, 11.76iter/s]
Best score: 0.2330: : 1030iter [01:50, 11.76iter/s]
Best score: 0.2330: : 1031iter [01:50, 11.76iter/s]
Best score: 0.2330: : 1032iter [01:50, 11.84iter/s]
Best score: 0.2330: : 1032iter [01:50, 11.84iter/s]
Best score: 0.2330: : 1033iter [01:50, 11.84iter/s]
Best score: 0.2330: : 1034iter [01:50, 11.81iter/s]
Best score: 0.2330: : 1034iter [01:50, 11.81iter/s]
Best score: 0.2330: : 1035iter [01:50, 11.81iter/s]
Best score: 0.2330: : 1036iter [01:50, 11.87iter/s]
Best score: 0.2330: : 1036iter [01:50, 11.87iter/s]
Best score: 0.2330: : 1037iter [01:50, 11.87iter/s]
Best score: 0.2330: : 1038iter [01:50, 11.93iter/s]
Best score: 0.2330: : 1038iter [01:50, 11.93iter/s]
Best score: 0.2329: : 1039iter [01:51, 11.93iter/s]
Best score: 0.2329: : 1040iter [01:51,  9.05iter/s]
Best score: 0.2329: : 1040iter [01:51,  9.05iter/s]
Best score: 0.2329: : 1041iter [01:51,  9.05iter/s]
Best score: 0.2329: : 1042iter [01:51,  9.73iter/s]
Best score: 0.2329: : 1042iter [01:51,  9.73iter/s]
Best score: 0.2329: : 1043iter [01:51,  9.73iter/s]
Best score: 0.2329: : 1044iter [01:51, 10.35iter/s]
Best score: 0.2329: : 1044iter [01:51, 10.35iter/s]
Best score: 0.2329: : 1045iter [01:51, 10.35iter/s]
Best score: 0.2329: : 1046iter [01:51, 10.80iter/s]
Best score: 0.2329: : 1046iter [01:51, 10.80iter/s]
Best score: 0.2329: : 1047iter [01:51, 10.80iter/s]
Best score: 0.2329: : 1048iter [01:51, 11.16iter/s]
Best score: 0.2329: : 1048iter [01:51, 11.16iter/s]
[ITER 1050] Best: 0.2327
[PARAMS] Current best parameters:
  fx: 561.6185
  fy: 561.3613
  px: 1021.8181
  py: 785.3546
  k1: -0.04017175
  k2: 0.01316058
  k3: -0.00459795
  k4: 0.00058899
  p1: -0.00652790
  p2: -0.00718603
  p3: 0.01414016
  p4: 0.00661677
  s1: -0.0060
  s2: -0.0069
  s3: -0.0120
  s4: -0.0065
  tilt_x: -0.0373
  tilt_y: 0.0342
  scale: 3.0101
  rotation: -0.1541

