2026-09-11T01:06:17 - INFO: Slick 0.0.8a13

🟢 Starting Calibration Pipeline

=== Processing MDC021_W042_2026-09-09 ===
2026-09-11T01:06:17 - INFO: Camera ID: 15091853
2026-09-11T01:06:17 - INFO: Wand ID: 
2026-09-11T01:06:17 - INFO: Recorded At: 2026-09-09T12:24:32Z

-------------------------------------------------------------------
                        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 2 las0.zip files to process
Processing Rigs:   0%|          | 0/2 [00:00<?, ?it/s][INFO] Filtered 534 stationary frames, 574 remain

→ 1000 (574 images) Phase 1:   0%|          | 0/574 [00:00<?, ?it/s][A
→ 1000 (574 images) Phase 1:   0%|          | 1/574 [00:00<04:30,  2.12it/s][A
→ 1000 (574 images) Phase 1:   1%|          | 3/574 [00:00<01:32,  6.19it/s][A
→ 1000 (574 images) Phase 1:   2%|▏         | 14/574 [00:00<00:18, 30.89it/s][A
→ 1000 (574 images) Phase 1:   6%|▌         | 33/574 [00:00<00:10, 51.48it/s][A
→ 1000 (574 images) Phase 1:   7%|▋         | 40/574 [00:01<00:10, 49.06it/s][A
→ 1000 (574 images) Phase 1:   8%|▊         | 48/574 [00:01<00:09, 55.02it/s][A
→ 1000 (574 images) Phase 1:  11%|█▏        | 65/574 [00:01<00:07, 69.24it/s][A
→ 1000 (574 images) Phase 1:  13%|█▎        | 73/574 [00:01<00:07, 63.84it/s][A
→ 1000 (574 images) Phase 1:  14%|█▍        | 80/574 [00:01<00:07, 64.12it/s][A
→ 1000 (574 images) Phase 1:  17%|█▋        | 97/574 [00:01<00:06, 75.33it/s][A
→ 1000 (574 images) Phase 1:  18%|█▊        | 105/574 [00:01<00:06, 68.47it/s][A
→ 1000 (574 images) Phase 1:  20%|█▉        | 112/574 [00:02<00:06, 67.73it/s][A
→ 1000 (574 images) Phase 1:  22%|██▏       | 129/574 [00:02<00:05, 77.20it/s][A
→ 1000 (574 images) Phase 1:  24%|██▍       | 137/574 [00:02<00:06, 69.32it/s][A
→ 1000 (574 images) Phase 1:  25%|██▌       | 144/574 [00:02<00:06, 68.49it/s][A
→ 1000 (574 images) Phase 1:  28%|██▊       | 160/574 [00:02<00:04, 88.64it/s][A
→ 1000 (574 images) Phase 1:  30%|██▉       | 170/574 [00:02<00:05, 69.51it/s][A
→ 1000 (574 images) Phase 1:  31%|███       | 178/574 [00:02<00:05, 68.11it/s][A
→ 1000 (574 images) Phase 1:  34%|███▎      | 193/574 [00:03<00:05, 75.44it/s][A
→ 1000 (574 images) Phase 1:  35%|███▌      | 201/574 [00:03<00:05, 70.05it/s][A
→ 1000 (574 images) Phase 1:  36%|███▋      | 209/574 [00:03<00:05, 69.59it/s][A
→ 1000 (574 images) Phase 1:  39%|███▉      | 224/574 [00:03<00:04, 84.66it/s][A
→ 1000 (574 images) Phase 1:  41%|████      | 233/574 [00:03<00:04, 69.58it/s][A
→ 1000 (574 images) Phase 1:  42%|████▏     | 241/574 [00:03<00:04, 68.35it/s][A
→ 1000 (574 images) Phase 1:  44%|████▍     | 254/574 [00:03<00:03, 82.18it/s][A
→ 1000 (574 images) Phase 1:  46%|████▌     | 263/574 [00:04<00:04, 66.65it/s][A
→ 1000 (574 images) Phase 1:  47%|████▋     | 271/574 [00:04<00:04, 69.05it/s][A
→ 1000 (574 images) Phase 1:  49%|████▉     | 282/574 [00:04<00:03, 76.46it/s][A
→ 1000 (574 images) Phase 1:  51%|█████     | 291/574 [00:04<00:03, 70.82it/s][A
→ 1000 (574 images) Phase 1:  52%|█████▏    | 299/574 [00:04<00:03, 72.52it/s][A
→ 1000 (574 images) Phase 1:  53%|█████▎    | 307/574 [00:04<00:03, 73.27it/s][A
→ 1000 (574 images) Phase 1:  55%|█████▌    | 317/574 [00:04<00:03, 77.45it/s][A
→ 1000 (574 images) Phase 1:  57%|█████▋    | 325/574 [00:04<00:03, 69.34it/s][A
→ 1000 (574 images) Phase 1:  58%|█████▊    | 334/574 [00:05<00:03, 71.39it/s][A
→ 1000 (574 images) Phase 1:  60%|█████▉    | 343/574 [00:05<00:03, 71.24it/s][A
→ 1000 (574 images) Phase 1:  62%|██████▏   | 354/574 [00:05<00:03, 73.21it/s][A
→ 1000 (574 images) Phase 1:  63%|██████▎   | 362/574 [00:05<00:02, 73.17it/s][A
→ 1000 (574 images) Phase 1:  64%|██████▍   | 370/574 [00:05<00:02, 72.41it/s][A
→ 1000 (574 images) Phase 1:  66%|██████▌   | 380/574 [00:05<00:02, 77.71it/s][A
→ 1000 (574 images) Phase 1:  68%|██████▊   | 388/574 [00:05<00:02, 69.62it/s][A
→ 1000 (574 images) Phase 1:  69%|██████▉   | 397/574 [00:05<00:02, 73.84it/s][A
→ 1000 (574 images) Phase 1:  71%|███████   | 405/574 [00:06<00:02, 74.26it/s][A
→ 1000 (574 images) Phase 1:  72%|███████▏  | 413/574 [00:06<00:02, 74.60it/s][A
→ 1000 (574 images) Phase 1:  73%|███████▎  | 421/574 [00:06<00:02, 64.68it/s][A
→ 1000 (574 images) Phase 1:  75%|███████▍  | 430/574 [00:06<00:02, 70.24it/s][A
→ 1000 (574 images) Phase 1:  76%|███████▋  | 439/574 [00:06<00:01, 73.47it/s][A
→ 1000 (574 images) Phase 1:  78%|███████▊  | 449/574 [00:06<00:01, 77.70it/s][A
→ 1000 (574 images) Phase 1:  80%|███████▉  | 457/574 [00:06<00:01, 72.58it/s][A
→ 1000 (574 images) Phase 1:  81%|████████▏ | 467/574 [00:06<00:01, 79.60it/s][A
→ 1000 (574 images) Phase 1:  83%|████████▎ | 476/574 [00:07<00:01, 71.14it/s][A
→ 1000 (574 images) Phase 1:  84%|████████▍ | 484/574 [00:07<00:01, 69.84it/s][A
→ 1000 (574 images) Phase 1:  86%|████████▌ | 493/574 [00:07<00:01, 70.99it/s][A
→ 1000 (574 images) Phase 1:  87%|████████▋ | 502/574 [00:07<00:01, 71.43it/s][A
→ 1000 (574 images) Phase 1:  89%|████████▉ | 510/574 [00:07<00:00, 71.99it/s][A
→ 1000 (574 images) Phase 1:  90%|█████████ | 518/574 [00:07<00:00, 69.55it/s][A
→ 1000 (574 images) Phase 1:  92%|█████████▏| 526/574 [00:07<00:00, 72.05it/s][A
→ 1000 (574 images) Phase 1:  93%|█████████▎| 534/574 [00:07<00:00, 70.62it/s][A
→ 1000 (574 images) Phase 1:  94%|█████████▍| 542/574 [00:07<00:00, 72.19it/s][A
→ 1000 (574 images) Phase 1:  96%|█████████▌| 550/574 [00:08<00:00, 72.76it/s][A
→ 1000 (574 images) Phase 1:  99%|█████████▉| 567/574 [00:08<00:00, 95.55it/s][A
                                                                              [A
→ 1000 Phase 2: corners:   0%|          | 0/574 [00:00<?, ?it/s][A
→ 1000 Phase 2: corners:   0%|          | 1/574 [00:00<01:41,  5.62it/s][A
→ 1000 Phase 2: corners:   3%|▎         | 15/574 [00:00<00:08, 64.43it/s][A
→ 1000 Phase 2: corners:   5%|▍         | 26/574 [00:00<00:06, 78.48it/s][A
→ 1000 Phase 2: corners:   7%|▋         | 42/574 [00:00<00:05, 103.36it/s][A
→ 1000 Phase 2: corners:  10%|█         | 59/574 [00:00<00:04, 122.72it/s][A
→ 1000 Phase 2: corners:  13%|█▎        | 72/574 [00:00<00:04, 119.85it/s][A
→ 1000 Phase 2: corners:  15%|█▍        | 85/574 [00:00<00:04, 121.09it/s][A
→ 1000 Phase 2: corners:  17%|█▋        | 98/574 [00:00<00:04, 115.38it/s][A
→ 1000 Phase 2: corners:  19%|█▉        | 111/574 [00:01<00:03, 117.91it/s][A
→ 1000 Phase 2: corners:  22%|██▏       | 125/574 [00:01<00:03, 120.82it/s][A
→ 1000 Phase 2: corners:  25%|██▍       | 142/574 [00:01<00:03, 131.10it/s][A
→ 1000 Phase 2: corners:  27%|██▋       | 156/574 [00:01<00:03, 132.30it/s][A
→ 1000 Phase 2: corners:  30%|██▉       | 171/574 [00:01<00:02, 136.60it/s][A
→ 1000 Phase 2: corners:  33%|███▎      | 188/574 [00:01<00:02, 146.22it/s][A
→ 1000 Phase 2: corners:  35%|███▌      | 203/574 [00:01<00:02, 134.21it/s][A
→ 1000 Phase 2: corners:  38%|███▊      | 219/574 [00:01<00:02, 136.10it/s][A
→ 1000 Phase 2: corners:  41%|████      | 234/574 [00:01<00:02, 137.06it/s][A
→ 1000 Phase 2: corners:  44%|████▎     | 251/574 [00:02<00:02, 142.68it/s][A
→ 1000 Phase 2: corners:  46%|████▋     | 266/574 [00:02<00:02, 142.96it/s][A
→ 1000 Phase 2: corners:  49%|████▉     | 284/574 [00:02<00:01, 151.47it/s][A
→ 1000 Phase 2: corners:  52%|█████▏    | 300/574 [00:02<00:01, 147.72it/s][A
→ 1000 Phase 2: corners:  55%|█████▍    | 315/574 [00:02<00:01, 147.46it/s][A
→ 1000 Phase 2: corners:  57%|█████▋    | 330/574 [00:02<00:01, 142.18it/s][A
→ 1000 Phase 2: corners:  60%|██████    | 345/574 [00:02<00:01, 139.97it/s][A
→ 1000 Phase 2: corners:  63%|██████▎   | 362/574 [00:02<00:01, 145.06it/s][A
→ 1000 Phase 2: corners:  66%|██████▌   | 377/574 [00:02<00:01, 143.53it/s][A
→ 1000 Phase 2: corners:  68%|██████▊   | 392/574 [00:03<00:01, 144.94it/s][A
→ 1000 Phase 2: corners:  71%|███████   | 407/574 [00:03<00:01, 140.85it/s][A
→ 1000 Phase 2: corners:  74%|███████▍  | 426/574 [00:03<00:00, 154.39it/s][A
→ 1000 Phase 2: corners:  77%|███████▋  | 442/574 [00:03<00:00, 147.18it/s][A
→ 1000 Phase 2: corners:  80%|███████▉  | 458/574 [00:03<00:00, 148.75it/s][A
→ 1000 Phase 2: corners:  83%|████████▎ | 475/574 [00:03<00:00, 153.13it/s][A
→ 1000 Phase 2: corners:  86%|████████▌ | 494/574 [00:03<00:00, 159.98it/s][A
→ 1000 Phase 2: corners:  89%|████████▉ | 511/574 [00:03<00:00, 150.57it/s][A
→ 1000 Phase 2: corners:  92%|█████████▏| 527/574 [00:03<00:00, 141.56it/s][A
→ 1000 Phase 2: corners:  95%|█████████▍| 543/574 [00:04<00:00, 143.45it/s][A
                                                                           [A[PASS2] Frame 0000321: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000322: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000323: fixed corners {2, 3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000325: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000327: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000391: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000392: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000393: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000394: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000396: fixed corners {3} (was_fixed=False, 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=False, 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=False)
[PASS2] Frame 0000404: fixed corners {3} (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 0000415: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000416: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000428: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000429: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000430: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000431: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000458: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000468: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000473: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000476: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000482: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000483: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000485: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000487: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000508: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000509: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000510: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000511: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000565: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000566: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000567: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000568: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000569: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000570: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000571: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000842: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000843: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000844: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000845: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000902: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000903: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000904: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000905: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000906: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000907: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000908: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000909: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001039: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001040: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001041: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001042: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001049: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001050: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001051: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001052: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001106: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001107: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001108: fixed corners {2, 3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001110: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001118: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001119: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001120: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001121: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000323: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000324: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000325: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000393: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000398: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000399: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000400: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000403: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000415: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000430: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000473: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000485: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000510: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000567: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000569: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000570: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000844: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000904: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000908: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001041: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001051: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001108: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001109: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001120: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Summary: 42 frames fixed, 36 untrusted, 574 total

→ 1000 Phase 3: finalize:   0%|          | 0/574 [00:00<?, ?it/s][A
→ 1000 Phase 3: finalize:   1%|          | 5/574 [00:00<00:11, 49.87it/s][A
→ 1000 Phase 3: finalize:   2%|▏         | 11/574 [00:00<00:10, 55.20it/s][A
→ 1000 Phase 3: finalize:   3%|▎         | 18/574 [00:00<00:09, 58.25it/s][A
→ 1000 Phase 3: finalize:   4%|▍         | 25/574 [00:00<00:09, 59.35it/s][A
→ 1000 Phase 3: finalize:   6%|▌         | 32/574 [00:00<00:09, 60.20it/s][A
→ 1000 Phase 3: finalize:   7%|▋         | 39/574 [00:00<00:08, 60.49it/s][A
→ 1000 Phase 3: finalize:   8%|▊         | 46/574 [00:00<00:08, 60.59it/s][A
→ 1000 Phase 3: finalize:   9%|▉         | 53/574 [00:00<00:08, 60.34it/s][A
→ 1000 Phase 3: finalize:  10%|█         | 60/574 [00:01<00:08, 58.99it/s][A
→ 1000 Phase 3: finalize:  11%|█▏        | 66/574 [00:01<00:08, 57.08it/s][A
→ 1000 Phase 3: finalize:  13%|█▎        | 72/574 [00:01<00:08, 55.95it/s][A
→ 1000 Phase 3: finalize:  14%|█▎        | 78/574 [00:01<00:09, 54.96it/s][A
→ 1000 Phase 3: finalize:  15%|█▍        | 84/574 [00:01<00:09, 54.36it/s][A
→ 1000 Phase 3: finalize:  16%|█▌        | 90/574 [00:01<00:08, 53.90it/s][A
→ 1000 Phase 3: finalize:  17%|█▋        | 96/574 [00:01<00:08, 53.52it/s][A
→ 1000 Phase 3: finalize:  18%|█▊        | 102/574 [00:01<00:08, 53.27it/s][A
→ 1000 Phase 3: finalize:  19%|█▉        | 108/574 [00:01<00:08, 53.13it/s][A
→ 1000 Phase 3: finalize:  20%|█▉        | 114/574 [00:02<00:08, 52.98it/s][A
→ 1000 Phase 3: finalize:  21%|██        | 120/574 [00:02<00:08, 52.85it/s][A
→ 1000 Phase 3: finalize:  22%|██▏       | 126/574 [00:02<00:08, 52.63it/s][A
→ 1000 Phase 3: finalize:  23%|██▎       | 132/574 [00:02<00:08, 52.43it/s][A
→ 1000 Phase 3: finalize:  24%|██▍       | 138/574 [00:02<00:08, 52.41it/s][A
→ 1000 Phase 3: finalize:  25%|██▌       | 144/574 [00:02<00:08, 52.42it/s][A
→ 1000 Phase 3: finalize:  26%|██▌       | 150/574 [00:02<00:08, 52.48it/s][A
→ 1000 Phase 3: finalize:  27%|██▋       | 156/574 [00:02<00:07, 52.44it/s][A
→ 1000 Phase 3: finalize:  28%|██▊       | 162/574 [00:02<00:07, 52.51it/s][A
→ 1000 Phase 3: finalize:  29%|██▉       | 168/574 [00:03<00:07, 52.52it/s][A
→ 1000 Phase 3: finalize:  30%|███       | 174/574 [00:03<00:07, 52.55it/s][A
→ 1000 Phase 3: finalize:  31%|███▏      | 180/574 [00:03<00:07, 52.55it/s][A
→ 1000 Phase 3: finalize:  32%|███▏      | 186/574 [00:03<00:07, 52.50it/s][A
→ 1000 Phase 3: finalize:  33%|███▎      | 192/574 [00:03<00:07, 52.42it/s][A
→ 1000 Phase 3: finalize:  34%|███▍      | 198/574 [00:03<00:07, 52.44it/s][A
→ 1000 Phase 3: finalize:  36%|███▌      | 204/574 [00:03<00:07, 52.32it/s][A
→ 1000 Phase 3: finalize:  37%|███▋      | 210/574 [00:03<00:07, 51.61it/s][A
→ 1000 Phase 3: finalize:  38%|███▊      | 216/574 [00:03<00:06, 51.36it/s][A