Best score: 0.2327: : 1049iter [01:51, 11.16iter/s]
Best score: 0.2327: : 1050iter [01:51, 11.24iter/s]
Best score: 0.2327: : 1050iter [01:52, 11.24iter/s]
Best score: 0.2327: : 1051iter [01:52, 11.24iter/s]
Best score: 0.2327: : 1052iter [01:52,  7.50iter/s]
Best score: 0.2327: : 1052iter [01:52,  7.50iter/s]
Best score: 0.2327: : 1053iter [01:52,  7.50iter/s]
Best score: 0.2327: : 1054iter [01:52,  8.46iter/s]
Best score: 0.2327: : 1054iter [01:52,  8.46iter/s]
Best score: 0.2327: : 1055iter [01:52,  8.46iter/s]
Best score: 0.2327: : 1056iter [01:52,  9.29iter/s]
Best score: 0.2327: : 1056iter [01:52,  9.29iter/s]
Best score: 0.2327: : 1057iter [01:52,  9.29iter/s]
Best score: 0.2327: : 1058iter [01:52,  9.95iter/s]
Best score: 0.2327: : 1058iter [01:52,  9.95iter/s]
Best score: 0.2326: : 1059iter [01:53,  9.95iter/s]
Best score: 0.2326: : 1060iter [01:53, 10.35iter/s]
Best score: 0.2326: : 1060iter [01:53, 10.35iter/s]
Best score: 0.2326: : 1061iter [01:53, 10.35iter/s]
Best score: 0.2326: : 1062iter [01:53, 10.82iter/s]
Best score: 0.2326: : 1062iter [01:53, 10.82iter/s]
Best score: 0.2326: : 1063iter [01:53, 10.82iter/s]
Best score: 0.2326: : 1064iter [01:53, 11.12iter/s]
Best score: 0.2326: : 1064iter [01:53, 11.12iter/s]
Best score: 0.2326: : 1065iter [01:53, 11.12iter/s]
Best score: 0.2326: : 1066iter [01:53, 11.40iter/s]
Best score: 0.2326: : 1066iter [01:53, 11.40iter/s]
Best score: 0.2326: : 1067iter [01:53, 11.40iter/s]
Best score: 0.2326: : 1068iter [01:53, 11.59iter/s]
Best score: 0.2326: : 1068iter [01:53, 11.59iter/s]
Best score: 0.2324: : 1069iter [01:53, 11.59iter/s]
Best score: 0.2324: : 1070iter [01:53, 11.54iter/s]
Best score: 0.2324: : 1070iter [01:53, 11.54iter/s]
Best score: 0.2324: : 1071iter [01:54, 11.54iter/s]
Best score: 0.2324: : 1072iter [01:54, 11.69iter/s]
Best score: 0.2324: : 1072iter [01:54, 11.69iter/s]
Best score: 0.2324: : 1073iter [01:54, 11.69iter/s]
Best score: 0.2324: : 1074iter [01:54, 11.79iter/s]
Best score: 0.2324: : 1074iter [01:54, 11.79iter/s]
Best score: 0.2324: : 1075iter [01:54, 11.79iter/s]
Best score: 0.2324: : 1076iter [01:54, 11.88iter/s]
Best score: 0.2324: : 1076iter [01:54, 11.88iter/s]
Best score: 0.2324: : 1077iter [01:54, 11.88iter/s]
Best score: 0.2324: : 1078iter [01:54, 11.94iter/s]
Best score: 0.2324: : 1078iter [01:54, 11.94iter/s]
Best score: 0.2322: : 1079iter [01:54, 11.94iter/s]
Best score: 0.2322: : 1080iter [01:54, 11.79iter/s]
Best score: 0.2322: : 1080iter [01:54, 11.79iter/s]
Best score: 0.2322: : 1081iter [01:54, 11.79iter/s]
Best score: 0.2322: : 1082iter [01:54, 11.87iter/s]
Best score: 0.2322: : 1082iter [01:54, 11.87iter/s]
Best score: 0.2322: : 1083iter [01:55, 11.87iter/s]
Best score: 0.2322: : 1084iter [01:55, 11.88iter/s]
Best score: 0.2322: : 1084iter [01:55, 11.88iter/s]
Best score: 0.2322: : 1085iter [01:55, 11.88iter/s]
Best score: 0.2322: : 1086iter [01:55, 11.93iter/s]
Best score: 0.2322: : 1086iter [01:55, 11.93iter/s]
Best score: 0.2322: : 1087iter [01:55, 11.93iter/s]
Best score: 0.2322: : 1088iter [01:55, 11.92iter/s]
Best score: 0.2322: : 1088iter [01:55, 11.92iter/s]
Best score: 0.2321: : 1089iter [01:55, 11.92iter/s]
Best score: 0.2321: : 1090iter [01:55, 11.71iter/s]
Best score: 0.2321: : 1090iter [01:55, 11.71iter/s]
Best score: 0.2321: : 1091iter [01:55, 11.71iter/s]
Best score: 0.2321: : 1092iter [01:55, 11.81iter/s]
Best score: 0.2321: : 1092iter [01:55, 11.81iter/s]
Best score: 0.2321: : 1093iter [01:55, 11.81iter/s]
Best score: 0.2321: : 1094iter [01:55, 11.88iter/s]
Best score: 0.2321: : 1094iter [01:55, 11.88iter/s]
Best score: 0.2321: : 1095iter [01:56, 11.88iter/s]
Best score: 0.2321: : 1096iter [01:56, 11.86iter/s]
Best score: 0.2321: : 1096iter [01:56, 11.86iter/s]
Best score: 0.2321: : 1097iter [01:56, 11.86iter/s]
Best score: 0.2321: : 1098iter [01:56, 11.91iter/s]
Best score: 0.2321: : 1098iter [01:56, 11.91iter/s]
[ITER 1100] Best: 0.2321
[PARAMS] Current best parameters:
  fx: 559.8440
  fy: 559.6085
  px: 1021.6291
  py: 785.4800
  k1: -0.03974183
  k2: 0.01686149
  k3: -0.00809492
  k4: 0.00157518
  p1: -0.00566487
  p2: -0.00797479
  p3: 0.01768917
  p4: 0.00238391
  s1: -0.0093
  s2: -0.0024
  s3: -0.0161
  s4: -0.0025
  tilt_x: -0.0382
  tilt_y: 0.0334
  scale: 3.0113
  rotation: -0.1537

Best score: 0.2321: : 1099iter [01:56, 11.91iter/s]
Best score: 0.2321: : 1100iter [01:56, 11.75iter/s]
Best score: 0.2321: : 1100iter [01:56,  9.43iter/s]

[📈] Running L-BFGS-B polish after 1100 DE iterations...
  Polish improved score: 0.232077 -> 0.231735

[⭕] Ring refinement pass (3500mm diameter)...
  Points: 100,658 → 93,130 within 3500mm ring
  Ring polish did not improve score: 0.231735
  Success: True
  Tangential distortion: p1=-0.005701, p2=-0.008004, p3=0.017743, p4=0.002428
  ✓ Tangential correction is significant for corner improvement
[✅] Square reference optimization complete. Score: 0.2317
[✅] Parameters copied to: /working/MDC006_W020(6)_2026-07-10/calibration/params.json
[📌] Selecting best parameters...
[✅] Saved final refined parameters.


-------------------------------------------------------------------
                        Step 4: Undistortion                       
-------------------------------------------------------------------


[DEBUG] Parameters being applied to PTD conversion:
    fx: 559.8439788462953
    fy: 559.6084930223101
    px: 1021.6291369934908
    py: 785.4799569802424
    k1: -0.03976924129746345
    k2: 0.01684745017342637
    k3: -0.008094562230790827
    k4: 0.0015925839655284968
    p1: -0.005700607085639785
    p2: -0.008004323355730784
    p3: 0.017742716502311243
    p4: 0.0024283292607377364
    scale: 3.0112956444124346
    rotation: -0.15371338187825298
    mmpp: 3.4916408456670287

[🔄] Converting 2390 frames to PTD, creating debug images for 400 calibration frames...

📁 Rigs:   0%|          | 0/4 [00:00<?, ?rig/s]

   🔄 2000L:   0%|          | 0/584 [00:00<?, ?frame/s]

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   🔄 2000L:  10%|▉         | 57/584 [00:00<00:02, 178.87frame/s]

   🔄 2000L:  13%|█▎        | 75/584 [00:00<00:02, 178.53frame/s]

   🔄 2000L:  16%|█▌        | 94/584 [00:00<00:02, 179.83frame/s]

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   🔄 2000L:  45%|████▌     | 265/584 [00:01<00:01, 181.34frame/s]

   🔄 2000L:  49%|████▊     | 284/584 [00:01<00:01, 180.40frame/s]

   🔄 2000L:  52%|█████▏    | 303/584 [00:01<00:01, 179.71frame/s]

   🔄 2000L:  55%|█████▍    | 321/584 [00:01<00:01, 179.54frame/s]

   🔄 2000L:  58%|█████▊    | 339/584 [00:01<00:01, 179.64frame/s]

   🔄 2000L:  61%|██████▏   | 358/584 [00:01<00:01, 179.76frame/s]

   🔄 2000L:  65%|██████▍   | 377/584 [00:02<00:01, 180.30frame/s]

   🔄 2000L:  68%|██████▊   | 396/584 [00:02<00:01, 180.85frame/s]

   🔄 2000L:  71%|███████   | 415/584 [00:02<00:00, 181.54frame/s]

   🔄 2000L:  74%|███████▍  | 434/584 [00:02<00:00, 180.48frame/s]

   🔄 2000L:  78%|███████▊  | 453/584 [00:02<00:00, 181.14frame/s]

   🔄 2000L:  81%|████████  | 472/584 [00:02<00:00, 181.48frame/s]

   🔄 2000L:  84%|████████▍ | 491/584 [00:02<00:00, 181.32frame/s]

   🔄 2000L:  87%|████████▋ | 510/584 [00:02<00:00, 181.17frame/s]

   🔄 2000L:  91%|█████████ | 529/584 [00:02<00:00, 180.87frame/s]

   🔄 2000L:  94%|█████████▍| 548/584 [00:03<00:00, 180.57frame/s]

   🔄 2000L:  97%|█████████▋| 567/584 [00:03<00:00, 180.10frame/s]

                                                                  
📁 Rigs:  25%|██▌       | 1/4 [00:05<00:17,  5.91s/rig]

   🔄 2000R:   0%|          | 0/578 [00:00<?, ?frame/s]

   🔄 2000R:   3%|▎         | 19/578 [00:00<00:03, 180.57frame/s]

   🔄 2000R:   7%|▋         | 38/578 [00:00<00:02, 181.56frame/s]

   🔄 2000R:  10%|▉         | 57/578 [00:00<00:02, 182.28frame/s]

   🔄 2000R:  13%|█▎        | 76/578 [00:00<00:02, 183.10frame/s]

   🔄 2000R:  16%|█▋        | 95/578 [00:00<00:04, 103.28frame/s]

   🔄 2000R:  20%|█▉        | 114/578 [00:00<00:03, 121.38frame/s]

   🔄 2000R:  23%|██▎       | 133/578 [00:00<00:03, 136.34frame/s]

   🔄 2000R:  26%|██▋       | 152/578 [00:01<00:02, 148.42frame/s]

   🔄 2000R:  30%|██▉       | 171/578 [00:01<00:02, 157.94frame/s]

   🔄 2000R:  33%|███▎      | 190/578 [00:01<00:02, 164.91frame/s]

   🔄 2000R:  36%|███▌      | 208/578 [00:01<00:02, 168.79frame/s]

   🔄 2000R:  39%|███▉      | 226/578 [00:01<00:02, 171.72frame/s]

   🔄 2000R:  42%|████▏     | 244/578 [00:01<00:01, 173.65frame/s]