→ 1000 Phase 3: finalize:  39%|███▊      | 222/574 [00:04<00:06, 51.23it/s][A
→ 1000 Phase 3: finalize:  40%|███▉      | 228/574 [00:04<00:06, 51.02it/s][A
→ 1000 Phase 3: finalize:  41%|████      | 234/574 [00:04<00:06, 50.74it/s][A
→ 1000 Phase 3: finalize:  42%|████▏     | 240/574 [00:04<00:06, 50.48it/s][A
→ 1000 Phase 3: finalize:  43%|████▎     | 246/574 [00:04<00:06, 49.84it/s][A
→ 1000 Phase 3: finalize:  44%|████▎     | 251/574 [00:04<00:06, 49.40it/s][A
→ 1000 Phase 3: finalize:  45%|████▍     | 256/574 [00:04<00:06, 49.37it/s][A
→ 1000 Phase 3: finalize:  45%|████▌     | 261/574 [00:04<00:06, 49.07it/s][A
→ 1000 Phase 3: finalize:  46%|████▋     | 266/574 [00:05<00:06, 48.88it/s][A
→ 1000 Phase 3: finalize:  47%|████▋     | 271/574 [00:05<00:06, 48.69it/s][A
→ 1000 Phase 3: finalize:  48%|████▊     | 276/574 [00:05<00:06, 48.73it/s][A
→ 1000 Phase 3: finalize:  49%|████▉     | 281/574 [00:05<00:06, 48.67it/s][A
→ 1000 Phase 3: finalize:  50%|████▉     | 286/574 [00:05<00:05, 48.79it/s][A
→ 1000 Phase 3: finalize:  51%|█████     | 291/574 [00:05<00:05, 49.11it/s][A
→ 1000 Phase 3: finalize:  52%|█████▏    | 296/574 [00:05<00:05, 49.26it/s][A
→ 1000 Phase 3: finalize:  52%|█████▏    | 301/574 [00:05<00:05, 49.44it/s][A
→ 1000 Phase 3: finalize:  53%|█████▎    | 306/574 [00:05<00:05, 49.42it/s][A
→ 1000 Phase 3: finalize:  54%|█████▍    | 311/574 [00:05<00:05, 49.17it/s][A
→ 1000 Phase 3: finalize:  55%|█████▌    | 316/574 [00:06<00:05, 48.40it/s][A
→ 1000 Phase 3: finalize:  56%|█████▌    | 321/574 [00:06<00:05, 48.30it/s][A
→ 1000 Phase 3: finalize:  57%|█████▋    | 326/574 [00:06<00:05, 48.28it/s][A
→ 1000 Phase 3: finalize:  58%|█████▊    | 331/574 [00:06<00:05, 48.05it/s][A
→ 1000 Phase 3: finalize:  59%|█████▊    | 336/574 [00:06<00:04, 48.13it/s][A
→ 1000 Phase 3: finalize:  59%|█████▉    | 341/574 [00:06<00:04, 48.37it/s][A
→ 1000 Phase 3: finalize:  60%|██████    | 346/574 [00:06<00:04, 48.75it/s][A
→ 1000 Phase 3: finalize:  61%|██████    | 351/574 [00:06<00:04, 49.07it/s][A
→ 1000 Phase 3: finalize:  62%|██████▏   | 357/574 [00:06<00:04, 49.36it/s][A
→ 1000 Phase 3: finalize:  63%|██████▎   | 363/574 [00:06<00:04, 49.57it/s][A
→ 1000 Phase 3: finalize:  64%|██████▍   | 369/574 [00:07<00:04, 49.83it/s][A
→ 1000 Phase 3: finalize:  65%|██████▌   | 375/574 [00:07<00:03, 50.01it/s][A
→ 1000 Phase 3: finalize:  66%|██████▋   | 381/574 [00:07<00:03, 50.24it/s][A
→ 1000 Phase 3: finalize:  67%|██████▋   | 387/574 [00:07<00:03, 50.46it/s][A
→ 1000 Phase 3: finalize:  68%|██████▊   | 393/574 [00:07<00:03, 50.80it/s][A
→ 1000 Phase 3: finalize:  70%|██████▉   | 399/574 [00:07<00:03, 51.15it/s][A
→ 1000 Phase 3: finalize:  71%|███████   | 405/574 [00:07<00:03, 51.53it/s][A
→ 1000 Phase 3: finalize:  72%|███████▏  | 411/574 [00:07<00:03, 51.77it/s][A
→ 1000 Phase 3: finalize:  73%|███████▎  | 417/574 [00:08<00:03, 52.00it/s][A
→ 1000 Phase 3: finalize:  74%|███████▎  | 423/574 [00:08<00:02, 52.11it/s][A
→ 1000 Phase 3: finalize:  75%|███████▍  | 429/574 [00:08<00:02, 52.27it/s][A
→ 1000 Phase 3: finalize:  76%|███████▌  | 435/574 [00:08<00:02, 52.38it/s][A
→ 1000 Phase 3: finalize:  77%|███████▋  | 441/574 [00:08<00:02, 52.47it/s][A
→ 1000 Phase 3: finalize:  78%|███████▊  | 447/574 [00:08<00:02, 52.46it/s][A
→ 1000 Phase 3: finalize:  79%|███████▉  | 453/574 [00:08<00:02, 52.47it/s][A
→ 1000 Phase 3: finalize:  80%|███████▉  | 459/574 [00:08<00:02, 52.52it/s][A
→ 1000 Phase 3: finalize:  81%|████████  | 465/574 [00:08<00:02, 52.03it/s][A
→ 1000 Phase 3: finalize:  82%|████████▏ | 471/574 [00:09<00:01, 51.80it/s][A
→ 1000 Phase 3: finalize:  83%|████████▎ | 477/574 [00:09<00:01, 51.71it/s][A
→ 1000 Phase 3: finalize:  84%|████████▍ | 483/574 [00:09<00:01, 51.64it/s][A
→ 1000 Phase 3: finalize:  85%|████████▌ | 489/574 [00:09<00:01, 51.51it/s][A
→ 1000 Phase 3: finalize:  86%|████████▌ | 495/574 [00:09<00:01, 51.47it/s][A
→ 1000 Phase 3: finalize:  87%|████████▋ | 501/574 [00:09<00:01, 51.32it/s][A
→ 1000 Phase 3: finalize:  88%|████████▊ | 507/574 [00:09<00:01, 51.56it/s][A
→ 1000 Phase 3: finalize:  89%|████████▉ | 513/574 [00:09<00:01, 51.73it/s][A
→ 1000 Phase 3: finalize:  90%|█████████ | 519/574 [00:10<00:01, 51.77it/s][A
→ 1000 Phase 3: finalize:  91%|█████████▏| 525/574 [00:10<00:00, 51.69it/s][A
→ 1000 Phase 3: finalize:  93%|█████████▎| 531/574 [00:10<00:00, 51.61it/s][A
→ 1000 Phase 3: finalize:  94%|█████████▎| 537/574 [00:10<00:00, 51.48it/s][A
→ 1000 Phase 3: finalize:  95%|█████████▍| 543/574 [00:10<00:00, 51.47it/s][A
→ 1000 Phase 3: finalize:  96%|█████████▌| 549/574 [00:10<00:00, 51.49it/s][A
→ 1000 Phase 3: finalize:  97%|█████████▋| 555/574 [00:10<00:00, 51.41it/s][A
→ 1000 Phase 3: finalize:  98%|█████████▊| 561/574 [00:10<00:00, 51.35it/s][A
→ 1000 Phase 3: finalize:  99%|█████████▉| 567/574 [00:10<00:00, 51.31it/s][A
→ 1000 Phase 3: finalize: 100%|█████████▉| 573/574 [00:11<00:00, 51.34it/s][A
                                                                           [A
[TIMING] 1000 — 574 frames
  Phase 1  radial detect   (parallel)  :   8.39s  (14.6 ms/frame)
  Phase 2a corner detect   (parallel)  :   4.12s  (7.2 ms/frame)
  Phase 2b corner fix      (sequential):   1.78s
  Phase 3  finalize        (sequential):  11.08s  (19.3 ms/frame)
    decode + undistort                 :   5.58s  (9.7 ms/frame)
    corner apply + refinement          :   2.47s  (4.3 ms/frame)
    segment                            :   2.35s  (4.1 ms/frame)
    smooth                             :   0.49s  (0.9 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  25.37s

Processing Rigs:  50%|█████     | 1/2 [00:29<00:29, 29.19s/it][INFO] Filtered 307 stationary frames, 709 remain

→ 500 (709 images) Phase 1:   0%|          | 0/709 [00:00<?, ?it/s][A
→ 500 (709 images) Phase 1:   0%|          | 1/709 [00:00<07:44,  1.53it/s][A
→ 500 (709 images) Phase 1:   3%|▎         | 20/709 [00:00<00:19, 35.17it/s][A
→ 500 (709 images) Phase 1:   5%|▍         | 33/709 [00:01<00:16, 40.46it/s][A
→ 500 (709 images) Phase 1:   6%|▌         | 42/709 [00:01<00:14, 46.56it/s][A
→ 500 (709 images) Phase 1:   9%|▉         | 63/709 [00:01<00:08, 77.94it/s][A
→ 500 (709 images) Phase 1:  11%|█         | 76/709 [00:01<00:10, 58.54it/s][A
→ 500 (709 images) Phase 1:  14%|█▎        | 96/709 [00:01<00:07, 79.02it/s][A
→ 500 (709 images) Phase 1:  15%|█▌        | 108/709 [00:02<00:09, 61.64it/s][A
→ 500 (709 images) Phase 1:  18%|█▊        | 128/709 [00:02<00:07, 80.57it/s][A
→ 500 (709 images) Phase 1:  20%|█▉        | 140/709 [00:02<00:08, 63.27it/s][A
→ 500 (709 images) Phase 1:  22%|██▏       | 159/709 [00:02<00:06, 83.05it/s][A
→ 500 (709 images) Phase 1:  24%|██▍       | 172/709 [00:02<00:08, 63.30it/s][A
→ 500 (709 images) Phase 1:  27%|██▋       | 191/709 [00:03<00:06, 81.93it/s][A
→ 500 (709 images) Phase 1:  29%|██▉       | 204/709 [00:03<00:07, 64.30it/s][A
→ 500 (709 images) Phase 1:  31%|███▏      | 223/709 [00:03<00:05, 82.03it/s][A
→ 500 (709 images) Phase 1:  33%|███▎      | 235/709 [00:03<00:07, 64.07it/s][A
→ 500 (709 images) Phase 1:  36%|███▌      | 254/709 [00:03<00:05, 81.83it/s][A
→ 500 (709 images) Phase 1:  38%|███▊      | 266/709 [00:04<00:06, 63.61it/s][A
→ 500 (709 images) Phase 1:  39%|███▉      | 277/709 [00:04<00:06, 69.28it/s][A
→ 500 (709 images) Phase 1:  41%|████      | 288/709 [00:04<00:05, 71.17it/s][A
→ 500 (709 images) Phase 1:  42%|████▏     | 297/709 [00:04<00:07, 57.32it/s][A
→ 500 (709 images) Phase 1:  45%|████▍     | 317/709 [00:04<00:04, 80.98it/s][A
→ 500 (709 images) Phase 1:  46%|████▋     | 328/709 [00:05<00:06, 59.91it/s][A
→ 500 (709 images) Phase 1:  49%|████▉     | 348/709 [00:05<00:04, 81.81it/s][A
→ 500 (709 images) Phase 1:  51%|█████     | 360/709 [00:05<00:05, 61.19it/s][A
→ 500 (709 images) Phase 1:  54%|█████▎    | 380/709 [00:05<00:03, 82.33it/s][A
→ 500 (709 images) Phase 1:  55%|█████▌    | 393/709 [00:06<00:04, 63.45it/s][A
→ 500 (709 images) Phase 1:  58%|█████▊    | 413/709 [00:06<00:03, 83.75it/s][A
→ 500 (709 images) Phase 1:  60%|██████    | 426/709 [00:06<00:04, 64.44it/s][A
→ 500 (709 images) Phase 1:  62%|██████▏   | 443/709 [00:06<00:03, 79.35it/s][A
→ 500 (709 images) Phase 1:  64%|██████▍   | 455/709 [00:06<00:04, 62.47it/s][A
→ 500 (709 images) Phase 1:  66%|██████▋   | 471/709 [00:07<00:03, 77.43it/s][A
→ 500 (709 images) Phase 1:  68%|██████▊   | 483/709 [00:07<00:03, 61.76it/s][A
→ 500 (709 images) Phase 1:  70%|███████   | 498/709 [00:07<00:02, 75.03it/s][A
→ 500 (709 images) Phase 1:  72%|███████▏  | 511/709 [00:07<00:02, 84.87it/s][A
→ 500 (709 images) Phase 1:  74%|███████▍  | 523/709 [00:07<00:02, 67.73it/s][A
→ 500 (709 images) Phase 1:  76%|███████▌  | 539/709 [00:07<00:02, 83.83it/s][A
→ 500 (709 images) Phase 1:  78%|███████▊  | 551/709 [00:08<00:02, 62.98it/s][A
→ 500 (709 images) Phase 1:  80%|███████▉  | 564/709 [00:08<00:01, 73.99it/s][A
→ 500 (709 images) Phase 1:  81%|████████▏ | 577/709 [00:08<00:02, 63.08it/s][A
→ 500 (709 images) Phase 1:  83%|████████▎ | 591/709 [00:08<00:01, 74.76it/s][A
→ 500 (709 images) Phase 1:  85%|████████▌ | 606/709 [00:08<00:01, 88.85it/s][A
→ 500 (709 images) Phase 1:  87%|████████▋ | 618/709 [00:09<00:01, 68.13it/s][A
→ 500 (709 images) Phase 1:  89%|████████▊ | 629/709 [00:09<00:01, 74.99it/s][A
→ 500 (709 images) Phase 1:  90%|█████████ | 640/709 [00:09<00:00, 81.86it/s][A
→ 500 (709 images) Phase 1:  92%|█████████▏| 650/709 [00:09<00:00, 65.44it/s][A
→ 500 (709 images) Phase 1:  93%|█████████▎| 662/709 [00:09<00:00, 75.18it/s][A
→ 500 (709 images) Phase 1:  95%|█████████▍| 673/709 [00:09<00:00, 61.67it/s][A
→ 500 (709 images) Phase 1:  97%|█████████▋| 687/709 [00:10<00:00, 73.26it/s][A
→ 500 (709 images) Phase 1:  99%|█████████▉| 705/709 [00:10<00:00, 83.14it/s][A
                                                                             [A
→ 500 Phase 2: corners:   0%|          | 0/709 [00:00<?, ?it/s][A
→ 500 Phase 2: corners:   0%|          | 1/709 [00:00<03:29,  3.37it/s][A
→ 500 Phase 2: corners:   2%|▏         | 14/709 [00:00<00:15, 43.79it/s][A
→ 500 Phase 2: corners:   4%|▎         | 26/709 [00:00<00:10, 64.03it/s][A
→ 500 Phase 2: corners:   6%|▌         | 39/709 [00:00<00:08, 81.03it/s][A
→ 500 Phase 2: corners:   7%|▋         | 52/709 [00:00<00:07, 93.17it/s][A
→ 500 Phase 2: corners:   9%|▉         | 66/709 [00:00<00:06, 105.92it/s][A
→ 500 Phase 2: corners:  11%|█         | 78/709 [00:00<00:06, 103.21it/s][A
→ 500 Phase 2: corners:  13%|█▎        | 91/709 [00:01<00:05, 110.55it/s][A
→ 500 Phase 2: corners:  15%|█▍        | 103/709 [00:01<00:05, 111.34it/s][A
→ 500 Phase 2: corners:  16%|█▌        | 115/709 [00:01<00:06, 94.92it/s] [A
→ 500 Phase 2: corners:  18%|█▊        | 130/709 [00:01<00:05, 105.89it/s][A
→ 500 Phase 2: corners:  21%|██        | 146/709 [00:01<00:04, 117.11it/s][A
→ 500 Phase 2: corners:  22%|██▏       | 159/709 [00:01<00:04, 119.01it/s][A
→ 500 Phase 2: corners:  24%|██▍       | 173/709 [00:01<00:04, 123.98it/s][A
→ 500 Phase 2: corners:  26%|██▌       | 186/709 [00:01<00:04, 124.88it/s][A
→ 500 Phase 2: corners:  28%|██▊       | 199/709 [00:01<00:04, 124.10it/s][A
→ 500 Phase 2: corners:  30%|██▉       | 212/709 [00:02<00:04, 122.85it/s][A
→ 500 Phase 2: corners:  32%|███▏      | 227/709 [00:02<00:03, 130.45it/s][A
→ 500 Phase 2: corners:  34%|███▍      | 241/709 [00:02<00:03, 128.15it/s][A
→ 500 Phase 2: corners:  37%|███▋      | 260/709 [00:02<00:03, 145.66it/s][A
→ 500 Phase 2: corners:  39%|███▉      | 275/709 [00:02<00:03, 137.07it/s][A
→ 500 Phase 2: corners:  41%|████      | 291/709 [00:02<00:02, 141.59it/s][A
→ 500 Phase 2: corners:  43%|████▎     | 307/709 [00:02<00:02, 144.61it/s][A
→ 500 Phase 2: corners:  46%|████▌     | 326/709 [00:02<00:02, 154.07it/s][A
→ 500 Phase 2: corners:  49%|████▊     | 344/709 [00:02<00:02, 160.25it/s][A
→ 500 Phase 2: corners:  51%|█████     | 361/709 [00:03<00:02, 156.05it/s][A
→ 500 Phase 2: corners:  53%|█████▎    | 377/709 [00:03<00:02, 146.73it/s][A
→ 500 Phase 2: corners:  56%|█████▌    | 394/709 [00:03<00:02, 150.62it/s][A
→ 500 Phase 2: corners:  58%|█████▊    | 410/709 [00:03<00:01, 150.54it/s][A
→ 500 Phase 2: corners:  60%|██████    | 426/709 [00:03<00:01, 149.38it/s][A
→ 500 Phase 2: corners:  62%|██████▏   | 441/709 [00:03<00:01, 148.46it/s][A
→ 500 Phase 2: corners:  65%|██████▍   | 459/709 [00:03<00:01, 154.95it/s][A
→ 500 Phase 2: corners:  67%|██████▋   | 475/709 [00:03<00:01, 149.72it/s][A
→ 500 Phase 2: corners:  69%|██████▉   | 492/709 [00:03<00:01, 152.63it/s][A
→ 500 Phase 2: corners:  72%|███████▏  | 510/709 [00:04<00:01, 158.42it/s][A
→ 500 Phase 2: corners:  74%|███████▍  | 527/709 [00:04<00:01, 161.12it/s][A
→ 500 Phase 2: corners:  77%|███████▋  | 544/709 [00:04<00:01, 159.16it/s][A
→ 500 Phase 2: corners:  79%|███████▉  | 560/709 [00:04<00:00, 152.76it/s][A
→ 500 Phase 2: corners:  81%|████████  | 576/709 [00:04<00:00, 149.12it/s][A
→ 500 Phase 2: corners:  84%|████████▍ | 594/709 [00:04<00:00, 155.56it/s][A
→ 500 Phase 2: corners:  86%|████████▋ | 613/709 [00:04<00:00, 161.93it/s][A
→ 500 Phase 2: corners:  89%|████████▉ | 633/709 [00:04<00:00, 172.47it/s][A
→ 500 Phase 2: corners:  92%|█████████▏| 654/709 [00:04<00:00, 174.43it/s][A
→ 500 Phase 2: corners:  95%|█████████▍| 672/709 [00:05<00:00, 169.12it/s][A
                                                                          [A[PASS2] Frame 0000250: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000251: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000252: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000254: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000349: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000357: fixed corners {2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000358: fixed corners {2, 3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000364: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000780: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000940: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000941: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000942: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000943: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000946: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000947: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000948: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000949: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000984: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000988: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000990: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000991: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000993: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000994: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000997: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000252: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000361: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000942: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Summary: 14 frames fixed, 16 untrusted, 709 total

→ 500 Phase 3: finalize:   0%|          | 0/709 [00:00<?, ?it/s][A
→ 500 Phase 3: finalize:   1%|          | 6/709 [00:00<00:12, 56.77it/s][A
→ 500 Phase 3: finalize:   2%|▏         | 13/709 [00:00<00:11, 59.62it/s][A
→ 500 Phase 3: finalize:   3%|▎         | 20/709 [00:00<00:11, 61.01it/s][A
→ 500 Phase 3: finalize:   4%|▍         | 27/709 [00:00<00:11, 61.47it/s][A
→ 500 Phase 3: finalize:   5%|▍         | 34/709 [00:00<00:10, 61.88it/s][A
→ 500 Phase 3: finalize:   6%|▌         | 41/709 [00:00<00:10, 62.49it/s][A
→ 500 Phase 3: finalize:   7%|▋         | 48/709 [00:00<00:10, 62.98it/s][A
→ 500 Phase 3: finalize:   8%|▊         | 55/709 [00:00<00:11, 59.28it/s][A
→ 500 Phase 3: finalize:   9%|▊         | 61/709 [00:01<00:11, 56.83it/s][A
→ 500 Phase 3: finalize:   9%|▉         | 67/709 [00:01<00:11, 55.23it/s][A
→ 500 Phase 3: finalize:  10%|█         | 73/709 [00:01<00:11, 54.28it/s][A
→ 500 Phase 3: finalize:  11%|█         | 79/709 [00:01<00:11, 53.63it/s][A
→ 500 Phase 3: finalize:  12%|█▏        | 85/709 [00:01<00:11, 53.09it/s][A
→ 500 Phase 3: finalize:  13%|█▎        | 91/709 [00:01<00:11, 52.75it/s][A
→ 500 Phase 3: finalize:  14%|█▎        | 97/709 [00:01<00:11, 52.50it/s][A
→ 500 Phase 3: finalize:  15%|█▍        | 103/709 [00:01<00:11, 52.45it/s][A
→ 500 Phase 3: finalize:  15%|█▌        | 109/709 [00:01<00:11, 52.53it/s][A
→ 500 Phase 3: finalize:  16%|█▌        | 115/709 [00:02<00:11, 52.52it/s][A
→ 500 Phase 3: finalize:  17%|█▋        | 121/709 [00:02<00:11, 52.56it/s][A
→ 500 Phase 3: finalize:  18%|█▊        | 127/709 [00:02<00:11, 52.52it/s][A
→ 500 Phase 3: finalize:  19%|█▉        | 133/709 [00:02<00:10, 52.53it/s][A