   🔄 2000R:  45%|████▌     | 262/578 [00:01<00:01, 174.87frame/s]

   🔄 2000R:  48%|████▊     | 280/578 [00:01<00:01, 175.72frame/s]

   🔄 2000R:  52%|█████▏    | 298/578 [00:01<00:01, 176.24frame/s]

   🔄 2000R:  55%|█████▍    | 316/578 [00:01<00:01, 176.82frame/s]

   🔄 2000R:  58%|█████▊    | 334/578 [00:02<00:01, 177.75frame/s]

   🔄 2000R:  61%|██████    | 352/578 [00:02<00:01, 178.03frame/s]

   🔄 2000R:  64%|██████▍   | 370/578 [00:02<00:01, 178.50frame/s]

   🔄 2000R:  67%|██████▋   | 389/578 [00:02<00:01, 179.75frame/s]

   🔄 2000R:  71%|███████   | 408/578 [00:02<00:00, 180.52frame/s]

   🔄 2000R:  74%|███████▍  | 427/578 [00:02<00:00, 181.31frame/s]

   🔄 2000R:  77%|███████▋  | 446/578 [00:02<00:00, 181.94frame/s]

   🔄 2000R:  80%|████████  | 465/578 [00:02<00:00, 182.35frame/s]

   🔄 2000R:  84%|████████▎ | 484/578 [00:02<00:00, 182.61frame/s]

   🔄 2000R:  87%|████████▋ | 503/578 [00:02<00:00, 181.67frame/s]

   🔄 2000R:  90%|█████████ | 522/578 [00:03<00:00, 181.03frame/s]

   🔄 2000R:  94%|█████████▎| 541/578 [00:03<00:00, 180.83frame/s]

   🔄 2000R:  97%|█████████▋| 560/578 [00:03<00:00, 180.67frame/s]

                                                                  
📁 Rigs:  50%|█████     | 2/4 [00:11<00:11,  5.81s/rig]

   🔄 1500:   0%|          | 0/729 [00:00<?, ?frame/s]

   🔄 1500:   3%|▎         | 19/729 [00:00<00:03, 187.97frame/s]

   🔄 1500:   5%|▌         | 38/729 [00:00<00:03, 182.79frame/s]

   🔄 1500:   8%|▊         | 57/729 [00:00<00:03, 181.28frame/s]

   🔄 1500:  10%|█         | 76/729 [00:00<00:03, 181.27frame/s]

   🔄 1500:  13%|█▎        | 95/729 [00:00<00:03, 182.23frame/s]

   🔄 1500:  16%|█▌        | 114/729 [00:00<00:03, 182.63frame/s]

   🔄 1500:  18%|█▊        | 133/729 [00:00<00:03, 182.92frame/s]

   🔄 1500:  21%|██        | 152/729 [00:00<00:03, 182.71frame/s]

   🔄 1500:  23%|██▎       | 171/729 [00:00<00:03, 182.23frame/s]

   🔄 1500:  26%|██▌       | 190/729 [00:01<00:02, 182.31frame/s]

   🔄 1500:  29%|██▊       | 209/729 [00:01<00:02, 182.26frame/s]

   🔄 1500:  31%|███▏      | 228/729 [00:01<00:02, 182.95frame/s]

   🔄 1500:  34%|███▍      | 247/729 [00:01<00:02, 183.30frame/s]

   🔄 1500:  36%|███▋      | 266/729 [00:01<00:02, 183.28frame/s]

   🔄 1500:  39%|███▉      | 285/729 [00:01<00:02, 183.50frame/s]

   🔄 1500:  42%|████▏     | 304/729 [00:01<00:02, 184.73frame/s]

   🔄 1500:  44%|████▍     | 323/729 [00:01<00:02, 185.68frame/s]

   🔄 1500:  47%|████▋     | 342/729 [00:01<00:02, 186.35frame/s]

   🔄 1500:  50%|████▉     | 361/729 [00:01<00:01, 186.94frame/s]

   🔄 1500:  52%|█████▏    | 380/729 [00:02<00:01, 187.39frame/s]

   🔄 1500:  55%|█████▍    | 399/729 [00:02<00:01, 187.82frame/s]

   🔄 1500:  57%|█████▋    | 418/729 [00:02<00:01, 187.76frame/s]

   🔄 1500:  60%|█████▉    | 437/729 [00:02<00:01, 187.80frame/s]

   🔄 1500:  63%|██████▎   | 456/729 [00:02<00:01, 187.54frame/s]

   🔄 1500:  65%|██████▌   | 475/729 [00:02<00:01, 186.26frame/s]

   🔄 1500:  68%|██████▊   | 494/729 [00:02<00:01, 185.51frame/s]

   🔄 1500:  70%|███████   | 513/729 [00:02<00:01, 185.31frame/s]

   🔄 1500:  73%|███████▎  | 532/729 [00:02<00:01, 185.02frame/s]

   🔄 1500:  76%|███████▌  | 551/729 [00:02<00:00, 183.96frame/s]