→ 500 Phase 3: finalize:  20%|█▉        | 139/709 [00:02<00:10, 52.37it/s][A
→ 500 Phase 3: finalize:  20%|██        | 145/709 [00:02<00:10, 52.47it/s][A
→ 500 Phase 3: finalize:  21%|██▏       | 151/709 [00:02<00:10, 52.63it/s][A
→ 500 Phase 3: finalize:  22%|██▏       | 157/709 [00:02<00:10, 52.79it/s][A
→ 500 Phase 3: finalize:  23%|██▎       | 163/709 [00:02<00:10, 52.86it/s][A
→ 500 Phase 3: finalize:  24%|██▍       | 169/709 [00:03<00:10, 52.91it/s][A
→ 500 Phase 3: finalize:  25%|██▍       | 175/709 [00:03<00:10, 52.83it/s][A
→ 500 Phase 3: finalize:  26%|██▌       | 181/709 [00:03<00:09, 52.86it/s][A
→ 500 Phase 3: finalize:  26%|██▋       | 187/709 [00:03<00:09, 52.85it/s][A
→ 500 Phase 3: finalize:  27%|██▋       | 193/709 [00:03<00:09, 52.78it/s][A
→ 500 Phase 3: finalize:  28%|██▊       | 199/709 [00:03<00:09, 52.64it/s][A
→ 500 Phase 3: finalize:  29%|██▉       | 205/709 [00:03<00:09, 52.63it/s][A
→ 500 Phase 3: finalize:  30%|██▉       | 211/709 [00:03<00:09, 52.55it/s][A
→ 500 Phase 3: finalize:  31%|███       | 217/709 [00:03<00:09, 52.41it/s][A
→ 500 Phase 3: finalize:  31%|███▏      | 223/709 [00:04<00:09, 52.36it/s][A
→ 500 Phase 3: finalize:  32%|███▏      | 229/709 [00:04<00:09, 52.40it/s][A
→ 500 Phase 3: finalize:  33%|███▎      | 235/709 [00:04<00:09, 52.31it/s][A
→ 500 Phase 3: finalize:  34%|███▍      | 241/709 [00:04<00:08, 52.12it/s][A
→ 500 Phase 3: finalize:  35%|███▍      | 247/709 [00:04<00:08, 51.63it/s][A
→ 500 Phase 3: finalize:  36%|███▌      | 253/709 [00:04<00:08, 51.50it/s][A
→ 500 Phase 3: finalize:  37%|███▋      | 259/709 [00:04<00:08, 51.71it/s][A
→ 500 Phase 3: finalize:  37%|███▋      | 265/709 [00:04<00:08, 51.82it/s][A
→ 500 Phase 3: finalize:  38%|███▊      | 271/709 [00:05<00:08, 51.99it/s][A
→ 500 Phase 3: finalize:  39%|███▉      | 277/709 [00:05<00:08, 52.04it/s][A
→ 500 Phase 3: finalize:  40%|███▉      | 283/709 [00:05<00:08, 51.98it/s][A
→ 500 Phase 3: finalize:  41%|████      | 289/709 [00:05<00:08, 52.12it/s][A
→ 500 Phase 3: finalize:  42%|████▏     | 295/709 [00:05<00:07, 52.26it/s][A
→ 500 Phase 3: finalize:  42%|████▏     | 301/709 [00:05<00:07, 52.30it/s][A
→ 500 Phase 3: finalize:  43%|████▎     | 307/709 [00:05<00:07, 52.31it/s][A
→ 500 Phase 3: finalize:  44%|████▍     | 313/709 [00:05<00:07, 52.31it/s][A
→ 500 Phase 3: finalize:  45%|████▍     | 319/709 [00:05<00:07, 52.25it/s][A
→ 500 Phase 3: finalize:  46%|████▌     | 325/709 [00:06<00:07, 52.25it/s][A
→ 500 Phase 3: finalize:  47%|████▋     | 331/709 [00:06<00:07, 52.14it/s][A
→ 500 Phase 3: finalize:  48%|████▊     | 337/709 [00:06<00:07, 51.93it/s][A
→ 500 Phase 3: finalize:  48%|████▊     | 343/709 [00:06<00:07, 51.83it/s][A
→ 500 Phase 3: finalize:  49%|████▉     | 349/709 [00:06<00:06, 51.74it/s][A
→ 500 Phase 3: finalize:  50%|█████     | 355/709 [00:06<00:06, 51.86it/s][A
→ 500 Phase 3: finalize:  51%|█████     | 361/709 [00:06<00:06, 51.89it/s][A
→ 500 Phase 3: finalize:  52%|█████▏    | 367/709 [00:06<00:06, 51.97it/s][A
→ 500 Phase 3: finalize:  53%|█████▎    | 373/709 [00:06<00:06, 51.99it/s][A
→ 500 Phase 3: finalize:  53%|█████▎    | 379/709 [00:07<00:06, 51.98it/s][A
→ 500 Phase 3: finalize:  54%|█████▍    | 385/709 [00:07<00:06, 51.91it/s][A
→ 500 Phase 3: finalize:  55%|█████▌    | 391/709 [00:07<00:06, 51.90it/s][A
→ 500 Phase 3: finalize:  56%|█████▌    | 397/709 [00:07<00:06, 51.86it/s][A
→ 500 Phase 3: finalize:  57%|█████▋    | 403/709 [00:07<00:05, 51.87it/s][A
→ 500 Phase 3: finalize:  58%|█████▊    | 409/709 [00:07<00:05, 51.84it/s][A
→ 500 Phase 3: finalize:  59%|█████▊    | 415/709 [00:07<00:05, 51.83it/s][A
→ 500 Phase 3: finalize:  59%|█████▉    | 421/709 [00:07<00:05, 51.88it/s][A
→ 500 Phase 3: finalize:  60%|██████    | 427/709 [00:08<00:05, 52.01it/s][A
→ 500 Phase 3: finalize:  61%|██████    | 433/709 [00:08<00:05, 52.25it/s][A
→ 500 Phase 3: finalize:  62%|██████▏   | 439/709 [00:08<00:05, 52.63it/s][A
→ 500 Phase 3: finalize:  63%|██████▎   | 445/709 [00:08<00:05, 52.66it/s][A
→ 500 Phase 3: finalize:  64%|██████▎   | 451/709 [00:08<00:04, 52.74it/s][A
→ 500 Phase 3: finalize:  64%|██████▍   | 457/709 [00:08<00:04, 52.68it/s][A
→ 500 Phase 3: finalize:  65%|██████▌   | 463/709 [00:08<00:04, 52.66it/s][A
→ 500 Phase 3: finalize:  66%|██████▌   | 469/709 [00:08<00:04, 52.61it/s][A
→ 500 Phase 3: finalize:  67%|██████▋   | 475/709 [00:08<00:04, 52.69it/s][A
→ 500 Phase 3: finalize:  68%|██████▊   | 481/709 [00:09<00:04, 52.72it/s][A
→ 500 Phase 3: finalize:  69%|██████▊   | 487/709 [00:09<00:04, 52.71it/s][A
→ 500 Phase 3: finalize:  70%|██████▉   | 493/709 [00:09<00:04, 52.70it/s][A
→ 500 Phase 3: finalize:  70%|███████   | 499/709 [00:09<00:03, 52.57it/s][A
→ 500 Phase 3: finalize:  71%|███████   | 505/709 [00:09<00:03, 52.51it/s][A
→ 500 Phase 3: finalize:  72%|███████▏  | 511/709 [00:09<00:03, 52.62it/s][A
→ 500 Phase 3: finalize:  73%|███████▎  | 517/709 [00:09<00:03, 52.48it/s][A
→ 500 Phase 3: finalize:  74%|███████▍  | 523/709 [00:09<00:03, 52.40it/s][A
→ 500 Phase 3: finalize:  75%|███████▍  | 529/709 [00:09<00:03, 52.47it/s][A
→ 500 Phase 3: finalize:  75%|███████▌  | 535/709 [00:10<00:03, 52.52it/s][A
→ 500 Phase 3: finalize:  76%|███████▋  | 541/709 [00:10<00:03, 52.56it/s][A
→ 500 Phase 3: finalize:  77%|███████▋  | 547/709 [00:10<00:03, 52.62it/s][A
→ 500 Phase 3: finalize:  78%|███████▊  | 553/709 [00:10<00:02, 52.61it/s][A
→ 500 Phase 3: finalize:  79%|███████▉  | 559/709 [00:10<00:02, 52.52it/s][A
→ 500 Phase 3: finalize:  80%|███████▉  | 565/709 [00:10<00:02, 52.52it/s][A
→ 500 Phase 3: finalize:  81%|████████  | 571/709 [00:10<00:02, 52.43it/s][A
→ 500 Phase 3: finalize:  81%|████████▏ | 577/709 [00:10<00:02, 52.24it/s][A
→ 500 Phase 3: finalize:  82%|████████▏ | 583/709 [00:11<00:02, 52.02it/s][A
→ 500 Phase 3: finalize:  83%|████████▎ | 589/709 [00:11<00:02, 51.95it/s][A
→ 500 Phase 3: finalize:  84%|████████▍ | 595/709 [00:11<00:02, 52.09it/s][A
→ 500 Phase 3: finalize:  85%|████████▍ | 601/709 [00:11<00:02, 52.13it/s][A
→ 500 Phase 3: finalize:  86%|████████▌ | 607/709 [00:11<00:01, 52.13it/s][A
→ 500 Phase 3: finalize:  86%|████████▋ | 613/709 [00:11<00:01, 52.17it/s][A
→ 500 Phase 3: finalize:  87%|████████▋ | 619/709 [00:11<00:01, 52.21it/s][A
→ 500 Phase 3: finalize:  88%|████████▊ | 625/709 [00:11<00:01, 52.16it/s][A
→ 500 Phase 3: finalize:  89%|████████▉ | 631/709 [00:11<00:01, 52.06it/s][A
→ 500 Phase 3: finalize:  90%|████████▉ | 637/709 [00:12<00:01, 51.98it/s][A
→ 500 Phase 3: finalize:  91%|█████████ | 643/709 [00:12<00:01, 51.98it/s][A
→ 500 Phase 3: finalize:  92%|█████████▏| 649/709 [00:12<00:01, 51.80it/s][A
→ 500 Phase 3: finalize:  92%|█████████▏| 655/709 [00:12<00:01, 51.78it/s][A
→ 500 Phase 3: finalize:  93%|█████████▎| 661/709 [00:12<00:00, 51.62it/s][A
→ 500 Phase 3: finalize:  94%|█████████▍| 667/709 [00:12<00:00, 51.43it/s][A
→ 500 Phase 3: finalize:  95%|█████████▍| 673/709 [00:12<00:00, 51.33it/s][A
→ 500 Phase 3: finalize:  96%|█████████▌| 679/709 [00:12<00:00, 51.19it/s][A
→ 500 Phase 3: finalize:  97%|█████████▋| 685/709 [00:12<00:00, 51.10it/s][A
→ 500 Phase 3: finalize:  97%|█████████▋| 691/709 [00:13<00:00, 51.16it/s][A
→ 500 Phase 3: finalize:  98%|█████████▊| 697/709 [00:13<00:00, 51.20it/s][A
→ 500 Phase 3: finalize:  99%|█████████▉| 703/709 [00:13<00:00, 51.20it/s][A
→ 500 Phase 3: finalize: 100%|██████████| 709/709 [00:13<00:00, 51.15it/s][A
                                                                          [A
[TIMING] 500 — 709 frames
  Phase 1  radial detect   (parallel)  :  10.40s  (14.7 ms/frame)
  Phase 2a corner detect   (parallel)  :   5.21s  (7.4 ms/frame)
  Phase 2b corner fix      (sequential):   0.81s
  Phase 3  finalize        (sequential):  13.45s  (19.0 ms/frame)
    decode + undistort                 :   6.93s  (9.8 ms/frame)
    corner apply + refinement          :   2.65s  (3.7 ms/frame)
    segment                            :   2.88s  (4.1 ms/frame)
    smooth                             :   0.76s  (1.1 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  29.87s

Processing Rigs: 100%|██████████| 2/2 [01:02<00:00, 31.70s/it]Processing Rigs: 100%|██████████| 2/2 [01:02<00:00, 31.33s/it]
[💾] Saved RigFrameDataset to /working/MDC021_W042_2026-09-09/calibration/debug/1_digitized_full/rig_frames_full.json
[✅] Saved full dataset: 1283 frames from 2 rigs to /working/MDC021_W042_2026-09-09/calibration/debug/1_digitized_full/rig_frames_full.json
[💾] Saved RigFrameDataset to /working/MDC021_W042_2026-09-09/calibration/debug/1_digitized_full/rig_frames_full.json
[📋] Creating calibration subset (100 frames/rig) with visualizations...
[📋] 1000: 100 frames selected from 574
[📋] 500: 100 frames selected from 709
[💾] Saved RigFrameDataset to /working/MDC021_W042_2026-09-09/calibration/debug/1_digitized/rig_frames.json
[INFO] Reloading dataset from disk to ensure clean state for multiprocessing...
[📂] Loaded RigFrameDataset from /working/MDC021_W042_2026-09-09/calibration/debug/1_digitized/rig_frames.json

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

-> Calculating the casing center ...
[INFO] Using 40 total sampled bright frames
Computing max image from bright frames:   0%|          | 0/40 [00:00<?, ?it/s]Computing max image from bright frames:   2%|▎         | 1/40 [00:04<03:07,  4.80s/it]Computing max image from bright frames:   5%|▌         | 2/40 [00:04<01:17,  2.04s/it]Computing max image from bright frames:   8%|▊         | 3/40 [00:05<00:43,  1.17s/it]Computing max image from bright frames:  10%|█         | 4/40 [00:05<00:27,  1.31it/s]Computing max image from bright frames:  12%|█▎        | 5/40 [00:05<00:19,  1.84it/s]Computing max image from bright frames:  15%|█▌        | 6/40 [00:05<00:13,  2.50it/s]Computing max image from bright frames:  18%|█▊        | 7/40 [00:05<00:10,  3.26it/s]Computing max image from bright frames:  22%|██▎       | 9/40 [00:05<00:05,  5.24it/s]Computing max image from bright frames:  28%|██▊       | 11/40 [00:05<00:04,  6.01it/s]Computing max image from bright frames:  30%|███       | 12/40 [00:06<00:05,  4.78it/s]Computing max image from bright frames:  32%|███▎      | 13/40 [00:06<00:07,  3.71it/s]Computing max image from bright frames:  38%|███▊      | 15/40 [00:06<00:04,  5.42it/s]Computing max image from bright frames:  42%|████▎     | 17/40 [00:07<00:03,  7.06it/s]Computing max image from bright frames:  48%|████▊     | 19/40 [00:07<00:02,  8.71it/s]Computing max image from bright frames:  55%|█████▌    | 22/40 [00:07<00:01, 11.70it/s]Computing max image from bright frames:  62%|██████▎   | 25/40 [00:07<00:01, 14.53it/s]Computing max image from bright frames:  70%|███████   | 28/40 [00:07<00:00, 17.15it/s]Computing max image from bright frames:  78%|███████▊  | 31/40 [00:07<00:00, 11.63it/s]Computing max image from bright frames:  82%|████████▎ | 33/40 [00:09<00:01,  4.33it/s]Computing max image from bright frames:  90%|█████████ | 36/40 [00:09<00:00,  6.05it/s]Computing max image from bright frames:  98%|█████████▊| 39/40 [00:09<00:00,  7.84it/s]                                                                                       [✅] Casing detection complete: cx=1029.0, cy=757.0

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

  0%|          | 0/100 [00:00<?, ?it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   0%|          | 0/100 [00:00<?, ?it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   1%|          | 1/100 [00:00<00:09,  9.91it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   1%|          | 1/100 [00:00<00:09,  9.91it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   2%|▏         | 2/100 [00:00<00:09,  9.91it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   3%|▎         | 3/100 [00:00<00:09,  9.91it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   4%|▍         | 4/100 [00:00<00:09,  9.91it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   5%|▌         | 5/100 [00:00<00:09,  9.91it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   6%|▌         | 6/100 [00:00<00:09,  9.91it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   7%|▋         | 7/100 [00:00<00:09,  9.91it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   8%|▊         | 8/100 [00:00<00:09,  9.91it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   9%|▉         | 9/100 [00:00<00:09,  9.91it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  10%|█         | 10/100 [00:00<00:09,  9.91it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  11%|█         | 11/100 [00:00<00:01, 58.84it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  11%|█         | 11/100 [00:00<00:01, 58.84it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  12%|█▏        | 12/100 [00:00<00:01, 58.84it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  13%|█▎        | 13/100 [00:00<00:01, 58.84it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  14%|█▍        | 14/100 [00:00<00:01, 58.84it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  15%|█▌        | 15/100 [00:00<00:01, 58.84it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  16%|█▌        | 16/100 [00:00<00:01, 58.84it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  17%|█▋        | 17/100 [00:00<00:01, 58.84it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  18%|█▊        | 18/100 [00:00<00:01, 58.84it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  19%|█▉        | 19/100 [00:00<00:01, 58.84it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  20%|██        | 20/100 [00:00<00:01, 58.84it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  21%|██        | 21/100 [00:00<00:01, 58.84it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  22%|██▏       | 22/100 [00:00<00:01, 58.84it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  23%|██▎       | 23/100 [00:00<00:01, 58.84it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  24%|██▍       | 24/100 [00:00<00:00, 79.88it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  24%|██▍       | 24/100 [00:00<00:00, 79.88it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 476.768} (0.000):  25%|██▌       | 25/100 [00:00<00:00, 79.88it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.000 | Best: {'fx': 483.838} (0.000):  26%|██▌       | 26/100 [00:00<00:00, 79.88it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.001 | Best: {'fx': 490.909} (0.001):  27%|██▋       | 27/100 [00:00<00:00, 79.88it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.004 | Best: {'fx': 497.98} (0.004):  28%|██▊       | 28/100 [00:00<00:00, 79.88it/s] Brute | Start: {'fx': 500.0} (0.006) | Current: 0.008 | Best: {'fx': 505.051} (0.008):  29%|██▉       | 29/100 [00:00<00:00, 79.88it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.022 | Best: {'fx': 512.121} (0.022):  30%|███       | 30/100 [00:00<00:00, 79.88it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.038 | Best: {'fx': 519.192} (0.038):  31%|███       | 31/100 [00:00<00:00, 79.88it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.065 | Best: {'fx': 526.263} (0.065):  32%|███▏      | 32/100 [00:00<00:00, 79.88it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.075 | Best: {'fx': 533.333} (0.075):  33%|███▎      | 33/100 [00:00<00:00, 79.88it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.021 | Best: {'fx': 533.333} (0.075):  34%|███▍      | 34/100 [00:00<00:00, 79.88it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.044 | Best: {'fx': 533.333} (0.075):  35%|███▌      | 35/100 [00:00<00:00, 79.88it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.019 | Best: {'fx': 533.333} (0.075):  36%|███▌      | 36/100 [00:00<00:00, 79.88it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.030 | Best: {'fx': 533.333} (0.075):  37%|███▋      | 37/100 [00:00<00:00, 79.88it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.025 | Best: {'fx': 533.333} (0.075):  38%|███▊      | 38/100 [00:00<00:00, 79.88it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.025 | Best: {'fx': 533.333} (0.075):  39%|███▉      | 39/100 [00:00<00:00, 104.50it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.016 | Best: {'fx': 533.333} (0.075):  39%|███▉      | 39/100 [00:00<00:00, 104.50it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.017 | Best: {'fx': 533.333} (0.075):  40%|████      | 40/100 [00:00<00:00, 104.50it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.014 | Best: {'fx': 533.333} (0.075):  41%|████      | 41/100 [00:00<00:00, 104.50it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.014 | Best: {'fx': 533.333} (0.075):  42%|████▏     | 42/100 [00:00<00:00, 104.50it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.012 | Best: {'fx': 533.333} (0.075):  43%|████▎     | 43/100 [00:00<00:00, 104.50it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.013 | Best: {'fx': 533.333} (0.075):  44%|████▍     | 44/100 [00:00<00:00, 104.50it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.013 | Best: {'fx': 533.333} (0.075):  45%|████▌     | 45/100 [00:00<00:00, 104.50it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.011 | Best: {'fx': 533.333} (0.075):  46%|████▌     | 46/100 [00:00<00:00, 104.50it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.012 | Best: {'fx': 533.333} (0.075):  47%|████▋     | 47/100 [00:00<00:00, 104.50it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.012 | Best: {'fx': 533.333} (0.075):  48%|████▊     | 48/100 [00:00<00:00, 104.50it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.011 | Best: {'fx': 533.333} (0.075):  49%|████▉     | 49/100 [00:00<00:00, 104.50it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.011 | Best: {'fx': 533.333} (0.075):  50%|█████     | 50/100 [00:00<00:00, 104.50it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.011 | Best: {'fx': 533.333} (0.075):  51%|█████     | 51/100 [00:00<00:00, 104.50it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.010 | Best: {'fx': 533.333} (0.075):  52%|█████▏    | 52/100 [00:00<00:00, 104.50it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.011 | Best: {'fx': 533.333} (0.075):  53%|█████▎    | 53/100 [00:00<00:00, 104.50it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.011 | Best: {'fx': 533.333} (0.075):  54%|█████▍    | 54/100 [00:00<00:00, 116.96it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.010 | Best: {'fx': 533.333} (0.075):  54%|█████▍    | 54/100 [00:00<00:00, 116.96it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.010 | Best: {'fx': 533.333} (0.075):  55%|█████▌    | 55/100 [00:00<00:00, 116.96it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.010 | Best: {'fx': 533.333} (0.075):  56%|█████▌    | 56/100 [00:00<00:00, 116.96it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.010 | Best: {'fx': 533.333} (0.075):  57%|█████▋    | 57/100 [00:00<00:00, 116.96it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.010 | Best: {'fx': 533.333} (0.075):  58%|█████▊    | 58/100 [00:00<00:00, 116.96it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.010 | Best: {'fx': 533.333} (0.075):  59%|█████▉    | 59/100 [00:00<00:00, 116.96it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.010 | Best: {'fx': 533.333} (0.075):  60%|██████    | 60/100 [00:00<00:00, 116.96it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  61%|██████    | 61/100 [00:00<00:00, 116.96it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  62%|██████▏   | 62/100 [00:00<00:00, 116.96it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.010 | Best: {'fx': 533.333} (0.075):  63%|██████▎   | 63/100 [00:00<00:00, 116.96it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  64%|██████▍   | 64/100 [00:00<00:00, 116.96it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  65%|██████▌   | 65/100 [00:00<00:00, 116.96it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  66%|██████▌   | 66/100 [00:00<00:00, 116.96it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  67%|██████▋   | 67/100 [00:00<00:00, 116.96it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  68%|██████▊   | 68/100 [00:00<00:00, 118.57it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  68%|██████▊   | 68/100 [00:00<00:00, 118.57it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  69%|██████▉   | 69/100 [00:00<00:00, 118.57it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  70%|███████   | 70/100 [00:00<00:00, 118.57it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  71%|███████   | 71/100 [00:00<00:00, 118.57it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  72%|███████▏  | 72/100 [00:00<00:00, 118.57it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  73%|███████▎  | 73/100 [00:00<00:00, 118.57it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  74%|███████▍  | 74/100 [00:00<00:00, 118.57it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  75%|███████▌  | 75/100 [00:00<00:00, 118.57it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  76%|███████▌  | 76/100 [00:00<00:00, 118.57it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  77%|███████▋  | 77/100 [00:00<00:00, 118.57it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  78%|███████▊  | 78/100 [00:00<00:00, 118.57it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  79%|███████▉  | 79/100 [00:00<00:00, 118.57it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  80%|████████  | 80/100 [00:00<00:00, 118.57it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  81%|████████  | 81/100 [00:00<00:00, 118.57it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  82%|████████▏ | 82/100 [00:00<00:00, 118.57it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  83%|████████▎ | 83/100 [00:00<00:00, 128.04it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  83%|████████▎ | 83/100 [00:00<00:00, 128.04it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  84%|████████▍ | 84/100 [00:00<00:00, 128.04it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  85%|████████▌ | 85/100 [00:00<00:00, 128.04it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  86%|████████▌ | 86/100 [00:00<00:00, 128.04it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  87%|████████▋ | 87/100 [00:00<00:00, 128.04it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  88%|████████▊ | 88/100 [00:00<00:00, 128.04it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  89%|████████▉ | 89/100 [00:00<00:00, 128.04it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  90%|█████████ | 90/100 [00:00<00:00, 128.04it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  91%|█████████ | 91/100 [00:00<00:00, 128.04it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  92%|█████████▏| 92/100 [00:00<00:00, 128.04it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  93%|█████████▎| 93/100 [00:00<00:00, 128.04it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  94%|█████████▍| 94/100 [00:00<00:00, 128.04it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  95%|█████████▌| 95/100 [00:00<00:00, 128.04it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  96%|█████████▌| 96/100 [00:00<00:00, 128.04it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  97%|█████████▋| 97/100 [00:00<00:00, 130.88it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  97%|█████████▋| 97/100 [00:00<00:00, 130.88it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  98%|█████████▊| 98/100 [00:00<00:00, 130.88it/s]Brute | Start: {'fx': 500.0} (0.006) | Current: 0.009 | Best: {'fx': 533.333} (0.075):  99%|█████████▉| 99/100 [00:00<00:00, 130.88it/s]                                                                                                                                          0%|          | 0/50 [00:00<?, ?it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.013 | Best: {'fx': 509.354} (0.013):   0%|          | 0/50 [00:00<?, ?it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.013 | Best: {'fx': 509.354} (0.013):   2%|▏         | 1/50 [00:00<00:05,  8.38it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.012 | Best: {'fx': 509.354} (0.013):   2%|▏         | 1/50 [00:00<00:05,  8.38it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.017 | Best: {'fx': 510.374} (0.017):   4%|▍         | 2/50 [00:00<00:05,  8.38it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.019 | Best: {'fx': 511.395} (0.019):   6%|▌         | 3/50 [00:00<00:05,  8.38it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.030 | Best: {'fx': 515.476} (0.030):   8%|▊         | 4/50 [00:00<00:05,  8.38it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.022 | Best: {'fx': 515.476} (0.030):  10%|█         | 5/50 [00:00<00:05,  8.38it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.030 | Best: {'fx': 515.476} (0.030):  12%|█▏        | 6/50 [00:00<00:05,  8.38it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.031 | Best: {'fx': 516.497} (0.031):  14%|█▍        | 7/50 [00:00<00:05,  8.38it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.034 | Best: {'fx': 517.517} (0.034):  16%|█▌        | 8/50 [00:00<00:05,  8.38it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.028 | Best: {'fx': 517.517} (0.034):  18%|█▊        | 9/50 [00:00<00:04,  8.38it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.035 | Best: {'fx': 518.537} (0.035):  20%|██        | 10/50 [00:00<00:04,  8.38it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.037 | Best: {'fx': 519.558} (0.037):  22%|██▏       | 11/50 [00:00<00:04,  8.38it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.037 | Best: {'fx': 519.558} (0.037):  24%|██▍       | 12/50 [00:00<00:00, 63.45it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.039 | Best: {'fx': 520.578} (0.039):  24%|██▍       | 12/50 [00:00<00:00, 63.45it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.045 | Best: {'fx': 522.619} (0.045):  26%|██▌       | 13/50 [00:00<00:00, 63.45it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.042 | Best: {'fx': 522.619} (0.045):  28%|██▊       | 14/50 [00:00<00:00, 63.45it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.050 | Best: {'fx': 523.639} (0.050):  30%|███       | 15/50 [00:00<00:00, 63.45it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.069 | Best: {'fx': 526.701} (0.069):  32%|███▏      | 16/50 [00:00<00:00, 63.45it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.072 | Best: {'fx': 527.721} (0.072):  34%|███▍      | 17/50 [00:00<00:00, 63.45it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.056 | Best: {'fx': 527.721} (0.072):  36%|███▌      | 18/50 [00:00<00:00, 63.45it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.060 | Best: {'fx': 527.721} (0.072):  38%|███▊      | 19/50 [00:00<00:00, 63.45it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.082 | Best: {'fx': 529.762} (0.082):  40%|████      | 20/50 [00:00<00:00, 63.45it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.082 | Best: {'fx': 529.762} (0.082):  42%|████▏     | 21/50 [00:00<00:00, 74.13it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.077 | Best: {'fx': 529.762} (0.082):  42%|████▏     | 21/50 [00:00<00:00, 74.13it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.081 | Best: {'fx': 529.762} (0.082):  44%|████▍     | 22/50 [00:00<00:00, 74.13it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.084 | Best: {'fx': 530.782} (0.084):  46%|████▌     | 23/50 [00:00<00:00, 74.13it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.077 | Best: {'fx': 530.782} (0.084):  48%|████▊     | 24/50 [00:00<00:00, 74.13it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.059 | Best: {'fx': 530.782} (0.084):  50%|█████     | 25/50 [00:00<00:00, 74.13it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.063 | Best: {'fx': 530.782} (0.084):  52%|█████▏    | 26/50 [00:00<00:00, 74.13it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.072 | Best: {'fx': 530.782} (0.084):  54%|█████▍    | 27/50 [00:00<00:00, 74.13it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.051 | Best: {'fx': 530.782} (0.084):  56%|█████▌    | 28/50 [00:00<00:00, 74.13it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.054 | Best: {'fx': 530.782} (0.084):  58%|█████▊    | 29/50 [00:00<00:00, 74.13it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.041 | Best: {'fx': 530.782} (0.084):  60%|██████    | 30/50 [00:00<00:00, 74.13it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.041 | Best: {'fx': 530.782} (0.084):  62%|██████▏   | 31/50 [00:00<00:00, 83.53it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.047 | Best: {'fx': 530.782} (0.084):  62%|██████▏   | 31/50 [00:00<00:00, 83.53it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.044 | Best: {'fx': 530.782} (0.084):  64%|██████▍   | 32/50 [00:00<00:00, 83.53it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.039 | Best: {'fx': 530.782} (0.084):  66%|██████▌   | 33/50 [00:00<00:00, 83.53it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.034 | Best: {'fx': 530.782} (0.084):  68%|██████▊   | 34/50 [00:00<00:00, 83.53it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.036 | Best: {'fx': 530.782} (0.084):  70%|███████   | 35/50 [00:00<00:00, 83.53it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.036 | Best: {'fx': 530.782} (0.084):  72%|███████▏  | 36/50 [00:00<00:00, 83.53it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.032 | Best: {'fx': 530.782} (0.084):  74%|███████▍  | 37/50 [00:00<00:00, 83.53it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.029 | Best: {'fx': 530.782} (0.084):  76%|███████▌  | 38/50 [00:00<00:00, 83.53it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.031 | Best: {'fx': 530.782} (0.084):  78%|███████▊  | 39/50 [00:00<00:00, 83.53it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.030 | Best: {'fx': 530.782} (0.084):  80%|████████  | 40/50 [00:00<00:00, 83.53it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.027 | Best: {'fx': 530.782} (0.084):  82%|████████▏ | 41/50 [00:00<00:00, 83.53it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.026 | Best: {'fx': 530.782} (0.084):  84%|████████▍ | 42/50 [00:00<00:00, 83.53it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.028 | Best: {'fx': 530.782} (0.084):  86%|████████▌ | 43/50 [00:00<00:00, 83.53it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.026 | Best: {'fx': 530.782} (0.084):  88%|████████▊ | 44/50 [00:00<00:00, 83.53it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.023 | Best: {'fx': 530.782} (0.084):  90%|█████████ | 45/50 [00:00<00:00, 83.53it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.023 | Best: {'fx': 530.782} (0.084):  92%|█████████▏| 46/50 [00:00<00:00, 106.83it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.023 | Best: {'fx': 530.782} (0.084):  92%|█████████▏| 46/50 [00:00<00:00, 106.83it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.025 | Best: {'fx': 530.782} (0.084):  94%|█████████▍| 47/50 [00:00<00:00, 106.83it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.025 | Best: {'fx': 530.782} (0.084):  96%|█████████▌| 48/50 [00:00<00:00, 106.83it/s]Brute | Start: {'fx': 533.333} (0.075) | Current: 0.024 | Best: {'fx': 530.782} (0.084):  98%|█████████▊| 49/50 [00:00<00:00, 106.83it/s]                                                                                                                                         
[DEBUG] Parameters after Step 5 (before square optimization):
    fx: 530.7823129251701
    px: 1029.0
    py: 757.0
    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): 20 frames will be used for optimization
  Rigs: 1000(1000mm):20/20
  Total: 20/20 frames used for optimization
Initial score: 6.9579: 0iter [00:00, ?iter/s][DEBUG] objective(x0) = 6.9579, picklable_objective(x0) = 6.9597
Best score: 6.9597: : 0iter [00:01, ?iter/s] Best score: 6.9597: : 1iter [00:01,  1.98s/iter]Best score: 6.9597: : 1iter [00:02,  1.98s/iter]Best score: 6.9597: : 2iter [00:02,  1.98s/iter]Best score: 6.9597: : 3iter [00:02,  1.98s/iter]Best score: 6.9597: : 4iter [00:02,  1.98s/iter]Best score: 6.9597: : 5iter [00:02,  3.16iter/s]Best score: 6.9597: : 5iter [00:02,  3.16iter/s]Best score: 6.9597: : 6iter [00:02,  3.16iter/s]Best score: 6.9597: : 7iter [00:02,  3.16iter/s]Best score: 6.9597: : 8iter [00:02,  3.16iter/s]Best score: 6.9597: : 9iter [00:02,  6.38iter/s]Best score: 6.9597: : 9iter [00:02,  6.38iter/s]Best score: 6.9597: : 10iter [00:02,  6.38iter/s]Best score: 6.9597: : 11iter [00:02,  6.38iter/s]Best score: 6.9597: : 12iter [00:02,  6.38iter/s]Best score: 6.9597: : 13iter [00:02, 10.08iter/s]Best score: 6.9597: : 13iter [00:02, 10.08iter/s]Best score: 6.9597: : 14iter [00:02, 10.08iter/s]Best score: 6.9597: : 15iter [00:02, 10.08iter/s]Best score: 6.9597: : 16iter [00:02, 10.08iter/s]Best score: 6.9597: : 17iter [00:02, 14.15iter/s]Best score: 6.9597: : 17iter [00:02, 14.15iter/s]Best score: 6.9597: : 18iter [00:02, 14.15iter/s]Best score: 6.9597: : 19iter [00:02, 14.15iter/s]Best score: 6.9597: : 20iter [00:02, 14.15iter/s]Best score: 6.9597: : 21iter [00:02, 18.31iter/s]Best score: 6.9597: : 21iter [00:02, 18.31iter/s]Best score: 6.9597: : 22iter [00:02, 18.31iter/s]Best score: 6.9597: : 23iter [00:02, 18.31iter/s]Best score: 6.9597: : 24iter [00:02, 18.31iter/s]Best score: 6.9597: : 25iter [00:02, 22.37iter/s]Best score: 6.9597: : 25iter [00:02, 22.37iter/s]Best score: 6.9597: : 26iter [00:02, 22.37iter/s]Best score: 6.9597: : 27iter [00:02, 22.37iter/s]Best score: 6.9597: : 28iter [00:02, 22.37iter/s]Best score: 6.9597: : 29iter [00:02, 26.09iter/s]Best score: 6.9597: : 29iter [00:02, 26.09iter/s]Best score: 6.9597: : 30iter [00:02, 26.09iter/s]Best score: 6.9597: : 31iter [00:02, 26.09iter/s]Best score: 6.9597: : 32iter [00:02, 26.09iter/s]Best score: 6.9597: : 33iter [00:02, 29.12iter/s]Best score: 6.9597: : 33iter [00:02, 29.12iter/s]Best score: 6.9597: : 34iter [00:02, 29.12iter/s]Best score: 6.9597: : 35iter [00:02, 29.12iter/s]Best score: 6.9597: : 36iter [00:02, 29.12iter/s]Best score: 6.9597: : 37iter [00:02, 31.80iter/s]Best score: 6.9597: : 37iter [00:02, 31.80iter/s]Best score: 6.9597: : 38iter [00:02, 31.80iter/s]Best score: 6.9597: : 39iter [00:02, 31.80iter/s]Best score: 6.9597: : 40iter [00:02, 31.80iter/s]Best score: 6.9597: : 41iter [00:02, 33.74iter/s]Best score: 6.9597: : 41iter [00:03, 33.74iter/s]Best score: 6.9597: : 42iter [00:03, 33.74iter/s]Best score: 6.9597: : 43iter [00:03, 33.74iter/s]Best score: 6.9597: : 44iter [00:03, 33.74iter/s]Best score: 6.9597: : 45iter [00:03, 35.35iter/s]Best score: 6.9597: : 45iter [00:03, 35.35iter/s]Best score: 6.9597: : 46iter [00:03, 35.35iter/s]Best score: 6.9597: : 47iter [00:03, 35.35iter/s]Best score: 6.9597: : 48iter [00:03, 35.35iter/s]Best score: 6.9597: : 49iter [00:03, 36.57iter/s]