   🔄 1500:  78%|███████▊  | 570/729 [00:03<00:00, 183.50frame/s]

   🔄 1500:  81%|████████  | 589/729 [00:03<00:00, 183.60frame/s]

   🔄 1500:  83%|████████▎ | 608/729 [00:03<00:00, 183.80frame/s]

   🔄 1500:  86%|████████▌ | 627/729 [00:03<00:00, 184.18frame/s]

   🔄 1500:  89%|████████▊ | 646/729 [00:03<00:00, 184.09frame/s]

   🔄 1500:  91%|█████████ | 665/729 [00:03<00:00, 183.50frame/s]

   🔄 1500:  94%|█████████▍| 684/729 [00:03<00:00, 182.57frame/s]

   🔄 1500:  96%|█████████▋| 703/729 [00:03<00:00, 181.62frame/s]

   🔄 1500:  99%|█████████▉| 722/729 [00:03<00:00, 181.42frame/s]

                                                                 
📁 Rigs:  75%|███████▌  | 3/4 [00:18<00:06,  6.37s/rig]

   🔄 1000:   0%|          | 0/499 [00:00<?, ?frame/s]

   🔄 1000:   4%|▍         | 19/499 [00:00<00:02, 185.31frame/s]

   🔄 1000:   8%|▊         | 39/499 [00:00<00:02, 191.19frame/s]

   🔄 1000:  12%|█▏        | 59/499 [00:00<00:02, 190.80frame/s]

   🔄 1000:  16%|█▌        | 79/499 [00:00<00:02, 190.54frame/s]

   🔄 1000:  20%|█▉        | 99/499 [00:00<00:02, 190.32frame/s]

   🔄 1000:  24%|██▍       | 119/499 [00:00<00:01, 190.17frame/s]

   🔄 1000:  28%|██▊       | 139/499 [00:00<00:01, 189.66frame/s]

   🔄 1000:  32%|███▏      | 158/499 [00:00<00:01, 188.81frame/s]

   🔄 1000:  35%|███▌      | 177/499 [00:00<00:01, 188.02frame/s]

   🔄 1000:  39%|███▉      | 196/499 [00:01<00:01, 187.69frame/s]

   🔄 1000:  43%|████▎     | 216/499 [00:01<00:01, 188.71frame/s]

   🔄 1000:  47%|████▋     | 236/499 [00:01<00:01, 189.53frame/s]

   🔄 1000:  51%|█████▏    | 256/499 [00:01<00:01, 190.36frame/s]

   🔄 1000:  55%|█████▌    | 276/499 [00:01<00:01, 190.85frame/s]

   🔄 1000:  59%|█████▉    | 296/499 [00:01<00:01, 191.20frame/s]

   🔄 1000:  63%|██████▎   | 316/499 [00:01<00:00, 191.20frame/s]

   🔄 1000:  67%|██████▋   | 336/499 [00:01<00:00, 189.89frame/s]

   🔄 1000:  71%|███████   | 355/499 [00:01<00:00, 189.18frame/s]

   🔄 1000:  75%|███████▍  | 374/499 [00:01<00:00, 189.11frame/s]

   🔄 1000:  79%|███████▉  | 393/499 [00:02<00:00, 188.92frame/s]

   🔄 1000:  83%|████████▎ | 413/499 [00:02<00:00, 189.85frame/s]

   🔄 1000:  87%|████████▋ | 433/499 [00:02<00:00, 190.46frame/s]

   🔄 1000:  91%|█████████ | 453/499 [00:02<00:00, 190.61frame/s]

   🔄 1000:  95%|█████████▍| 473/499 [00:02<00:00, 190.41frame/s]

   🔄 1000:  99%|█████████▉| 493/499 [00:02<00:00, 189.51frame/s]

                                                                 
📁 Rigs: 100%|██████████| 4/4 [00:23<00:00,  5.77s/rig]
📁 Rigs: 100%|██████████| 4/4 [00:23<00:00,  5.89s/rig]
[✅] Saved PTDs: /working/MDC006_W020(6)_2026-07-10/calibration/debug/4_undistorted/output/ptd

📁 Rigs:   0%|          | 0/4 [00:00<?, ?rig/s]

   🔄 2000L:   0%|          | 0/100 [00:00<?, ?frame/s]

   🔄 2000L:  18%|█▊        | 18/100 [00:00<00:00, 178.08frame/s]

   🔄 2000L:  37%|███▋      | 37/100 [00:00<00:00, 180.95frame/s]

   🔄 2000L:  56%|█████▌    | 56/100 [00:00<00:00, 180.50frame/s]

   🔄 2000L:  75%|███████▌  | 75/100 [00:00<00:00, 180.57frame/s]

   🔄 2000L:  94%|█████████▍| 94/100 [00:00<00:00, 180.68frame/s]

                                                                 
📁 Rigs:  25%|██▌       | 1/4 [00:00<00:02,  1.10rig/s]

   🔄 2000R:   0%|          | 0/100 [00:00<?, ?frame/s]

   🔄 2000R:  19%|█▉        | 19/100 [00:00<00:00, 180.80frame/s]

   🔄 2000R:  38%|███▊      | 38/100 [00:00<00:00, 179.68frame/s]

   🔄 2000R:  56%|█████▌    | 56/100 [00:00<00:00, 177.95frame/s]

   🔄 2000R:  74%|███████▍  | 74/100 [00:00<00:00, 178.17frame/s]

   🔄 2000R:  92%|█████████▏| 92/100 [00:00<00:00, 178.40frame/s]

                                                                 
📁 Rigs:  50%|█████     | 2/4 [00:01<00:01,  1.09rig/s]

   🔄 1500:   0%|          | 0/100 [00:00<?, ?frame/s]

   🔄 1500:  19%|█▉        | 19/100 [00:00<00:00, 180.76frame/s]

   🔄 1500:  38%|███▊      | 38/100 [00:00<00:00, 180.56frame/s]

   🔄 1500:  57%|█████▋    | 57/100 [00:00<00:00, 182.68frame/s]

   🔄 1500:  76%|███████▌  | 76/100 [00:00<00:00, 182.15frame/s]

   🔄 1500:  95%|█████████▌| 95/100 [00:00<00:00, 181.39frame/s]

                                                                
📁 Rigs:  75%|███████▌  | 3/4 [00:02<00:00,  1.00rig/s]

   🔄 1000:   0%|          | 0/100 [00:00<?, ?frame/s]

   🔄 1000:  19%|█▉        | 19/100 [00:00<00:00, 184.50frame/s]

   🔄 1000:  38%|███▊      | 38/100 [00:00<00:00, 183.91frame/s]

   🔄 1000:  57%|█████▋    | 57/100 [00:00<00:00, 184.36frame/s]

   🔄 1000:  76%|███████▌  | 76/100 [00:00<00:00, 182.71frame/s]

   🔄 1000:  95%|█████████▌| 95/100 [00:00<00:00, 183.05frame/s]

                                                                
📁 Rigs: 100%|██████████| 4/4 [00:03<00:00,  1.05rig/s]
📁 Rigs: 100%|██████████| 4/4 [00:03<00:00,  1.05rig/s]
[✅] Saved PTDs: /working/MDC006_W020(6)_2026-07-10/calibration/debug/4_undistorted/temp_ptd
[WARN] No .tfd files found for serial extraction
[WARN] Failed to extract serial number from .tfd file. Check that .tfd files exist and contain 'LASERbidh' or 'LASERbidg' pattern. Using 'unknown' as fallback.

📤 Writing LUT:   0%|          | 0/3080448 [00:00<?, ?px/s]
📤 Writing LUT:   3%|▎         | 84468/3080448 [00:00<00:03, 844672.75px/s]
📤 Writing LUT:   6%|▌         | 171919/3080448 [00:00<00:03, 862219.66px/s]
📤 Writing LUT:   8%|▊         | 258937/3080448 [00:00<00:03, 865852.05px/s]
📤 Writing LUT:  11%|█         | 345879/3080448 [00:00<00:03, 867257.69px/s]
📤 Writing LUT:  14%|█▍        | 432605/3080448 [00:00<00:03, 866991.22px/s]
📤 Writing LUT:  17%|█▋        | 519305/3080448 [00:00<00:02, 866035.71px/s]
📤 Writing LUT:  20%|█▉        | 609858/3080448 [00:00<00:02, 878933.45px/s]
📤 Writing LUT:  23%|██▎       | 702042/3080448 [00:00<00:02, 892580.81px/s]
📤 Writing LUT:  26%|██▌       | 794803/3080448 [00:00<00:02, 903525.81px/s]
📤 Writing LUT:  29%|██▊       | 885158/3080448 [00:01<00:02, 896607.44px/s]
📤 Writing LUT:  32%|███▏      | 974832/3080448 [00:01<00:02, 892510.23px/s]
📤 Writing LUT:  35%|███▍      | 1064094/3080448 [00:01<00:02, 888108.72px/s]
📤 Writing LUT:  37%|███▋      | 1154780/3080448 [00:01<00:02, 893739.16px/s]
📤 Writing LUT:  40%|████      | 1244819/3080448 [00:01<00:02, 895735.21px/s]
📤 Writing LUT:  43%|████▎     | 1334402/3080448 [00:01<00:01, 893794.28px/s]
📤 Writing LUT:  46%|████▌     | 1423788/3080448 [00:01<00:01, 888722.42px/s]
📤 Writing LUT:  49%|████▉     | 1515548/3080448 [00:01<00:01, 897341.53px/s]
📤 Writing LUT:  52%|█████▏    | 1608486/3080448 [00:01<00:01, 906918.02px/s]
📤 Writing LUT:  55%|█████▌    | 1699192/3080448 [00:01<00:01, 896573.97px/s]
📤 Writing LUT:  58%|█████▊    | 1788883/3080448 [00:02<00:01, 892143.07px/s]
📤 Writing LUT:  61%|██████    | 1878121/3080448 [00:02<00:01, 888979.77px/s]
📤 Writing LUT:  64%|██████▍   | 1970085/3080448 [00:02<00:01, 898087.53px/s]
📤 Writing LUT:  67%|██████▋   | 2059915/3080448 [00:02<00:01, 893378.84px/s]
📤 Writing LUT:  70%|██████▉   | 2149270/3080448 [00:02<00:01, 891705.56px/s]
📤 Writing LUT:  73%|███████▎  | 2239740/3080448 [00:02<00:00, 895574.92px/s]
📤 Writing LUT:  76%|███████▌  | 2329309/3080448 [00:02<00:00, 892698.93px/s]
📤 Writing LUT:  79%|███████▊  | 2418662/3080448 [00:02<00:00, 892945.14px/s]
📤 Writing LUT:  81%|████████▏ | 2508546/3080448 [00:02<00:00, 894699.55px/s]
📤 Writing LUT:  84%|████████▍ | 2598021/3080448 [00:02<00:00, 894402.97px/s]
📤 Writing LUT:  87%|████████▋ | 2689434/3080448 [00:03<00:00, 900306.61px/s]
📤 Writing LUT:  90%|█████████ | 2780790/3080448 [00:03<00:00, 904273.97px/s]
📤 Writing LUT:  93%|█████████▎| 2872539/3080448 [00:03<00:00, 908232.01px/s]
📤 Writing LUT:  96%|█████████▌| 2964139/3080448 [00:03<00:00, 910559.54px/s]
📤 Writing LUT:  99%|█████████▉| 3055198/3080448 [00:03<00:00, 910277.41px/s]
📤 Writing LUT: 100%|██████████| 3080448/3080448 [00:03<00:00, 893568.72px/s]
[✅] LUT written to: /working/MDC006_W020(6)_2026-07-10/calibration/debug/4_undistorted/output/LUT.lut
[WARN] Folder name 'MDC006_W020(6)_2026-07-10' does not match expected pattern MDC042_W007_5_28_2025. Using simple naming convention.
[✅] LUT copied to: /working/MDC006_W020(6)_2026-07-10/calibration/MDC006_W020(6)_2026-07-10_unknown.lut