[ITER 50] Best: 6.9597
[PARAMS] Current best parameters:
  fx: 530.7823
  fy: 530.7823
  px: 1029.0000
  py: 757.0000
  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: 6.9597: : 49iter [00:03, 36.57iter/s]Best score: 6.9597: : 50iter [00:03, 36.57iter/s]Best score: 6.9597: : 51iter [00:03, 36.57iter/s]Best score: 6.9597: : 52iter [00:03, 36.57iter/s]Best score: 6.9597: : 53iter [00:03, 37.40iter/s]Best score: 6.9597: : 53iter [00:03, 37.40iter/s]Best score: 6.9597: : 54iter [00:03, 37.40iter/s]Best score: 6.9597: : 55iter [00:03, 37.40iter/s]Best score: 6.9597: : 56iter [00:03, 37.40iter/s]Best score: 6.9597: : 57iter [00:03, 38.00iter/s]Best score: 6.9597: : 57iter [00:03, 38.00iter/s]Best score: 6.9597: : 58iter [00:03, 38.00iter/s]Best score: 6.9597: : 59iter [00:03, 38.00iter/s]Best score: 6.9597: : 60iter [00:03, 38.00iter/s]Best score: 6.9597: : 61iter [00:03, 38.26iter/s]Best score: 6.9597: : 61iter [00:03, 38.26iter/s]Best score: 6.9597: : 62iter [00:03, 38.26iter/s]Best score: 6.9597: : 63iter [00:03, 38.26iter/s]Best score: 6.9597: : 64iter [00:03, 38.26iter/s]Best score: 6.9597: : 65iter [00:03, 38.71iter/s]Best score: 6.9597: : 65iter [00:03, 38.71iter/s]Best score: 6.9597: : 66iter [00:03, 38.71iter/s]Best score: 6.9597: : 67iter [00:03, 38.71iter/s]Best score: 6.9597: : 68iter [00:03, 38.71iter/s]Best score: 6.9597: : 69iter [00:03, 38.92iter/s]Best score: 6.9597: : 69iter [00:03, 38.92iter/s]Best score: 6.9597: : 70iter [00:03, 38.92iter/s]Best score: 6.9597: : 71iter [00:03, 38.92iter/s]Best score: 6.9597: : 72iter [00:03, 38.92iter/s]Best score: 6.9597: : 73iter [00:03, 38.89iter/s]Best score: 6.9597: : 73iter [00:03, 38.89iter/s]Best score: 6.9597: : 74iter [00:03, 38.89iter/s]Best score: 6.9597: : 75iter [00:03, 38.89iter/s]Best score: 6.9597: : 76iter [00:03, 38.89iter/s]Best score: 6.9597: : 77iter [00:03, 38.97iter/s]Best score: 6.9597: : 77iter [00:03, 38.97iter/s]Best score: 6.9597: : 78iter [00:03, 38.97iter/s]Best score: 6.9597: : 79iter [00:03, 38.97iter/s]Best score: 6.9597: : 80iter [00:04, 38.97iter/s]Best score: 6.9597: : 81iter [00:04, 38.82iter/s]Best score: 6.9597: : 81iter [00:04, 38.82iter/s]Best score: 6.9597: : 82iter [00:04, 38.82iter/s]Best score: 6.9597: : 83iter [00:04, 38.82iter/s]Best score: 6.9597: : 84iter [00:04, 38.82iter/s]Best score: 6.9597: : 85iter [00:04, 38.54iter/s]Best score: 6.9597: : 85iter [00:04, 38.54iter/s]Best score: 6.9597: : 86iter [00:04, 38.54iter/s]Best score: 6.9597: : 87iter [00:04, 38.54iter/s]Best score: 6.9597: : 88iter [00:04, 38.54iter/s]Best score: 6.9597: : 89iter [00:04, 38.83iter/s]Best score: 6.9597: : 89iter [00:04, 38.83iter/s]Best score: 6.9597: : 90iter [00:04, 38.83iter/s]Best score: 6.9597: : 91iter [00:04, 38.83iter/s]Best score: 6.9597: : 92iter [00:04, 38.83iter/s]Best score: 6.9597: : 93iter [00:04, 38.80iter/s]Best score: 6.9597: : 93iter [00:04, 38.80iter/s]Best score: 6.9597: : 94iter [00:04, 38.80iter/s]Best score: 6.9597: : 95iter [00:04, 38.80iter/s]Best score: 6.9597: : 96iter [00:04, 38.80iter/s]Best score: 6.9597: : 97iter [00:04, 39.11iter/s]Best score: 6.9597: : 97iter [00:04, 39.11iter/s]Best score: 6.9597: : 98iter [00:04, 39.11iter/s]
[ITER 100] Best: 6.9597
[PARAMS] Current best parameters:
  fx: 530.7823
  fy: 530.7823
  px: 1029.0000
  py: 757.0000
  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: 6.9597: : 99iter [00:04, 39.11iter/s]Best score: 6.9597: : 100iter [00:04, 39.11iter/s]Best score: 6.9597: : 101iter [00:04, 36.00iter/s]Best score: 6.9597: : 101iter [00:04, 36.00iter/s]Best score: 6.9597: : 102iter [00:04, 36.00iter/s]Best score: 6.9597: : 103iter [00:04, 36.00iter/s]Best score: 6.9597: : 104iter [00:04, 36.00iter/s]Best score: 6.9597: : 105iter [00:04, 37.04iter/s]Best score: 6.9597: : 105iter [00:04, 37.04iter/s]Best score: 6.9597: : 106iter [00:04, 37.04iter/s]Best score: 6.9597: : 107iter [00:04, 37.04iter/s]Best score: 6.9597: : 108iter [00:04, 37.04iter/s]Best score: 6.9597: : 109iter [00:04, 37.77iter/s]Best score: 6.9597: : 109iter [00:04, 37.77iter/s]Best score: 6.9597: : 110iter [00:04, 37.77iter/s]Best score: 6.9597: : 111iter [00:04, 37.77iter/s]Best score: 6.9597: : 112iter [00:04, 37.77iter/s]Best score: 6.9597: : 113iter [00:04, 38.10iter/s]Best score: 6.9597: : 113iter [00:04, 38.10iter/s]Best score: 6.9597: : 114iter [00:04, 38.10iter/s]Best score: 6.9597: : 115iter [00:04, 38.10iter/s]Best score: 6.9597: : 116iter [00:04, 38.10iter/s]Best score: 6.9597: : 117iter [00:04, 38.63iter/s]Best score: 6.9597: : 117iter [00:04, 38.63iter/s]Best score: 6.9597: : 118iter [00:05, 38.63iter/s]Best score: 6.9597: : 119iter [00:05, 38.63iter/s]Best score: 6.9597: : 120iter [00:05, 38.63iter/s]Best score: 6.9597: : 121iter [00:05, 38.69iter/s]Best score: 6.9597: : 121iter [00:05, 38.69iter/s]Best score: 6.9597: : 122iter [00:05, 38.69iter/s]Best score: 6.9597: : 123iter [00:05, 38.69iter/s]Best score: 6.9597: : 124iter [00:05, 38.69iter/s]Best score: 6.9597: : 125iter [00:05, 39.00iter/s]Best score: 6.9597: : 125iter [00:05, 39.00iter/s]Best score: 6.9597: : 126iter [00:05, 39.00iter/s]Best score: 6.9597: : 127iter [00:05, 39.00iter/s]Best score: 6.9597: : 128iter [00:05, 39.00iter/s]Best score: 6.9597: : 129iter [00:05, 39.25iter/s]Best score: 6.9597: : 129iter [00:05, 39.25iter/s]Best score: 6.9597: : 130iter [00:05, 39.25iter/s]Best score: 6.9597: : 131iter [00:05, 39.25iter/s]Best score: 6.9597: : 132iter [00:05, 39.25iter/s]Best score: 6.9597: : 133iter [00:05, 39.18iter/s]Best score: 6.9597: : 133iter [00:05, 39.18iter/s]Best score: 6.9597: : 134iter [00:05, 39.18iter/s]Best score: 6.9597: : 135iter [00:05, 39.18iter/s]Best score: 6.9597: : 136iter [00:05, 39.18iter/s]Best score: 6.9597: : 137iter [00:05, 39.18iter/s]Best score: 6.9597: : 138iter [00:05, 39.52iter/s]Best score: 6.9597: : 138iter [00:05, 39.52iter/s]Best score: 6.9597: : 139iter [00:05, 39.52iter/s]Best score: 6.9597: : 140iter [00:05, 39.52iter/s]Best score: 6.9597: : 141iter [00:05, 39.52iter/s]Best score: 6.9597: : 142iter [00:05, 39.28iter/s]Best score: 6.9597: : 142iter [00:05, 39.28iter/s]Best score: 6.9597: : 143iter [00:05, 39.28iter/s]Best score: 6.9597: : 144iter [00:05, 39.28iter/s]Best score: 6.9597: : 145iter [00:05, 39.28iter/s]Best score: 6.9597: : 146iter [00:05, 39.43iter/s]Best score: 6.9597: : 146iter [00:05, 39.43iter/s]Best score: 6.9597: : 147iter [00:05, 39.43iter/s]Best score: 6.9597: : 148iter [00:05, 39.43iter/s]
[ITER 150] Best: 6.9597
[PARAMS] Current best parameters:
  fx: 530.7823
  fy: 530.7823
  px: 1029.0000
  py: 757.0000
  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: 6.9597: : 149iter [00:05, 39.43iter/s]Best score: 6.9597: : 150iter [00:05, 39.30iter/s]Best score: 6.9597: : 150iter [00:05, 39.30iter/s]Best score: 6.9597: : 151iter [00:05, 39.30iter/s]Best score: 6.9597: : 152iter [00:05, 39.30iter/s]Best score: 6.9597: : 153iter [00:05, 39.30iter/s]Best score: 6.9597: : 154iter [00:05, 32.18iter/s]Best score: 6.9597: : 154iter [00:06, 32.18iter/s]Best score: 6.9597: : 155iter [00:06, 32.18iter/s]Best score: 6.9597: : 156iter [00:06, 32.18iter/s]Best score: 6.9597: : 157iter [00:06, 32.18iter/s]Best score: 6.9597: : 158iter [00:06, 34.06iter/s]Best score: 6.9597: : 158iter [00:06, 34.06iter/s]Best score: 6.9597: : 159iter [00:06, 34.06iter/s]Best score: 6.9597: : 160iter [00:06, 34.06iter/s]Best score: 6.9597: : 161iter [00:06, 34.06iter/s]Best score: 6.9597: : 162iter [00:06, 35.39iter/s]Best score: 6.9597: : 162iter [00:06, 35.39iter/s]Best score: 6.9597: : 163iter [00:06, 35.39iter/s]Best score: 6.9597: : 164iter [00:06, 35.39iter/s]Best score: 6.9597: : 165iter [00:06, 35.39iter/s]Best score: 6.9597: : 166iter [00:06, 36.50iter/s]Best score: 6.9597: : 166iter [00:06, 36.50iter/s]Best score: 6.9597: : 167iter [00:06, 36.50iter/s]Best score: 6.9597: : 168iter [00:06, 36.50iter/s]Best score: 6.9597: : 169iter [00:06, 36.50iter/s]Best score: 6.9597: : 170iter [00:06, 37.20iter/s]Best score: 6.9597: : 170iter [00:06, 37.20iter/s]Best score: 6.9597: : 171iter [00:06, 37.20iter/s]Best score: 6.9597: : 172iter [00:06, 37.20iter/s]Best score: 6.9597: : 173iter [00:06, 37.20iter/s]Best score: 6.9597: : 174iter [00:06, 37.98iter/s]Best score: 6.9597: : 174iter [00:06, 37.98iter/s]Best score: 6.9597: : 175iter [00:06, 37.98iter/s]Best score: 6.9597: : 176iter [00:06, 37.98iter/s]Best score: 6.9597: : 177iter [00:06, 37.98iter/s]Best score: 6.9597: : 178iter [00:06, 38.46iter/s]Best score: 6.9597: : 178iter [00:06, 38.46iter/s]Best score: 6.9597: : 179iter [00:06, 38.46iter/s]Best score: 6.9597: : 180iter [00:06, 38.46iter/s]Best score: 6.9597: : 181iter [00:06, 38.46iter/s]Best score: 6.9597: : 182iter [00:06, 38.50iter/s]Best score: 6.9597: : 182iter [00:06, 38.50iter/s]Best score: 6.9597: : 183iter [00:06, 38.50iter/s]Best score: 6.9597: : 184iter [00:06, 38.50iter/s]Best score: 6.9597: : 185iter [00:06, 38.50iter/s]Best score: 6.9597: : 186iter [00:06, 38.90iter/s]Best score: 6.9597: : 186iter [00:06, 38.90iter/s]Best score: 6.9597: : 187iter [00:06, 38.90iter/s]Best score: 6.9597: : 188iter [00:06, 38.90iter/s]Best score: 6.9597: : 189iter [00:06, 38.90iter/s]Best score: 6.9597: : 190iter [00:06, 38.86iter/s]Best score: 6.9597: : 190iter [00:06, 38.86iter/s]Best score: 6.9597: : 191iter [00:06, 38.86iter/s]Best score: 6.9597: : 192iter [00:06, 38.86iter/s]Best score: 6.9597: : 193iter [00:06, 38.86iter/s]Best score: 6.9597: : 194iter [00:06, 39.04iter/s]Best score: 6.9597: : 194iter [00:07, 39.04iter/s]Best score: 6.9597: : 195iter [00:07, 39.04iter/s]Best score: 6.9597: : 196iter [00:07, 39.04iter/s]Best score: 6.9597: : 197iter [00:07, 39.04iter/s]Best score: 6.9597: : 198iter [00:07, 39.21iter/s]Best score: 6.9597: : 198iter [00:07, 39.21iter/s]
[ITER 200] Best: 6.9597
[PARAMS] Current best parameters:
  fx: 530.7823
  fy: 530.7823
  px: 1029.0000
  py: 757.0000
  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: 6.9597: : 199iter [00:07, 39.21iter/s]Best score: 6.9597: : 200iter [00:07, 39.21iter/s]Best score: 6.9597: : 201iter [00:07, 39.21iter/s]Best score: 6.9597: : 202iter [00:07, 31.86iter/s]Best score: 6.9597: : 202iter [00:07, 31.86iter/s]Best score: 6.9597: : 203iter [00:07, 31.86iter/s]Best score: 6.9597: : 204iter [00:07, 31.86iter/s]Best score: 6.9597: : 205iter [00:07, 31.86iter/s]Best score: 6.9597: : 206iter [00:07, 33.91iter/s]Best score: 6.9597: : 206iter [00:07, 33.91iter/s]Best score: 6.9597: : 207iter [00:07, 33.91iter/s]Best score: 6.9597: : 208iter [00:07, 33.91iter/s]Best score: 6.9597: : 209iter [00:07, 33.91iter/s]Best score: 6.9597: : 210iter [00:07, 35.39iter/s]Best score: 6.9597: : 210iter [00:07, 35.39iter/s]Best score: 6.9597: : 211iter [00:07, 35.39iter/s]Best score: 6.9597: : 212iter [00:07, 35.39iter/s]Best score: 6.9597: : 213iter [00:07, 35.39iter/s]Best score: 6.9597: : 214iter [00:07, 35.39iter/s]Best score: 6.9597: : 215iter [00:07, 37.00iter/s]Best score: 6.9597: : 215iter [00:07, 37.00iter/s]Best score: 6.9597: : 216iter [00:07, 37.00iter/s]Best score: 6.9597: : 217iter [00:07, 37.00iter/s]Best score: 6.9597: : 218iter [00:07, 37.00iter/s]Best score: 6.9597: : 219iter [00:07, 37.81iter/s]Best score: 6.9597: : 219iter [00:07, 37.81iter/s]Best score: 6.9597: : 220iter [00:07, 37.81iter/s]Best score: 6.9597: : 221iter [00:07, 37.81iter/s]Best score: 6.9597: : 222iter [00:07, 37.81iter/s]Best score: 6.9597: : 223iter [00:07, 38.30iter/s]Best score: 6.9597: : 223iter [00:07, 38.30iter/s]Best score: 6.9597: : 224iter [00:07, 38.30iter/s]Best score: 6.9597: : 225iter [00:07, 38.30iter/s]Best score: 6.9597: : 226iter [00:07, 38.30iter/s]Best score: 6.9597: : 227iter [00:07, 38.30iter/s]Best score: 6.9597: : 228iter [00:07, 38.84iter/s]Best score: 6.9597: : 228iter [00:07, 38.84iter/s]Best score: 6.9597: : 229iter [00:07, 38.84iter/s]Best score: 6.9597: : 230iter [00:08, 38.84iter/s]Best score: 6.9597: : 231iter [00:08, 38.84iter/s]Best score: 6.9597: : 232iter [00:08, 38.98iter/s]Best score: 6.9597: : 232iter [00:08, 38.98iter/s]Best score: 6.9597: : 233iter [00:08, 38.98iter/s]Best score: 6.9597: : 234iter [00:08, 38.98iter/s]Best score: 6.9597: : 235iter [00:08, 38.98iter/s]Best score: 6.9597: : 236iter [00:08, 38.98iter/s]Best score: 6.9597: : 237iter [00:08, 39.43iter/s]Best score: 6.9597: : 237iter [00:08, 39.43iter/s]Best score: 6.9597: : 238iter [00:08, 39.43iter/s]Best score: 6.9597: : 239iter [00:08, 39.43iter/s]Best score: 6.9597: : 240iter [00:08, 39.43iter/s]Best score: 6.9597: : 241iter [00:08, 39.42iter/s]Best score: 6.9597: : 241iter [00:08, 39.42iter/s]Best score: 6.9597: : 242iter [00:08, 39.42iter/s]Best score: 6.9597: : 243iter [00:08, 39.42iter/s]Best score: 6.9597: : 244iter [00:08, 39.42iter/s]Best score: 6.9597: : 245iter [00:08, 39.42iter/s]Best score: 6.9597: : 246iter [00:08, 39.70iter/s]Best score: 6.9597: : 246iter [00:08, 39.70iter/s]Best score: 6.9597: : 247iter [00:08, 39.70iter/s]Best score: 6.9597: : 248iter [00:08, 39.70iter/s]
[ITER 250] Best: 6.9597
[PARAMS] Current best parameters:
  fx: 530.7823
  fy: 530.7823
  px: 1029.0000
  py: 757.0000
  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: 6.9597: : 249iter [00:08, 39.70iter/s]Best score: 6.9597: : 250iter [00:08, 39.59iter/s]Best score: 6.9597: : 250iter [00:08, 39.59iter/s]Best score: 6.9597: : 251iter [00:08, 39.59iter/s]Best score: 6.9597: : 252iter [00:08, 39.59iter/s]Best score: 6.9597: : 253iter [00:08, 39.59iter/s]Best score: 6.9597: : 254iter [00:08, 32.63iter/s]Best score: 6.9597: : 254iter [00:08, 32.63iter/s]Best score: 6.9597: : 255iter [00:08, 32.63iter/s]Best score: 6.9597: : 256iter [00:08, 32.63iter/s]Best score: 6.9597: : 257iter [00:08, 32.63iter/s]Best score: 6.9597: : 258iter [00:08, 32.63iter/s]Best score: 6.9597: : 259iter [00:08, 34.82iter/s]Best score: 6.9597: : 259iter [00:08, 34.82iter/s]Best score: 6.9597: : 260iter [00:08, 34.82iter/s]Best score: 6.9597: : 261iter [00:08, 34.82iter/s]Best score: 6.9597: : 262iter [00:08, 34.82iter/s]Best score: 6.9597: : 263iter [00:08, 35.96iter/s]Best score: 6.9597: : 263iter [00:08, 35.96iter/s]Best score: 6.9597: : 264iter [00:08, 35.96iter/s]Best score: 6.9597: : 265iter [00:08, 35.96iter/s]Best score: 6.9597: : 266iter [00:08, 35.96iter/s]Best score: 6.9597: : 267iter [00:09, 35.96iter/s]Best score: 6.9597: : 268iter [00:09, 37.38iter/s]Best score: 6.9597: : 268iter [00:09, 37.38iter/s]Best score: 6.9597: : 269iter [00:09, 37.38iter/s]Best score: 6.9597: : 270iter [00:09, 37.38iter/s]Best score: 6.9597: : 271iter [00:09, 37.38iter/s]Best score: 6.9597: : 272iter [00:09, 38.05iter/s]Best score: 6.9597: : 272iter [00:09, 38.05iter/s]Best score: 6.9597: : 273iter [00:09, 38.05iter/s]Best score: 6.9597: : 274iter [00:09, 38.05iter/s]Best score: 6.9597: : 275iter [00:09, 38.05iter/s]Best score: 6.9597: : 276iter [00:09, 38.05iter/s]Best score: 6.9597: : 277iter [00:09, 38.84iter/s]Best score: 6.9597: : 277iter [00:09, 38.84iter/s]Best score: 6.9597: : 278iter [00:09, 38.84iter/s]Best score: 6.9597: : 279iter [00:09, 38.84iter/s]Best score: 6.9597: : 280iter [00:09, 38.84iter/s]Best score: 6.9597: : 281iter [00:09, 39.06iter/s]Best score: 6.9597: : 281iter [00:09, 39.06iter/s]Best score: 6.9597: : 282iter [00:09, 39.06iter/s]Best score: 6.9597: : 283iter [00:09, 39.06iter/s]Best score: 6.9597: : 284iter [00:09, 39.06iter/s]Best score: 6.9597: : 285iter [00:09, 39.06iter/s]Best score: 6.9597: : 286iter [00:09, 39.62iter/s]Best score: 6.9597: : 286iter [00:09, 39.62iter/s]Best score: 6.9597: : 287iter [00:09, 39.62iter/s]Best score: 6.9597: : 288iter [00:09, 39.62iter/s]Best score: 6.9597: : 289iter [00:09, 39.62iter/s]Best score: 6.9597: : 290iter [00:09, 39.69iter/s]Best score: 6.9597: : 290iter [00:09, 39.69iter/s]Best score: 6.9597: : 291iter [00:09, 39.69iter/s]Best score: 6.9597: : 292iter [00:09, 39.69iter/s]Best score: 6.9597: : 293iter [00:09, 39.69iter/s]Best score: 6.9597: : 294iter [00:09, 39.69iter/s]Best score: 6.9597: : 295iter [00:09, 39.99iter/s]Best score: 6.9597: : 295iter [00:09, 39.99iter/s]Best score: 6.9597: : 296iter [00:09, 39.99iter/s]Best score: 6.9597: : 297iter [00:09, 39.99iter/s]Best score: 6.9597: : 298iter [00:09, 39.99iter/s]