-------------------------------------------------------------------
                          Step 5: Heatmap                          
-------------------------------------------------------------------

[ℹ️] Detected device type: SMD_P3D (rigs: [1000, 1500, 2000]mm)

📁 Rigs (heatmap):   0%|          | 0/4 [00:00<?, ?rig/s]

   🔥 2000L:   0%|          | 0/584 [00:00<?, ?frame/s]

   🔥 2000L:   1%|          | 7/584 [00:00<00:08, 69.64frame/s]

   🔥 2000L:   3%|▎         | 16/584 [00:00<00:07, 77.84frame/s]

   🔥 2000L:   4%|▍         | 25/584 [00:00<00:07, 78.92frame/s]

   🔥 2000L:   6%|▌         | 33/584 [00:00<00:07, 78.48frame/s]

   🔥 2000L:   7%|▋         | 42/584 [00:00<00:06, 79.09frame/s]

   🔥 2000L:   9%|▊         | 51/584 [00:00<00:06, 79.68frame/s]

   🔥 2000L:  10%|█         | 59/584 [00:00<00:06, 79.71frame/s]

   🔥 2000L:  12%|█▏        | 68/584 [00:00<00:06, 80.36frame/s]

   🔥 2000L:  13%|█▎        | 77/584 [00:00<00:06, 81.44frame/s]

   🔥 2000L:  15%|█▍        | 86/584 [00:01<00:06, 81.83frame/s]

   🔥 2000L:  16%|█▋        | 95/584 [00:01<00:05, 83.05frame/s]

   🔥 2000L:  18%|█▊        | 104/584 [00:01<00:05, 84.00frame/s]

   🔥 2000L:  20%|█▉        | 114/584 [00:01<00:05, 87.06frame/s]

   🔥 2000L:  21%|██        | 124/584 [00:01<00:05, 89.68frame/s]

   🔥 2000L:  23%|██▎       | 134/584 [00:01<00:04, 91.80frame/s]

   🔥 2000L:  25%|██▍       | 144/584 [00:01<00:04, 94.07frame/s]

   🔥 2000L:  26%|██▋       | 154/584 [00:01<00:04, 95.62frame/s]

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                                                                 [✅] 2000L: /working/MDC006_W020(6)_2026-07-10/calibration/debug/5_heatmap/2000L_heatmap.png
[✅] 2000L (fitted): /working/MDC006_W020(6)_2026-07-10/calibration/debug/5_heatmap/2000L_heatmap_fitted.png

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                                                                 [✅] 2000R: /working/MDC006_W020(6)_2026-07-10/calibration/debug/5_heatmap/2000R_heatmap.png
[✅] 2000R (fitted): /working/MDC006_W020(6)_2026-07-10/calibration/debug/5_heatmap/2000R_heatmap_fitted.png

📁 Rigs (heatmap):  50%|█████     | 2/4 [00:15<00:15,  7.93s/rig]

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                                                                [✅] 1500: /working/MDC006_W020(6)_2026-07-10/calibration/debug/5_heatmap/1500_heatmap.png
[✅] 1500 (fitted): /working/MDC006_W020(6)_2026-07-10/calibration/debug/5_heatmap/1500_heatmap_fitted.png

📁 Rigs (heatmap):  75%|███████▌  | 3/4 [00:26<00:08,  8.96s/rig]

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   🔥 1000:  37%|███▋      | 185/499 [00:02<00:03, 92.92frame/s]

   🔥 1000:  39%|███▉      | 195/499 [00:02<00:03, 93.56frame/s]

   🔥 1000:  41%|████      | 205/499 [00:02<00:03, 94.35frame/s]

   🔥 1000:  43%|████▎     | 215/499 [00:02<00:02, 95.09frame/s]

   🔥 1000:  45%|████▌     | 225/499 [00:02<00:02, 96.05frame/s]

   🔥 1000:  47%|████▋     | 235/499 [00:02<00:02, 96.88frame/s]

   🔥 1000:  49%|████▉     | 245/499 [00:02<00:02, 97.68frame/s]

   🔥 1000:  51%|█████     | 255/499 [00:02<00:02, 97.78frame/s]

   🔥 1000:  53%|█████▎    | 265/499 [00:02<00:02, 97.65frame/s]

   🔥 1000:  55%|█████▌    | 275/499 [00:02<00:02, 97.33frame/s]

   🔥 1000:  57%|█████▋    | 285/499 [00:03<00:02, 95.69frame/s]

   🔥 1000:  59%|█████▉    | 295/499 [00:03<00:02, 93.76frame/s]

   🔥 1000:  61%|██████    | 305/499 [00:03<00:02, 92.00frame/s]

   🔥 1000:  63%|██████▎   | 315/499 [00:03<00:02, 90.10frame/s]

   🔥 1000:  65%|██████▌   | 325/499 [00:03<00:01, 88.94frame/s]

   🔥 1000:  67%|██████▋   | 334/499 [00:03<00:01, 88.16frame/s]

   🔥 1000:  69%|██████▊   | 343/499 [00:03<00:01, 87.58frame/s]

   🔥 1000:  71%|███████   | 352/499 [00:03<00:01, 87.32frame/s]

   🔥 1000:  72%|███████▏  | 361/499 [00:03<00:01, 87.17frame/s]

   🔥 1000:  74%|███████▍  | 370/499 [00:04<00:01, 87.11frame/s]

   🔥 1000:  76%|███████▌  | 379/499 [00:04<00:01, 87.08frame/s]

   🔥 1000:  78%|███████▊  | 388/499 [00:04<00:01, 86.91frame/s]

   🔥 1000:  80%|███████▉  | 397/499 [00:04<00:01, 86.97frame/s]

   🔥 1000:  81%|████████▏ | 406/499 [00:04<00:01, 87.35frame/s]

   🔥 1000:  83%|████████▎ | 416/499 [00:04<00:00, 88.79frame/s]

   🔥 1000:  85%|████████▌ | 426/499 [00:04<00:00, 90.05frame/s]

   🔥 1000:  87%|████████▋ | 436/499 [00:04<00:00, 91.17frame/s]

   🔥 1000:  89%|████████▉ | 446/499 [00:04<00:00, 90.57frame/s]

   🔥 1000:  91%|█████████▏| 456/499 [00:04<00:00, 90.20frame/s]

   🔥 1000:  93%|█████████▎| 466/499 [00:05<00:00, 90.19frame/s]

   🔥 1000:  95%|█████████▌| 476/499 [00:05<00:00, 88.61frame/s]

   🔥 1000:  97%|█████████▋| 485/499 [00:05<00:00, 88.25frame/s]

   🔥 1000:  99%|█████████▉| 494/499 [00:05<00:00, 87.92frame/s]

                                                                [✅] 1000: /working/MDC006_W020(6)_2026-07-10/calibration/debug/5_heatmap/1000_heatmap.png
[✅] 1000 (fitted): /working/MDC006_W020(6)_2026-07-10/calibration/debug/5_heatmap/1000_heatmap_fitted.png

📁 Rigs (heatmap): 100%|██████████| 4/4 [00:32<00:00,  7.86s/rig]
📁 Rigs (heatmap): 100%|██████████| 4/4 [00:32<00:00,  8.06s/rig]
[✅] all_rigs_average.png
[✅] all_rigs_best.png
[✅] all_rigs_average_fitted.png
[✅] all_rigs_best_fitted.png
[✅] Heatmaps saved to: /working/MDC006_W020(6)_2026-07-10/calibration/debug/5_heatmap
[🏁] Finished processing MDC006_W020(6)_2026-07-10


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