[ITER 300] Best: 6.9597
[PARAMS] Current best parameters:
  fx: 530.7823
  fy: 530.7823
  px: 1029.0000
  py: 757.0000
  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: 6.9597: : 299iter [00:09, 39.99iter/s]Best score: 6.9597: : 300iter [00:09, 39.92iter/s]Best score: 6.9597: : 300iter [00:09, 39.92iter/s]Best score: 6.9597: : 301iter [00:09, 39.92iter/s]Best score: 6.9597: : 302iter [00:09, 39.92iter/s]Best score: 6.9597: : 303iter [00:09, 39.92iter/s]Best score: 6.9597: : 304iter [00:09, 33.25iter/s]Best score: 6.9597: : 304iter [00:10, 33.25iter/s]Best score: 6.9597: : 305iter [00:10, 33.25iter/s]Best score: 6.9597: : 306iter [00:10, 33.25iter/s]Best score: 6.9597: : 307iter [00:10, 33.25iter/s]Best score: 6.9597: : 308iter [00:10, 33.25iter/s]Best score: 6.9597: : 309iter [00:10, 35.27iter/s]Best score: 6.8853: : 309iter [00:10, 35.27iter/s]Best score: 6.8853: : 310iter [00:10, 35.27iter/s]Best score: 6.8853: : 311iter [00:10, 35.27iter/s]Best score: 6.8853: : 312iter [00:10, 35.27iter/s]Best score: 6.8853: : 313iter [00:10, 36.38iter/s]Best score: 6.8853: : 313iter [00:10, 36.38iter/s]Best score: 6.8853: : 314iter [00:10, 36.38iter/s]Best score: 6.8853: : 315iter [00:10, 36.38iter/s]Best score: 6.8853: : 316iter [00:10, 36.38iter/s]Best score: 6.8853: : 317iter [00:10, 36.38iter/s]Best score: 6.8853: : 318iter [00:10, 37.55iter/s]Best score: 6.8853: : 318iter [00:10, 37.55iter/s]Best score: 6.6537: : 319iter [00:10, 37.55iter/s]Best score: 6.6537: : 320iter [00:10, 37.55iter/s]Best score: 6.6537: : 321iter [00:10, 37.55iter/s]Best score: 6.6537: : 322iter [00:10, 38.11iter/s]Best score: 6.6537: : 322iter [00:10, 38.11iter/s]Best score: 6.6537: : 323iter [00:10, 38.11iter/s]Best score: 6.6537: : 324iter [00:10, 38.11iter/s]Best score: 6.6537: : 325iter [00:10, 38.11iter/s]Best score: 6.6537: : 326iter [00:10, 38.11iter/s]Best score: 6.6537: : 327iter [00:10, 38.85iter/s]Best score: 6.6537: : 327iter [00:10, 38.85iter/s]Best score: 6.6537: : 328iter [00:10, 38.85iter/s]Best score: 6.6537: : 329iter [00:10, 38.85iter/s]Best score: 6.6537: : 330iter [00:10, 38.85iter/s]Best score: 6.6537: : 331iter [00:10, 39.09iter/s]Best score: 6.6537: : 331iter [00:10, 39.09iter/s]Best score: 6.6537: : 332iter [00:10, 39.09iter/s]Best score: 6.6537: : 333iter [00:10, 39.09iter/s]Best score: 6.6537: : 334iter [00:10, 39.09iter/s]Best score: 6.6537: : 335iter [00:10, 39.09iter/s]Best score: 6.6537: : 336iter [00:10, 39.52iter/s]Best score: 6.6537: : 336iter [00:10, 39.52iter/s]Best score: 6.6537: : 337iter [00:10, 39.52iter/s]Best score: 6.6537: : 338iter [00:10, 39.52iter/s]Best score: 4.5521: : 339iter [00:10, 39.52iter/s]Best score: 4.5521: : 340iter [00:10, 39.52iter/s]Best score: 4.5521: : 340iter [00:10, 39.52iter/s]Best score: 4.5521: : 341iter [00:10, 39.52iter/s]Best score: 4.5521: : 342iter [00:10, 39.52iter/s]Best score: 4.5521: : 343iter [00:10, 39.52iter/s]Best score: 4.5521: : 344iter [00:11, 39.52iter/s]Best score: 4.5521: : 345iter [00:11, 39.81iter/s]Best score: 4.5521: : 345iter [00:11, 39.81iter/s]Best score: 4.5521: : 346iter [00:11, 39.81iter/s]Best score: 4.5521: : 347iter [00:11, 39.81iter/s]Best score: 4.5521: : 348iter [00:11, 39.81iter/s]
[ITER 350] Best: 3.5961
[PARAMS] Current best parameters:
  fx: 524.9556
  fy: 524.6770
  px: 1019.2972
  py: 752.2925
  k1: -0.01649076
  k2: 0.03651041
  k3: -0.01874873
  k4: 0.00230214
  p1: -0.00220560
  p2: 0.00197477
  p3: 0.00338729
  p4: -0.01502171
  s1: -0.0219
  s2: 0.0239
  s3: -0.0071
  s4: 0.0161
  tilt_x: -0.0309
  tilt_y: 0.0492
  scale: 3.0402
  rotation: -0.1051
Best score: 3.5961: : 349iter [00:11, 39.81iter/s]Best score: 3.5961: : 350iter [00:11, 39.80iter/s]Best score: 3.5961: : 350iter [00:11, 39.80iter/s]Best score: 3.5961: : 351iter [00:11, 39.80iter/s]Best score: 3.5961: : 352iter [00:11, 39.80iter/s]Best score: 3.5961: : 353iter [00:11, 39.80iter/s]Best score: 3.5961: : 354iter [00:11, 33.03iter/s]Best score: 3.5961: : 354iter [00:11, 33.03iter/s]Best score: 3.5961: : 355iter [00:11, 33.03iter/s]Best score: 3.5961: : 356iter [00:11, 33.03iter/s]Best score: 3.5961: : 357iter [00:11, 33.03iter/s]Best score: 3.5961: : 358iter [00:11, 33.03iter/s]Best score: 3.5961: : 359iter [00:11, 35.05iter/s]Best score: 3.5961: : 359iter [00:11, 35.05iter/s]Best score: 3.5961: : 360iter [00:11, 35.05iter/s]Best score: 3.5961: : 361iter [00:11, 35.05iter/s]Best score: 3.5961: : 362iter [00:11, 35.05iter/s]Best score: 3.5961: : 363iter [00:11, 36.18iter/s]Best score: 3.5961: : 363iter [00:11, 36.18iter/s]Best score: 3.5961: : 364iter [00:11, 36.18iter/s]Best score: 3.5961: : 365iter [00:11, 36.18iter/s]Best score: 3.5961: : 366iter [00:11, 36.18iter/s]Best score: 3.5961: : 367iter [00:11, 36.18iter/s]Best score: 3.5961: : 368iter [00:11, 37.38iter/s]Best score: 3.5961: : 368iter [00:11, 37.38iter/s]Best score: 3.4412: : 369iter [00:11, 37.38iter/s]Best score: 3.4412: : 370iter [00:11, 37.38iter/s]Best score: 3.4412: : 371iter [00:11, 37.38iter/s]Best score: 3.4412: : 372iter [00:11, 37.90iter/s]Best score: 3.4412: : 372iter [00:11, 37.90iter/s]Best score: 3.4412: : 373iter [00:11, 37.90iter/s]Best score: 3.4412: : 374iter [00:11, 37.90iter/s]Best score: 3.4412: : 375iter [00:11, 37.90iter/s]Best score: 3.4412: : 376iter [00:11, 37.90iter/s]Best score: 3.4412: : 377iter [00:11, 38.76iter/s]Best score: 3.4412: : 377iter [00:11, 38.76iter/s]Best score: 3.4412: : 378iter [00:11, 38.76iter/s]Best score: 3.2253: : 379iter [00:11, 38.76iter/s]Best score: 3.2253: : 380iter [00:11, 38.76iter/s]Best score: 3.2253: : 381iter [00:11, 39.01iter/s]Best score: 3.2253: : 381iter [00:12, 39.01iter/s]Best score: 3.2253: : 382iter [00:12, 39.01iter/s]Best score: 3.2253: : 383iter [00:12, 39.01iter/s]Best score: 3.2253: : 384iter [00:12, 39.01iter/s]Best score: 3.2253: : 385iter [00:12, 39.01iter/s]Best score: 3.2253: : 386iter [00:12, 39.34iter/s]Best score: 3.2253: : 386iter [00:12, 39.34iter/s]Best score: 3.2253: : 387iter [00:12, 39.34iter/s]Best score: 3.2253: : 388iter [00:12, 39.34iter/s]Best score: 1.9180: : 389iter [00:12, 39.34iter/s]Best score: 1.9180: : 390iter [00:12, 39.35iter/s]Best score: 1.9180: : 390iter [00:12, 39.35iter/s]Best score: 1.9180: : 391iter [00:12, 39.35iter/s]Best score: 1.9180: : 392iter [00:12, 39.35iter/s]Best score: 1.9180: : 393iter [00:12, 39.35iter/s]Best score: 1.9180: : 394iter [00:12, 39.35iter/s]Best score: 1.9180: : 395iter [00:12, 39.76iter/s]Best score: 1.9180: : 395iter [00:12, 39.76iter/s]Best score: 1.9180: : 396iter [00:12, 39.76iter/s]Best score: 1.9180: : 397iter [00:12, 39.76iter/s]Best score: 1.9180: : 398iter [00:12, 39.76iter/s]Best score: 1.9180: : 399iter [00:12, 30.79iter/s]
[ITER 400] Best: 1.6352
[PARAMS] Current best parameters:
  fx: 524.9563
  fy: 524.3099
  px: 1020.7392
  py: 752.1269
  k1: 0.00231872
  k2: 0.03527485
  k3: -0.03347337
  k4: 0.00823276
  p1: 0.00160979
  p2: 0.00836248
  p3: 0.00241609
  p4: -0.01110186
  s1: -0.0200
  s2: 0.0128
  s3: -0.0001
  s4: 0.0080
  tilt_x: -0.0351
  tilt_y: 0.0519
  scale: 2.9732
  rotation: -0.0875
Best score: 1.6352: : 399iter [00:12, 30.79iter/s]Best score: 1.6352: : 400iter [00:12, 30.79iter/s]Best score: 1.6352: : 401iter [00:12, 30.79iter/s]Best score: 1.6352: : 402iter [00:12, 30.79iter/s]Best score: 1.6352: : 403iter [00:12, 27.84iter/s]Best score: 1.6352: : 403iter [00:12, 27.84iter/s]Best score: 1.6352: : 404iter [00:12, 27.84iter/s]Best score: 1.6352: : 405iter [00:12, 27.84iter/s]Best score: 1.6352: : 406iter [00:12, 27.84iter/s]Best score: 1.6352: : 407iter [00:12, 27.84iter/s]Best score: 1.6352: : 408iter [00:12, 31.02iter/s]Best score: 1.6352: : 408iter [00:12, 31.02iter/s]Best score: 1.6352: : 409iter [00:12, 31.02iter/s]Best score: 1.6352: : 410iter [00:12, 31.02iter/s]Best score: 1.6352: : 411iter [00:12, 31.02iter/s]Best score: 1.6352: : 412iter [00:12, 33.01iter/s]Best score: 1.6352: : 412iter [00:12, 33.01iter/s]Best score: 1.6352: : 413iter [00:12, 33.01iter/s]Best score: 1.6352: : 414iter [00:13, 33.01iter/s]Best score: 1.6352: : 415iter [00:13, 33.01iter/s]Best score: 1.6352: : 416iter [00:13, 33.01iter/s]Best score: 1.6352: : 417iter [00:13, 35.15iter/s]Best score: 1.6352: : 417iter [00:13, 35.15iter/s]Best score: 1.6352: : 418iter [00:13, 35.15iter/s]Best score: 1.0717: : 419iter [00:13, 35.15iter/s]Best score: 1.0717: : 420iter [00:13, 35.15iter/s]Best score: 1.0717: : 421iter [00:13, 36.16iter/s]Best score: 1.0717: : 421iter [00:13, 36.16iter/s]Best score: 1.0717: : 422iter [00:13, 36.16iter/s]Best score: 1.0717: : 423iter [00:13, 36.16iter/s]Best score: 1.0717: : 424iter [00:13, 36.16iter/s]Best score: 1.0717: : 425iter [00:13, 36.16iter/s]Best score: 1.0717: : 426iter [00:13, 37.53iter/s]Best score: 1.0717: : 426iter [00:13, 37.53iter/s]Best score: 1.0717: : 427iter [00:13, 37.53iter/s]Best score: 1.0717: : 428iter [00:13, 37.53iter/s]Best score: 0.9502: : 429iter [00:13, 37.53iter/s]Best score: 0.9502: : 430iter [00:13, 38.01iter/s]Best score: 0.9502: : 430iter [00:13, 38.01iter/s]Best score: 0.9502: : 431iter [00:13, 38.01iter/s]Best score: 0.9502: : 432iter [00:13, 38.01iter/s]Best score: 0.9502: : 433iter [00:13, 38.01iter/s]Best score: 0.9502: : 434iter [00:13, 38.01iter/s]Best score: 0.9502: : 435iter [00:13, 38.78iter/s]Best score: 0.9502: : 435iter [00:13, 38.78iter/s]Best score: 0.9502: : 436iter [00:13, 38.78iter/s]Best score: 0.9502: : 437iter [00:13, 38.78iter/s]Best score: 0.9502: : 438iter [00:13, 38.78iter/s]Best score: 0.9502: : 439iter [00:13, 38.78iter/s]Best score: 0.9502: : 440iter [00:13, 39.09iter/s]Best score: 0.9502: : 440iter [00:13, 39.09iter/s]Best score: 0.9502: : 441iter [00:13, 39.09iter/s]Best score: 0.9502: : 442iter [00:13, 39.09iter/s]Best score: 0.9502: : 443iter [00:13, 39.09iter/s]Best score: 0.9502: : 444iter [00:13, 39.09iter/s]Best score: 0.9502: : 445iter [00:13, 39.58iter/s]Best score: 0.9502: : 445iter [00:13, 39.58iter/s]Best score: 0.9502: : 446iter [00:13, 39.58iter/s]Best score: 0.9502: : 447iter [00:13, 39.58iter/s]Best score: 0.9502: : 448iter [00:13, 39.58iter/s]
[ITER 450] Best: 0.9502
[PARAMS] Current best parameters:
  fx: 524.3529
  fy: 523.5027
  px: 1029.2370
  py: 753.0308
  k1: 0.01706575
  k2: -0.00171158
  k3: -0.00509496
  k4: 0.00124152
  p1: -0.00211115
  p2: 0.02253888
  p3: -0.01480763
  p4: -0.00097404
  s1: -0.0086
  s2: 0.0015
  s3: 0.0064
  s4: 0.0043
  tilt_x: -0.0246
  tilt_y: 0.0381
  scale: 2.9807
  rotation: 0.0707
Best score: 0.9502: : 449iter [00:13, 39.58iter/s]Best score: 0.9502: : 450iter [00:13, 39.47iter/s]Best score: 0.9502: : 450iter [00:13, 39.47iter/s]Best score: 0.9502: : 451iter [00:14, 39.47iter/s]Best score: 0.9502: : 452iter [00:14, 39.47iter/s]Best score: 0.9502: : 453iter [00:14, 39.47iter/s]Best score: 0.9502: : 454iter [00:14, 33.15iter/s]Best score: 0.9502: : 454iter [00:14, 33.15iter/s]Best score: 0.9502: : 455iter [00:14, 33.15iter/s]Best score: 0.9502: : 456iter [00:14, 33.15iter/s]Best score: 0.9502: : 457iter [00:14, 33.15iter/s]Best score: 0.9502: : 458iter [00:14, 33.15iter/s]Best score: 0.9502: : 459iter [00:14, 35.10iter/s]Best score: 0.7214: : 459iter [00:14, 35.10iter/s]Best score: 0.7214: : 460iter [00:14, 35.10iter/s]Best score: 0.7214: : 461iter [00:14, 35.10iter/s]Best score: 0.7214: : 462iter [00:14, 35.10iter/s]Best score: 0.7214: : 463iter [00:14, 36.19iter/s]Best score: 0.7214: : 463iter [00:14, 36.19iter/s]Best score: 0.7214: : 464iter [00:14, 36.19iter/s]Best score: 0.7214: : 465iter [00:14, 36.19iter/s]Best score: 0.7214: : 466iter [00:14, 36.19iter/s]Best score: 0.7214: : 467iter [00:14, 36.19iter/s]Best score: 0.7214: : 468iter [00:14, 37.52iter/s]Best score: 0.7214: : 468iter [00:14, 37.52iter/s]Best score: 0.6658: : 469iter [00:14, 37.52iter/s]Best score: 0.6658: : 470iter [00:14, 37.52iter/s]Best score: 0.6658: : 471iter [00:14, 37.52iter/s]Best score: 0.6658: : 472iter [00:14, 37.98iter/s]Best score: 0.6658: : 472iter [00:14, 37.98iter/s]Best score: 0.6658: : 473iter [00:14, 37.98iter/s]Best score: 0.6658: : 474iter [00:14, 37.98iter/s]Best score: 0.6658: : 475iter [00:14, 37.98iter/s]Best score: 0.6658: : 476iter [00:14, 37.98iter/s]Best score: 0.6658: : 477iter [00:14, 38.65iter/s]Best score: 0.6658: : 477iter [00:14, 38.65iter/s]Best score: 0.6658: : 478iter [00:14, 38.65iter/s]Best score: 0.3920: : 479iter [00:14, 38.65iter/s]Best score: 0.3920: : 480iter [00:14, 38.65iter/s]Best score: 0.3920: : 481iter [00:14, 38.93iter/s]Best score: 0.3920: : 481iter [00:14, 38.93iter/s]Best score: 0.3920: : 482iter [00:14, 38.93iter/s]Best score: 0.3920: : 483iter [00:14, 38.93iter/s]Best score: 0.3920: : 484iter [00:14, 38.93iter/s]Best score: 0.3920: : 485iter [00:14, 38.93iter/s]Best score: 0.3920: : 486iter [00:14, 39.38iter/s]Best score: 0.3920: : 486iter [00:14, 39.38iter/s]Best score: 0.3920: : 487iter [00:14, 39.38iter/s]Best score: 0.3920: : 488iter [00:14, 39.38iter/s]Best score: 0.3920: : 489iter [00:14, 39.38iter/s]Best score: 0.3920: : 490iter [00:14, 39.45iter/s]Best score: 0.3920: : 490iter [00:14, 39.45iter/s]Best score: 0.3920: : 491iter [00:15, 39.45iter/s]Best score: 0.3920: : 492iter [00:15, 39.45iter/s]Best score: 0.3920: : 493iter [00:15, 39.45iter/s]Best score: 0.3920: : 494iter [00:15, 39.45iter/s]Best score: 0.3920: : 495iter [00:15, 39.81iter/s]Best score: 0.3920: : 495iter [00:15, 39.81iter/s]Best score: 0.3920: : 496iter [00:15, 39.81iter/s]Best score: 0.3920: : 497iter [00:15, 39.81iter/s]Best score: 0.3920: : 498iter [00:15, 39.81iter/s]
[ITER 500] Best: 0.3920
[PARAMS] Current best parameters:
  fx: 526.1823
  fy: 525.6788
  px: 1027.9282
  py: 757.2474
  k1: -0.00515796
  k2: 0.03065010
  k3: -0.02318436
  k4: 0.00484693
  p1: 0.00296075
  p2: 0.02008066
  p3: -0.00745253
  p4: -0.00146567
  s1: -0.0105
  s2: 0.0004
  s3: 0.0004
  s4: 0.0012
  tilt_x: -0.0116
  tilt_y: 0.0407
  scale: 2.9867
  rotation: 0.0281
Best score: 0.3920: : 499iter [00:15, 39.81iter/s]Best score: 0.3920: : 500iter [00:15, 39.72iter/s]Best score: 0.3920: : 500iter [00:15, 39.72iter/s]Best score: 0.3920: : 501iter [00:15, 39.72iter/s]Best score: 0.3920: : 502iter [00:15, 39.72iter/s]Best score: 0.3920: : 503iter [00:15, 39.72iter/s]Best score: 0.3920: : 504iter [00:15, 33.03iter/s]Best score: 0.3920: : 504iter [00:15, 33.03iter/s]Best score: 0.3920: : 505iter [00:15, 33.03iter/s]Best score: 0.3920: : 506iter [00:15, 33.03iter/s]Best score: 0.3920: : 507iter [00:15, 33.03iter/s]Best score: 0.3920: : 508iter [00:15, 33.03iter/s]Best score: 0.3920: : 509iter [00:15, 35.10iter/s]Best score: 0.3920: : 509iter [00:15, 35.10iter/s]Best score: 0.3920: : 510iter [00:15, 35.10iter/s]Best score: 0.3920: : 511iter [00:15, 35.10iter/s]Best score: 0.3920: : 512iter [00:15, 35.10iter/s]Best score: 0.3920: : 513iter [00:15, 36.23iter/s]Best score: 0.3920: : 513iter [00:15, 36.23iter/s]Best score: 0.3920: : 514iter [00:15, 36.23iter/s]Best score: 0.3920: : 515iter [00:15, 36.23iter/s]Best score: 0.3920: : 516iter [00:15, 36.23iter/s]Best score: 0.3920: : 517iter [00:15, 36.23iter/s]Best score: 0.3920: : 518iter [00:15, 37.48iter/s]Best score: 0.3920: : 518iter [00:15, 37.48iter/s]Best score: 0.3920: : 519iter [00:15, 37.48iter/s]Best score: 0.3920: : 520iter [00:15, 37.48iter/s]Best score: 0.3920: : 521iter [00:15, 37.48iter/s]Best score: 0.3920: : 522iter [00:15, 38.00iter/s]Best score: 0.3920: : 522iter [00:15, 38.00iter/s]Best score: 0.3920: : 523iter [00:15, 38.00iter/s]Best score: 0.3920: : 524iter [00:15, 38.00iter/s]Best score: 0.3920: : 525iter [00:15, 38.00iter/s]Best score: 0.3920: : 526iter [00:15, 38.00iter/s]Best score: 0.3920: : 527iter [00:15, 38.91iter/s]Best score: 0.3920: : 527iter [00:15, 38.91iter/s]Best score: 0.3920: : 528iter [00:16, 38.91iter/s]Best score: 0.3920: : 529iter [00:16, 38.91iter/s]Best score: 0.3920: : 530iter [00:16, 38.91iter/s]Best score: 0.3920: : 531iter [00:16, 39.05iter/s]Best score: 0.3920: : 531iter [00:16, 39.05iter/s]Best score: 0.3920: : 532iter [00:16, 39.05iter/s]Best score: 0.3920: : 533iter [00:16, 39.05iter/s]Best score: 0.3920: : 534iter [00:16, 39.05iter/s]Best score: 0.3920: : 535iter [00:16, 39.05iter/s]Best score: 0.3920: : 536iter [00:16, 39.41iter/s]Best score: 0.3920: : 536iter [00:16, 39.41iter/s]Best score: 0.3920: : 537iter [00:16, 39.41iter/s]Best score: 0.3920: : 538iter [00:16, 39.41iter/s]Best score: 0.3673: : 539iter [00:16, 39.41iter/s]Best score: 0.3673: : 540iter [00:16, 39.54iter/s]Best score: 0.3673: : 540iter [00:16, 39.54iter/s]Best score: 0.3673: : 541iter [00:16, 39.54iter/s]Best score: 0.3673: : 542iter [00:16, 39.54iter/s]Best score: 0.3673: : 543iter [00:16, 39.54iter/s]Best score: 0.3673: : 544iter [00:16, 39.65iter/s]Best score: 0.3673: : 544iter [00:16, 39.65iter/s]Best score: 0.3673: : 545iter [00:16, 39.65iter/s]Best score: 0.3673: : 546iter [00:16, 39.65iter/s]Best score: 0.3673: : 547iter [00:16, 39.65iter/s]Best score: 0.3673: : 548iter [00:16, 39.65iter/s]Best score: 0.3673: : 549iter [00:16, 39.91iter/s]
[ITER 550] Best: 0.3375
[PARAMS] Current best parameters:
  fx: 518.2666
  fy: 518.2146
  px: 1030.3162
  py: 753.5781
  k1: 0.02293233
  k2: 0.00080263
  k3: -0.00693766
  k4: 0.00147861
  p1: -0.00225499
  p2: 0.01652004
  p3: 0.00037550
  p4: 0.00133460
  s1: -0.0156
  s2: -0.0013
  s3: -0.0094
  s4: 0.0008
  tilt_x: -0.0186
  tilt_y: 0.0217
  scale: 2.9662
  rotation: -0.0496
Best score: 0.3375: : 549iter [00:16, 39.91iter/s]Best score: 0.3375: : 550iter [00:16, 39.91iter/s]Best score: 0.3375: : 551iter [00:16, 39.91iter/s]Best score: 0.3375: : 552iter [00:16, 39.91iter/s]Best score: 0.3375: : 553iter [00:16, 32.79iter/s]Best score: 0.3375: : 553iter [00:16, 32.79iter/s]Best score: 0.3375: : 554iter [00:16, 32.79iter/s]Best score: 0.3375: : 555iter [00:16, 32.79iter/s]Best score: 0.3375: : 556iter [00:16, 32.79iter/s]Best score: 0.3375: : 557iter [00:16, 32.79iter/s]Best score: 0.3375: : 558iter [00:16, 35.02iter/s]Best score: 0.3375: : 558iter [00:16, 35.02iter/s]Best score: 0.3375: : 559iter [00:16, 35.02iter/s]Best score: 0.3375: : 560iter [00:16, 35.02iter/s]Best score: 0.3375: : 561iter [00:16, 35.02iter/s]Best score: 0.3375: : 562iter [00:16, 36.13iter/s]Best score: 0.3375: : 562iter [00:16, 36.13iter/s]Best score: 0.3375: : 563iter [00:16, 36.13iter/s]Best score: 0.3375: : 564iter [00:16, 36.13iter/s]Best score: 0.3375: : 565iter [00:17, 36.13iter/s]Best score: 0.3375: : 566iter [00:17, 36.13iter/s]Best score: 0.3375: : 567iter [00:17, 37.47iter/s]Best score: 0.3375: : 567iter [00:17, 37.47iter/s]Best score: 0.3375: : 568iter [00:17, 37.47iter/s]Best score: 0.2973: : 569iter [00:17, 37.47iter/s]Best score: 0.2973: : 570iter [00:17, 37.47iter/s]Best score: 0.2973: : 571iter [00:17, 37.94iter/s]Best score: 0.2973: : 571iter [00:17, 37.94iter/s]Best score: 0.2973: : 572iter [00:17, 37.94iter/s]Best score: 0.2973: : 573iter [00:17, 37.94iter/s]Best score: 0.2973: : 574iter [00:17, 37.94iter/s]Best score: 0.2973: : 575iter [00:17, 37.94iter/s]Best score: 0.2973: : 576iter [00:17, 38.79iter/s]Best score: 0.2973: : 576iter [00:17, 38.79iter/s]Best score: 0.2973: : 577iter [00:17, 38.79iter/s]Best score: 0.2973: : 578iter [00:17, 38.79iter/s]Best score: 0.2973: : 579iter [00:17, 38.79iter/s]Best score: 0.2973: : 580iter [00:17, 38.96iter/s]Best score: 0.2973: : 580iter [00:17, 38.96iter/s]Best score: 0.2973: : 581iter [00:17, 38.96iter/s]Best score: 0.2973: : 582iter [00:17, 38.96iter/s]Best score: 0.2973: : 583iter [00:17, 38.96iter/s]Best score: 0.2973: : 584iter [00:17, 39.24iter/s]Best score: 0.2973: : 584iter [00:17, 39.24iter/s]Best score: 0.2973: : 585iter [00:17, 39.24iter/s]Best score: 0.2973: : 586iter [00:17, 39.24iter/s]Best score: 0.2973: : 587iter [00:17, 39.24iter/s]Best score: 0.2973: : 588iter [00:17, 39.24iter/s]Best score: 0.2973: : 589iter [00:17, 39.67iter/s]Best score: 0.2658: : 589iter [00:17, 39.67iter/s]Best score: 0.2658: : 590iter [00:17, 39.67iter/s]Best score: 0.2658: : 591iter [00:17, 39.67iter/s]Best score: 0.2658: : 592iter [00:17, 39.67iter/s]Best score: 0.2658: : 593iter [00:17, 39.59iter/s]Best score: 0.2658: : 593iter [00:17, 39.59iter/s]Best score: 0.2658: : 594iter [00:17, 39.59iter/s]Best score: 0.2658: : 595iter [00:17, 39.59iter/s]Best score: 0.2658: : 596iter [00:17, 39.59iter/s]Best score: 0.2658: : 597iter [00:17, 39.59iter/s]Best score: 0.2658: : 598iter [00:17, 39.98iter/s]Best score: 0.2658: : 598iter [00:17, 39.98iter/s]
[ITER 600] Best: 0.2658
[PARAMS] Current best parameters:
  fx: 519.7452
  fy: 519.4661
  px: 1029.4888
  py: 755.3515
  k1: 0.00694002
  k2: 0.01584985
  k3: -0.01132783
  k4: 0.00167543
  p1: -0.00008679
  p2: 0.01839101
  p3: -0.00391054
  p4: 0.00138843
  s1: -0.0147
  s2: -0.0006
  s3: -0.0034
  s4: 0.0001
  tilt_x: -0.0149
  tilt_y: 0.0293
  scale: 2.9906
  rotation: 0.0142
Best score: 0.2658: : 599iter [00:17, 39.98iter/s]Best score: 0.2658: : 600iter [00:17, 39.98iter/s]Best score: 0.2658: : 601iter [00:17, 39.98iter/s]Best score: 0.2658: : 602iter [00:18, 39.98iter/s]Best score: 0.2658: : 603iter [00:18, 33.43iter/s]Best score: 0.2658: : 603iter [00:18, 33.43iter/s]Best score: 0.2658: : 604iter [00:18, 33.43iter/s]Best score: 0.2658: : 605iter [00:18, 33.43iter/s]Best score: 0.2658: : 606iter [00:18, 33.43iter/s]Best score: 0.2658: : 607iter [00:18, 33.43iter/s]Best score: 0.2658: : 608iter [00:18, 35.38iter/s]Best score: 0.2658: : 608iter [00:18, 35.38iter/s]Best score: 0.2561: : 609iter [00:18, 35.38iter/s]Best score: 0.2561: : 610iter [00:18, 35.38iter/s]Best score: 0.2561: : 611iter [00:18, 35.38iter/s]Best score: 0.2561: : 612iter [00:18, 36.34iter/s]Best score: 0.2561: : 612iter [00:18, 36.34iter/s]Best score: 0.2561: : 613iter [00:18, 36.34iter/s]Best score: 0.2561: : 614iter [00:18, 36.34iter/s]Best score: 0.2561: : 615iter [00:18, 36.34iter/s]Best score: 0.2561: : 616iter [00:18, 36.34iter/s]Best score: 0.2561: : 617iter [00:18, 37.57iter/s]Best score: 0.2561: : 617iter [00:18, 37.57iter/s]Best score: 0.2561: : 618iter [00:18, 37.57iter/s]Best score: 0.2561: : 619iter [00:18, 37.57iter/s]Best score: 0.2561: : 620iter [00:18, 37.57iter/s]Best score: 0.2561: : 621iter [00:18, 38.09iter/s]Best score: 0.2561: : 621iter [00:18, 38.09iter/s]Best score: 0.2561: : 622iter [00:18, 38.09iter/s]Best score: 0.2561: : 623iter [00:18, 38.09iter/s]Best score: 0.2561: : 624iter [00:18, 38.09iter/s]Best score: 0.2561: : 625iter [00:18, 38.09iter/s]Best score: 0.2561: : 626iter [00:18, 38.81iter/s]Best score: 0.2561: : 626iter [00:18, 38.81iter/s]Best score: 0.2561: : 627iter [00:18, 38.81iter/s]Best score: 0.2561: : 628iter [00:18, 38.81iter/s]Best score: 0.2322: : 629iter [00:18, 38.81iter/s]Best score: 0.2322: : 630iter [00:18, 38.96iter/s]Best score: 0.2322: : 630iter [00:18, 38.96iter/s]Best score: 0.2322: : 631iter [00:18, 38.96iter/s]Best score: 0.2322: : 632iter [00:18, 38.96iter/s]Best score: 0.2322: : 633iter [00:18, 38.96iter/s]Best score: 0.2322: : 634iter [00:18, 38.96iter/s]Best score: 0.2322: : 635iter [00:18, 39.30iter/s]Best score: 0.2322: : 635iter [00:18, 39.30iter/s]Best score: 0.2322: : 636iter [00:18, 39.30iter/s]Best score: 0.2322: : 637iter [00:18, 39.30iter/s]Best score: 0.2322: : 638iter [00:18, 39.30iter/s]Best score: 0.2322: : 639iter [00:18, 39.43iter/s]Best score: 0.2235: : 639iter [00:18, 39.43iter/s]Best score: 0.2235: : 640iter [00:18, 39.43iter/s]Best score: 0.2235: : 641iter [00:18, 39.43iter/s]Best score: 0.2235: : 642iter [00:19, 39.43iter/s]Best score: 0.2235: : 643iter [00:19, 39.29iter/s]Best score: 0.2235: : 643iter [00:19, 39.29iter/s]Best score: 0.2235: : 644iter [00:19, 39.29iter/s]Best score: 0.2235: : 645iter [00:19, 39.29iter/s]Best score: 0.2235: : 646iter [00:19, 39.29iter/s]Best score: 0.2235: : 647iter [00:19, 39.29iter/s]Best score: 0.2235: : 648iter [00:19, 39.66iter/s]Best score: 0.2235: : 648iter [00:19, 39.66iter/s]
[ITER 650] Best: 0.2232
[PARAMS] Current best parameters:
  fx: 519.5038
  fy: 519.2241
  px: 1027.2714
  py: 754.7517
  k1: 0.00510599
  k2: 0.02074272
  k3: -0.01454681
  k4: 0.00232789
  p1: -0.00227111
  p2: 0.01490022
  p3: 0.00050863
  p4: 0.00133741
  s1: -0.0177
  s2: -0.0006
  s3: -0.0049
  s4: -0.0007
  tilt_x: -0.0135
  tilt_y: 0.0334
  scale: 2.9871
  rotation: -0.0074
Best score: 0.2232: : 649iter [00:19, 39.66iter/s]Best score: 0.2232: : 650iter [00:19, 39.66iter/s]Best score: 0.2232: : 651iter [00:19, 39.66iter/s]Best score: 0.2232: : 652iter [00:19, 32.59iter/s]Best score: 0.2232: : 652iter [00:19, 32.59iter/s]Best score: 0.2232: : 653iter [00:19, 32.59iter/s]Best score: 0.2232: : 654iter [00:19, 32.59iter/s]Best score: 0.2232: : 655iter [00:19, 32.59iter/s]Best score: 0.2232: : 656iter [00:19, 32.59iter/s]Best score: 0.2232: : 657iter [00:19, 34.74iter/s]Best score: 0.2232: : 657iter [00:19, 34.74iter/s]Best score: 0.2232: : 658iter [00:19, 34.74iter/s]Best score: 0.2198: : 659iter [00:19, 34.74iter/s]Best score: 0.2198: : 660iter [00:19, 34.74iter/s]Best score: 0.2198: : 661iter [00:19, 35.85iter/s]Best score: 0.2198: : 661iter [00:19, 35.85iter/s]Best score: 0.2198: : 662iter [00:19, 35.85iter/s]Best score: 0.2198: : 663iter [00:19, 35.85iter/s]Best score: 0.2198: : 664iter [00:19, 35.85iter/s]Best score: 0.2198: : 665iter [00:19, 36.89iter/s]Best score: 0.2198: : 665iter [00:19, 36.89iter/s]Best score: 0.2198: : 666iter [00:19, 36.89iter/s]Best score: 0.2198: : 667iter [00:19, 36.89iter/s]Best score: 0.2198: : 668iter [00:19, 36.89iter/s]Best score: 0.2014: : 669iter [00:19, 36.89iter/s]Best score: 0.2014: : 670iter [00:19, 37.66iter/s]Best score: 0.2014: : 670iter [00:19, 37.66iter/s]Best score: 0.2014: : 671iter [00:19, 37.66iter/s]Best score: 0.2014: : 672iter [00:19, 37.66iter/s]Best score: 0.2014: : 673iter [00:19, 37.66iter/s]Best score: 0.2014: : 674iter [00:19, 37.66iter/s]Best score: 0.2014: : 675iter [00:19, 38.51iter/s]Best score: 0.2014: : 675iter [00:19, 38.51iter/s]Best score: 0.2014: : 676iter [00:19, 38.51iter/s]Best score: 0.2014: : 677iter [00:19, 38.51iter/s]Best score: 0.2014: : 678iter [00:20, 38.51iter/s]Best score: 0.2014: : 679iter [00:20, 38.51iter/s]Best score: 0.2014: : 680iter [00:20, 38.87iter/s]Best score: 0.2014: : 680iter [00:20, 38.87iter/s]Best score: 0.2014: : 681iter [00:20, 38.87iter/s]Best score: 0.2014: : 682iter [00:20, 38.87iter/s]Best score: 0.2014: : 683iter [00:20, 38.87iter/s]Best score: 0.2014: : 684iter [00:20, 38.87iter/s]Best score: 0.2014: : 685iter [00:20, 39.39iter/s]Best score: 0.2014: : 685iter [00:20, 39.39iter/s]Best score: 0.2014: : 686iter [00:20, 39.39iter/s]Best score: 0.2014: : 687iter [00:20, 39.39iter/s]Best score: 0.2014: : 688iter [00:20, 39.39iter/s]Best score: 0.2014: : 689iter [00:20, 39.39iter/s]Best score: 0.2014: : 690iter [00:20, 39.59iter/s]Best score: 0.2014: : 690iter [00:20, 39.59iter/s]Best score: 0.2014: : 691iter [00:20, 39.59iter/s]Best score: 0.2014: : 692iter [00:20, 39.59iter/s]Best score: 0.2014: : 693iter [00:20, 39.59iter/s]Best score: 0.2014: : 694iter [00:20, 39.59iter/s]Best score: 0.2014: : 695iter [00:20, 39.82iter/s]Best score: 0.2014: : 695iter [00:20, 39.82iter/s]Best score: 0.2014: : 696iter [00:20, 39.82iter/s]Best score: 0.2014: : 697iter [00:20, 39.82iter/s]Best score: 0.2014: : 698iter [00:20, 39.82iter/s]Best score: 0.2014: : 699iter [00:20, 39.81iter/s]
[ITER 700] Best: 0.2013
[PARAMS] Current best parameters:
  fx: 518.4641
  fy: 518.1587
  px: 1028.0368
  py: 754.9669
  k1: 0.00417367
  k2: 0.01945995
  k3: -0.01214283
  k4: 0.00164502
  p1: 0.00026445
  p2: 0.01559620
  p3: 0.00052033
  p4: -0.00002114
  s1: -0.0176
  s2: 0.0007
  s3: -0.0048
  s4: -0.0001
  tilt_x: -0.0183
  tilt_y: 0.0310
  scale: 3.0002
  rotation: 0.0260
Best score: 0.2013: : 699iter [00:20, 39.81iter/s]Best score: 0.2013: : 700iter [00:20, 39.81iter/s]Best score: 0.2013: : 701iter [00:20, 39.81iter/s]Best score: 0.2013: : 702iter [00:20, 39.81iter/s]Best score: 0.2013: : 703iter [00:20, 32.78iter/s]Best score: 0.2013: : 703iter [00:20, 32.78iter/s]Best score: 0.2013: : 704iter [00:20, 32.78iter/s]Best score: 0.2013: : 705iter [00:20, 32.78iter/s]Best score: 0.2013: : 706iter [00:20, 32.78iter/s]Best score: 0.2013: : 707iter [00:20, 32.78iter/s]Best score: 0.2013: : 708iter [00:20, 34.89iter/s]Best score: 0.2013: : 708iter [00:20, 34.89iter/s]Best score: 0.2006: : 709iter [00:20, 34.89iter/s]Best score: 0.2006: : 710iter [00:20, 34.89iter/s]Best score: 0.2006: : 711iter [00:20, 34.89iter/s]Best score: 0.2006: : 712iter [00:20, 36.06iter/s]Best score: 0.2006: : 712iter [00:20, 36.06iter/s]Best score: 0.2006: : 713iter [00:20, 36.06iter/s]Best score: 0.2006: : 714iter [00:21, 36.06iter/s]Best score: 0.2006: : 715iter [00:21, 36.06iter/s]Best score: 0.2006: : 716iter [00:21, 29.00iter/s]Best score: 0.2006: : 716iter [00:21, 29.00iter/s]Best score: 0.2006: : 717iter [00:21, 29.00iter/s]Best score: 0.2006: : 718iter [00:21, 29.00iter/s]Best score: 0.1890: : 719iter [00:21, 29.00iter/s]Best score: 0.1890: : 720iter [00:21, 31.37iter/s]Best score: 0.1890: : 720iter [00:21, 31.37iter/s]Best score: 0.1890: : 721iter [00:21, 31.37iter/s]Best score: 0.1890: : 722iter [00:21, 31.37iter/s]Best score: 0.1890: : 723iter [00:21, 31.37iter/s]Best score: 0.1890: : 724iter [00:21, 31.37iter/s]Best score: 0.1890: : 725iter [00:21, 33.96iter/s]Best score: 0.1890: : 725iter [00:21, 33.96iter/s]Best score: 0.1890: : 726iter [00:21, 33.96iter/s]Best score: 0.1890: : 727iter [00:21, 33.96iter/s]Best score: 0.1890: : 728iter [00:21, 33.96iter/s]Best score: 0.1890: : 729iter [00:21, 35.25iter/s]Best score: 0.1890: : 729iter [00:21, 35.25iter/s]Best score: 0.1890: : 730iter [00:21, 35.25iter/s]Best score: 0.1890: : 731iter [00:21, 35.25iter/s]Best score: 0.1890: : 732iter [00:21, 35.25iter/s]Best score: 0.1890: : 733iter [00:21, 36.29iter/s]Best score: 0.1890: : 733iter [00:21, 36.29iter/s]Best score: 0.1890: : 734iter [00:21, 36.29iter/s]Best score: 0.1890: : 735iter [00:21, 36.29iter/s]Best score: 0.1890: : 736iter [00:21, 36.29iter/s]Best score: 0.1890: : 737iter [00:21, 36.29iter/s]Best score: 0.1890: : 738iter [00:21, 37.59iter/s]Best score: 0.1890: : 738iter [00:21, 37.59iter/s]Best score: 0.1871: : 739iter [00:21, 37.59iter/s]Best score: 0.1871: : 740iter [00:21, 37.59iter/s]Best score: 0.1871: : 741iter [00:21, 37.59iter/s]Best score: 0.1871: : 742iter [00:21, 38.12iter/s]Best score: 0.1871: : 742iter [00:21, 38.12iter/s]Best score: 0.1871: : 743iter [00:21, 38.12iter/s]Best score: 0.1871: : 744iter [00:21, 38.12iter/s]Best score: 0.1871: : 745iter [00:21, 38.12iter/s]Best score: 0.1871: : 746iter [00:21, 38.12iter/s]Best score: 0.1871: : 747iter [00:21, 38.83iter/s]Best score: 0.1871: : 747iter [00:21, 38.83iter/s]Best score: 0.1871: : 748iter [00:21, 38.83iter/s]
[ITER 750] Best: 0.1846
[PARAMS] Current best parameters:
  fx: 518.5995
  fy: 518.1839
  px: 1025.8319
  py: 753.8951
  k1: -0.00319240
  k2: 0.02515731
  k3: -0.01319318
  k4: 0.00162384
  p1: 0.00004879
  p2: 0.01235300
  p3: 0.00770337
  p4: -0.00164905
  s1: -0.0245
  s2: 0.0028
  s3: -0.0134
  s4: 0.0019
  tilt_x: -0.0230
  tilt_y: 0.0351
  scale: 3.0208
  rotation: 0.0073
Best score: 0.1846: : 749iter [00:21, 38.83iter/s]Best score: 0.1846: : 750iter [00:22, 38.83iter/s]Best score: 0.1846: : 751iter [00:22, 32.18iter/s]Best score: 0.1846: : 751iter [00:22, 32.18iter/s]Best score: 0.1846: : 752iter [00:22, 32.18iter/s]Best score: 0.1846: : 753iter [00:22, 32.18iter/s]Best score: 0.1846: : 754iter [00:22, 32.18iter/s]Best score: 0.1846: : 755iter [00:22, 32.18iter/s]Best score: 0.1846: : 756iter [00:22, 34.54iter/s]Best score: 0.1846: : 756iter [00:22, 34.54iter/s]Best score: 0.1846: : 757iter [00:22, 34.54iter/s]Best score: 0.1846: : 758iter [00:22, 34.54iter/s]Best score: 0.1840: : 759iter [00:22, 34.54iter/s]Best score: 0.1840: : 760iter [00:22, 35.75iter/s]Best score: 0.1840: : 760iter [00:22, 35.75iter/s]Best score: 0.1840: : 761iter [00:22, 35.75iter/s]Best score: 0.1840: : 762iter [00:22, 35.75iter/s]Best score: 0.1840: : 763iter [00:22, 35.75iter/s]Best score: 0.1840: : 764iter [00:22, 35.75iter/s]Best score: 0.1840: : 765iter [00:22, 37.16iter/s]Best score: 0.1840: : 765iter [00:22, 37.16iter/s]Best score: 0.1840: : 766iter [00:22, 37.16iter/s]Best score: 0.1840: : 767iter [00:22, 37.16iter/s]Best score: 0.1840: : 768iter [00:22, 37.16iter/s]Best score: 0.1798: : 769iter [00:22, 37.16iter/s]Best score: 0.1798: : 770iter [00:22, 37.84iter/s]Best score: 0.1798: : 770iter [00:22, 37.84iter/s]Best score: 0.1798: : 771iter [00:22, 37.84iter/s]Best score: 0.1798: : 772iter [00:22, 37.84iter/s]Best score: 0.1798: : 773iter [00:22, 37.84iter/s]Best score: 0.1798: : 774iter [00:22, 37.84iter/s]Best score: 0.1798: : 775iter [00:22, 38.64iter/s]Best score: 0.1798: : 775iter [00:22, 38.64iter/s]Best score: 0.1798: : 776iter [00:22, 38.64iter/s]Best score: 0.1798: : 777iter [00:22, 38.64iter/s]Best score: 0.1798: : 778iter [00:22, 38.64iter/s]Best score: 0.1798: : 779iter [00:22, 38.64iter/s]Best score: 0.1798: : 780iter [00:22, 39.10iter/s]Best score: 0.1798: : 780iter [00:22, 39.10iter/s]Best score: 0.1798: : 781iter [00:22, 39.10iter/s]Best score: 0.1798: : 782iter [00:22, 39.10iter/s]Best score: 0.1798: : 783iter [00:22, 39.10iter/s]Best score: 0.1798: : 784iter [00:22, 39.10iter/s]Best score: 0.1798: : 785iter [00:22, 39.54iter/s]Best score: 0.1798: : 785iter [00:22, 39.54iter/s]Best score: 0.1798: : 786iter [00:22, 39.54iter/s]Best score: 0.1798: : 787iter [00:22, 39.54iter/s]Best score: 0.1798: : 788iter [00:23, 39.54iter/s]Best score: 0.1798: : 789iter [00:23, 39.54iter/s]Best score: 0.1798: : 790iter [00:23, 39.67iter/s]Best score: 0.1798: : 790iter [00:23, 39.67iter/s]Best score: 0.1798: : 791iter [00:23, 39.67iter/s]Best score: 0.1798: : 792iter [00:23, 39.67iter/s]Best score: 0.1798: : 793iter [00:23, 39.67iter/s]Best score: 0.1798: : 794iter [00:23, 39.67iter/s]Best score: 0.1798: : 795iter [00:23, 40.00iter/s]Best score: 0.1798: : 795iter [00:23, 40.00iter/s]Best score: 0.1798: : 796iter [00:23, 40.00iter/s]Best score: 0.1798: : 797iter [00:23, 40.00iter/s]Best score: 0.1798: : 798iter [00:23, 40.00iter/s]
[ITER 800] Best: 0.1791
[PARAMS] Current best parameters:
  fx: 520.6297
  fy: 520.3010
  px: 1025.8046
  py: 753.9127
  k1: -0.00904249
  k2: 0.02800616
  k3: -0.01338886
  k4: 0.00149845
  p1: 0.00121293
  p2: 0.01423507
  p3: 0.00900596
  p4: -0.00291273
  s1: -0.0265
  s2: 0.0036
  s3: -0.0155
  s4: 0.0030
  tilt_x: -0.0257
  tilt_y: 0.0394
  scale: 3.0281
  rotation: 0.0135
Best score: 0.1791: : 799iter [00:23, 40.00iter/s]Best score: 0.1791: : 800iter [00:23, 39.81iter/s]Best score: 0.1791: : 800iter [00:23, 39.81iter/s]Best score: 0.1791: : 801iter [00:23, 39.81iter/s]Best score: 0.1791: : 802iter [00:23, 39.81iter/s]Best score: 0.1791: : 803iter [00:23, 39.81iter/s]Best score: 0.1791: : 804iter [00:23, 33.35iter/s]Best score: 0.1791: : 804iter [00:23, 33.35iter/s]Best score: 0.1791: : 805iter [00:23, 33.35iter/s]Best score: 0.1791: : 806iter [00:23, 33.35iter/s]Best score: 0.1791: : 807iter [00:23, 33.35iter/s]Best score: 0.1791: : 808iter [00:23, 33.35iter/s]Best score: 0.1791: : 809iter [00:23, 35.38iter/s]Best score: 0.1782: : 809iter [00:23, 35.38iter/s]Best score: 0.1782: : 810iter [00:23, 35.38iter/s]Best score: 0.1782: : 811iter [00:23, 35.38iter/s]Best score: 0.1782: : 812iter [00:23, 35.38iter/s]Best score: 0.1782: : 813iter [00:23, 36.34iter/s]Best score: 0.1782: : 813iter [00:23, 36.34iter/s]Best score: 0.1782: : 814iter [00:23, 36.34iter/s]Best score: 0.1782: : 815iter [00:23, 36.34iter/s]Best score: 0.1782: : 816iter [00:23, 36.34iter/s]Best score: 0.1782: : 817iter [00:23, 36.34iter/s]Best score: 0.1782: : 818iter [00:23, 37.56iter/s]Best score: 0.1782: : 818iter [00:23, 37.56iter/s]Best score: 0.1764: : 819iter [00:23, 37.56iter/s]Best score: 0.1764: : 820iter [00:23, 37.56iter/s]Best score: 0.1764: : 821iter [00:23, 37.56iter/s]Best score: 0.1764: : 822iter [00:23, 37.86iter/s]Best score: 0.1764: : 822iter [00:23, 37.86iter/s]Best score: 0.1764: : 823iter [00:23, 37.86iter/s]Best score: 0.1764: : 824iter [00:23, 37.86iter/s]Best score: 0.1764: : 825iter [00:24, 37.86iter/s]Best score: 0.1764: : 826iter [00:24, 37.86iter/s]Best score: 0.1764: : 827iter [00:24, 38.63iter/s]Best score: 0.1764: : 827iter [00:24, 38.63iter/s]Best score: 0.1764: : 828iter [00:24, 38.63iter/s]Best score: 0.1759: : 829iter [00:24, 38.63iter/s]Best score: 0.1759: : 830iter [00:24, 38.63iter/s]Best score: 0.1759: : 831iter [00:24, 38.71iter/s]Best score: 0.1759: : 831iter [00:24, 38.71iter/s]Best score: 0.1759: : 832iter [00:24, 38.71iter/s]Best score: 0.1759: : 833iter [00:24, 38.71iter/s]Best score: 0.1759: : 834iter [00:24, 38.71iter/s]Best score: 0.1759: : 835iter [00:24, 39.06iter/s]Best score: 0.1759: : 835iter [00:24, 39.06iter/s]Best score: 0.1759: : 836iter [00:24, 39.06iter/s]Best score: 0.1759: : 837iter [00:24, 39.06iter/s]Best score: 0.1759: : 838iter [00:24, 39.06iter/s]Best score: 0.1758: : 839iter [00:24, 39.06iter/s]Best score: 0.1758: : 840iter [00:24, 39.22iter/s]Best score: 0.1758: : 840iter [00:24, 39.22iter/s]Best score: 0.1758: : 841iter [00:24, 39.22iter/s]Best score: 0.1758: : 842iter [00:24, 39.22iter/s]Best score: 0.1758: : 843iter [00:24, 39.22iter/s]Best score: 0.1758: : 844iter [00:24, 39.22iter/s]Best score: 0.1758: : 845iter [00:24, 39.67iter/s]Best score: 0.1758: : 845iter [00:24, 39.67iter/s]Best score: 0.1758: : 846iter [00:24, 39.67iter/s]Best score: 0.1758: : 847iter [00:24, 39.67iter/s]Best score: 0.1758: : 848iter [00:24, 39.67iter/s]Best score: 0.1758: : 849iter [00:24, 39.71iter/s]
[ITER 850] Best: 0.1758
[PARAMS] Current best parameters:
  fx: 519.5079
  fy: 519.1056
  px: 1026.6938
  py: 753.9229
  k1: -0.00357517
  k2: 0.02368447
  k3: -0.01176487
  k4: 0.00122151
  p1: 0.00008983
  p2: 0.01248373
  p3: 0.00638902
  p4: -0.00116590
  s1: -0.0219
  s2: 0.0020
  s3: -0.0123
  s4: 0.0015
  tilt_x: -0.0231
  tilt_y: 0.0313
  scale: 3.0176
  rotation: 0.0079
Best score: 0.1758: : 849iter [00:24, 39.71iter/s]Best score: 0.1758: : 850iter [00:24, 39.71iter/s]Best score: 0.1758: : 851iter [00:24, 39.71iter/s]Best score: 0.1758: : 852iter [00:24, 39.71iter/s]Best score: 0.1758: : 853iter [00:24, 32.66iter/s]Best score: 0.1758: : 853iter [00:24, 32.66iter/s]Best score: 0.1758: : 854iter [00:24, 32.66iter/s]Best score: 0.1758: : 855iter [00:24, 32.66iter/s]Best score: 0.1758: : 856iter [00:24, 32.66iter/s]Best score: 0.1758: : 857iter [00:24, 32.66iter/s]Best score: 0.1758: : 858iter [00:24, 34.85iter/s]Best score: 0.1758: : 858iter [00:24, 34.85iter/s]Best score: 0.1740: : 859iter [00:24, 34.85iter/s]Best score: 0.1740: : 860iter [00:24, 34.85iter/s]Best score: 0.1740: : 861iter [00:25, 34.85iter/s]Best score: 0.1740: : 862iter [00:25, 36.01iter/s]Best score: 0.1740: : 862iter [00:25, 36.01iter/s]Best score: 0.1740: : 863iter [00:25, 36.01iter/s]Best score: 0.1740: : 864iter [00:25, 36.01iter/s]Best score: 0.1740: : 865iter [00:25, 36.01iter/s]Best score: 0.1740: : 866iter [00:25, 36.01iter/s]Best score: 0.1740: : 867iter [00:25, 37.42iter/s]Best score: 0.1740: : 867iter [00:25, 37.42iter/s]Best score: 0.1740: : 868iter [00:25, 37.42iter/s]Best score: 0.1740: : 869iter [00:25, 37.42iter/s]Best score: 0.1740: : 870iter [00:25, 37.42iter/s]Best score: 0.1740: : 871iter [00:25, 38.02iter/s]Best score: 0.1740: : 871iter [00:25, 38.02iter/s]Best score: 0.1740: : 872iter [00:25, 38.02iter/s]Best score: 0.1740: : 873iter [00:25, 38.02iter/s]Best score: 0.1740: : 874iter [00:25, 38.02iter/s]Best score: 0.1740: : 875iter [00:25, 38.02iter/s]Best score: 0.1740: : 876iter [00:25, 38.72iter/s]Best score: 0.1740: : 876iter [00:25, 38.72iter/s]Best score: 0.1740: : 877iter [00:25, 38.72iter/s]Best score: 0.1740: : 878iter [00:25, 38.72iter/s]Best score: 0.1740: : 879iter [00:25, 38.72iter/s]Best score: 0.1740: : 880iter [00:25, 38.86iter/s]Best score: 0.1740: : 880iter [00:25, 38.86iter/s]Best score: 0.1740: : 881iter [00:25, 38.86iter/s]Best score: 0.1740: : 882iter [00:25, 38.86iter/s]Best score: 0.1740: : 883iter [00:25, 38.86iter/s]Best score: 0.1740: : 884iter [00:25, 38.86iter/s]Best score: 0.1740: : 885iter [00:25, 39.43iter/s]Best score: 0.1740: : 885iter [00:25, 39.43iter/s]Best score: 0.1740: : 886iter [00:25, 39.43iter/s]Best score: 0.1740: : 887iter [00:25, 39.43iter/s]Best score: 0.1740: : 888iter [00:25, 39.43iter/s]Best score: 0.1734: : 889iter [00:25, 39.43iter/s]Best score: 0.1734: : 890iter [00:25, 39.36iter/s]Best score: 0.1734: : 890iter [00:25, 39.36iter/s]Best score: 0.1734: : 891iter [00:25, 39.36iter/s]Best score: 0.1734: : 892iter [00:25, 39.36iter/s]Best score: 0.1734: : 893iter [00:25, 39.36iter/s]Best score: 0.1734: : 894iter [00:25, 39.36iter/s]Best score: 0.1734: : 895iter [00:25, 39.59iter/s]Best score: 0.1734: : 895iter [00:25, 39.59iter/s]Best score: 0.1734: : 896iter [00:25, 39.59iter/s]Best score: 0.1734: : 897iter [00:25, 39.59iter/s]Best score: 0.1734: : 898iter [00:25, 39.59iter/s]
[ITER 900] Best: 0.1734
[PARAMS] Current best parameters:
  fx: 519.8238
  fy: 519.4404
  px: 1026.3142
  py: 753.9713
  k1: -0.00647316
  k2: 0.02563104
  k3: -0.01188226
  k4: 0.00110542
  p1: -0.00010054
  p2: 0.01253320
  p3: 0.00680381
  p4: -0.00124530
  s1: -0.0230
  s2: 0.0023
  s3: -0.0125
  s4: 0.0016
  tilt_x: -0.0224
  tilt_y: 0.0332
  scale: 3.0231
  rotation: 0.0025
Best score: 0.1734: : 899iter [00:25, 39.59iter/s]Best score: 0.1734: : 900iter [00:25, 39.50iter/s]Best score: 0.1734: : 900iter [00:26, 39.50iter/s]Best score: 0.1734: : 901iter [00:26, 39.50iter/s]Best score: 0.1734: : 902iter [00:26, 39.50iter/s]Best score: 0.1734: : 903iter [00:26, 39.50iter/s]Best score: 0.1734: : 904iter [00:26, 32.96iter/s]Best score: 0.1734: : 904iter [00:26, 32.96iter/s]Best score: 0.1734: : 905iter [00:26, 32.96iter/s]Best score: 0.1734: : 906iter [00:26, 32.96iter/s]Best score: 0.1734: : 907iter [00:26, 32.96iter/s]Best score: 0.1734: : 908iter [00:26, 32.96iter/s]Best score: 0.1734: : 909iter [00:26, 34.95iter/s]Best score: 0.1734: : 909iter [00:26, 34.95iter/s]Best score: 0.1734: : 910iter [00:26, 34.95iter/s]Best score: 0.1734: : 911iter [00:26, 34.95iter/s]Best score: 0.1734: : 912iter [00:26, 34.95iter/s]Best score: 0.1734: : 913iter [00:26, 35.96iter/s]Best score: 0.1734: : 913iter [00:26, 35.96iter/s]Best score: 0.1734: : 914iter [00:26, 35.96iter/s]Best score: 0.1734: : 915iter [00:26, 35.96iter/s]Best score: 0.1734: : 916iter [00:26, 35.96iter/s]Best score: 0.1734: : 917iter [00:26, 35.96iter/s]Best score: 0.1734: : 918iter [00:26, 37.23iter/s]Best score: 0.1734: : 918iter [00:26, 37.23iter/s]Best score: 0.1734: : 919iter [00:26, 37.23iter/s]Best score: 0.1734: : 920iter [00:26, 37.23iter/s]Best score: 0.1734: : 921iter [00:26, 37.23iter/s]Best score: 0.1734: : 922iter [00:26, 37.87iter/s]Best score: 0.1734: : 922iter [00:26, 37.87iter/s]Best score: 0.1734: : 923iter [00:26, 37.87iter/s]Best score: 0.1734: : 924iter [00:26, 37.87iter/s]Best score: 0.1734: : 925iter [00:26, 37.87iter/s]Best score: 0.1734: : 926iter [00:26, 38.44iter/s]Best score: 0.1734: : 926iter [00:26, 38.44iter/s]Best score: 0.1734: : 927iter [00:26, 38.44iter/s]Best score: 0.1734: : 928iter [00:26, 38.44iter/s]Best score: 0.1728: : 929iter [00:26, 38.44iter/s]Best score: 0.1728: : 930iter [00:26, 38.76iter/s]Best score: 0.1728: : 930iter [00:26, 38.76iter/s]Best score: 0.1728: : 931iter [00:26, 38.76iter/s]Best score: 0.1728: : 932iter [00:26, 38.76iter/s]Best score: 0.1728: : 933iter [00:26, 38.76iter/s]Best score: 0.1728: : 934iter [00:26, 39.10iter/s]Best score: 0.1728: : 934iter [00:26, 39.10iter/s]Best score: 0.1728: : 935iter [00:26, 39.10iter/s]Best score: 0.1728: : 936iter [00:26, 39.10iter/s]Best score: 0.1728: : 937iter [00:26, 39.10iter/s]Best score: 0.1728: : 938iter [00:27, 39.10iter/s]Best score: 0.1728: : 939iter [00:27, 39.42iter/s]Best score: 0.1727: : 939iter [00:27, 39.42iter/s]Best score: 0.1727: : 940iter [00:27, 39.42iter/s]Best score: 0.1727: : 941iter [00:27, 39.42iter/s]Best score: 0.1727: : 942iter [00:27, 39.42iter/s]Best score: 0.1727: : 943iter [00:27, 39.50iter/s]Best score: 0.1727: : 943iter [00:27, 39.50iter/s]Best score: 0.1727: : 944iter [00:27, 39.50iter/s]Best score: 0.1727: : 945iter [00:27, 39.50iter/s]Best score: 0.1727: : 946iter [00:27, 39.50iter/s]Best score: 0.1727: : 947iter [00:27, 39.50iter/s]Best score: 0.1727: : 948iter [00:27, 39.75iter/s]Best score: 0.1727: : 948iter [00:27, 39.75iter/s]
[ITER 950] Best: 0.1727
[PARAMS] Current best parameters:
  fx: 520.7511
  fy: 520.3536
  px: 1026.4482
  py: 753.9385
  k1: -0.00764343
  k2: 0.02485816
  k3: -0.01083329
  k4: 0.00081282
  p1: -0.00009988
  p2: 0.01277927
  p3: 0.00585950
  p4: -0.00153440
  s1: -0.0222
  s2: 0.0026
  s3: -0.0115
  s4: 0.0018
  tilt_x: -0.0226
  tilt_y: 0.0331
  scale: 3.0246
  rotation: 0.0069
Best score: 0.1727: : 949iter [00:27, 39.75iter/s]Best score: 0.1727: : 950iter [00:27, 39.75iter/s]Best score: 0.1727: : 951iter [00:27, 39.75iter/s]Best score: 0.1727: : 952iter [00:27, 32.56iter/s]Best score: 0.1727: : 952iter [00:27, 32.56iter/s]Best score: 0.1727: : 953iter [00:27, 32.56iter/s]Best score: 0.1727: : 954iter [00:27, 32.56iter/s]Best score: 0.1727: : 955iter [00:27, 32.56iter/s]Best score: 0.1727: : 956iter [00:27, 34.36iter/s]Best score: 0.1727: : 956iter [00:27, 34.36iter/s]Best score: 0.1727: : 957iter [00:27, 34.36iter/s]Best score: 0.1727: : 958iter [00:27, 34.36iter/s]Best score: 0.1726: : 959iter [00:27, 34.36iter/s]Best score: 0.1726: : 960iter [00:27, 35.59iter/s]Best score: 0.1726: : 960iter [00:27, 35.59iter/s]Best score: 0.1726: : 961iter [00:27, 35.59iter/s]Best score: 0.1726: : 962iter [00:27, 35.59iter/s]Best score: 0.1726: : 963iter [00:27, 35.59iter/s]Best score: 0.1726: : 964iter [00:27, 36.56iter/s]Best score: 0.1726: : 964iter [00:27, 36.56iter/s]Best score: 0.1726: : 965iter [00:27, 36.56iter/s]Best score: 0.1726: : 966iter [00:27, 36.56iter/s]Best score: 0.1726: : 967iter [00:27, 36.56iter/s]Best score: 0.1726: : 968iter [00:27, 37.45iter/s]Best score: 0.1726: : 968iter [00:27, 37.45iter/s]Best score: 0.1725: : 969iter [00:27, 37.45iter/s]Best score: 0.1725: : 970iter [00:27, 37.45iter/s]Best score: 0.1725: : 971iter [00:27, 37.45iter/s]Best score: 0.1725: : 972iter [00:27, 37.92iter/s]Best score: 0.1725: : 972iter [00:27, 37.92iter/s]Best score: 0.1725: : 973iter [00:27, 37.92iter/s]Best score: 0.1725: : 974iter [00:28, 37.92iter/s]Best score: 0.1725: : 975iter [00:28, 37.92iter/s]Best score: 0.1725: : 976iter [00:28, 37.92iter/s]Best score: 0.1725: : 977iter [00:28, 38.64iter/s]Best score: 0.1725: : 977iter [00:28, 38.64iter/s]Best score: 0.1725: : 978iter [00:28, 38.64iter/s]Best score: 0.1725: : 979iter [00:28, 38.64iter/s]Best score: 0.1725: : 980iter [00:28, 38.64iter/s]Best score: 0.1725: : 981iter [00:28, 38.92iter/s]Best score: 0.1725: : 981iter [00:28, 38.92iter/s]Best score: 0.1725: : 982iter [00:28, 38.92iter/s]Best score: 0.1725: : 983iter [00:28, 38.92iter/s]Best score: 0.1725: : 984iter [00:28, 38.92iter/s]Best score: 0.1725: : 985iter [00:28, 38.92iter/s]Best score: 0.1725: : 986iter [00:28, 39.50iter/s]Best score: 0.1725: : 986iter [00:28, 39.50iter/s]Best score: 0.1725: : 987iter [00:28, 39.50iter/s]Best score: 0.1725: : 988iter [00:28, 39.50iter/s]Best score: 0.1721: : 989iter [00:28, 39.50iter/s]Best score: 0.1721: : 990iter [00:28, 39.50iter/s]Best score: 0.1721: : 990iter [00:28, 39.50iter/s]Best score: 0.1721: : 991iter [00:28, 39.50iter/s]Best score: 0.1721: : 992iter [00:28, 39.50iter/s]Best score: 0.1721: : 993iter [00:28, 39.50iter/s]Best score: 0.1721: : 994iter [00:28, 39.50iter/s]Best score: 0.1721: : 995iter [00:28, 39.70iter/s]Best score: 0.1721: : 995iter [00:28, 39.70iter/s]Best score: 0.1721: : 996iter [00:28, 39.70iter/s]Best score: 0.1721: : 997iter [00:28, 39.70iter/s]Best score: 0.1721: : 998iter [00:28, 39.70iter/s]
[ITER 1000] Best: 0.1721
[PARAMS] Current best parameters:
  fx: 520.4801
  fy: 520.0869
  px: 1026.3928
  py: 753.8649
  k1: -0.00820419
  k2: 0.02649073
  k3: -0.01194424
  k4: 0.00106127
  p1: 0.00007670
  p2: 0.01263565
  p3: 0.00635583
  p4: -0.00150809
  s1: -0.0223
  s2: 0.0024
  s3: -0.0121
  s4: 0.0017
  tilt_x: -0.0234
  tilt_y: 0.0330
  scale: 3.0251
  rotation: 0.0056
Best score: 0.1721: : 999iter [00:28, 39.70iter/s]Best score: 0.1721: : 1000iter [00:28, 39.59iter/s]Best score: 0.1721: : 1000iter [00:28, 39.59iter/s]Best score: 0.1721: : 1001iter [00:28, 39.59iter/s]Best score: 0.1721: : 1002iter [00:28, 39.59iter/s]Best score: 0.1721: : 1003iter [00:28, 39.59iter/s]Best score: 0.1721: : 1004iter [00:28, 32.94iter/s]Best score: 0.1721: : 1004iter [00:28, 32.94iter/s]Best score: 0.1721: : 1005iter [00:28, 32.94iter/s]Best score: 0.1721: : 1006iter [00:28, 32.94iter/s]Best score: 0.1721: : 1007iter [00:28, 32.94iter/s]Best score: 0.1721: : 1008iter [00:28, 32.94iter/s]Best score: 0.1721: : 1009iter [00:28, 35.11iter/s]Best score: 0.1721: : 1009iter [00:28, 35.11iter/s]Best score: 0.1721: : 1010iter [00:28, 35.11iter/s]Best score: 0.1721: : 1011iter [00:29, 35.11iter/s]Best score: 0.1721: : 1012iter [00:29, 35.11iter/s]Best score: 0.1721: : 1013iter [00:29, 36.23iter/s]Best score: 0.1721: : 1013iter [00:29, 36.23iter/s]Best score: 0.1721: : 1014iter [00:29, 36.23iter/s]Best score: 0.1721: : 1015iter [00:29, 36.23iter/s]Best score: 0.1721: : 1016iter [00:29, 36.23iter/s]Best score: 0.1721: : 1017iter [00:29, 36.23iter/s]Best score: 0.1721: : 1018iter [00:29, 37.51iter/s]Best score: 0.1721: : 1018iter [00:29, 37.51iter/s]Best score: 0.1720: : 1019iter [00:29, 37.51iter/s]Best score: 0.1720: : 1020iter [00:29, 37.51iter/s]Best score: 0.1720: : 1021iter [00:29, 37.51iter/s]Best score: 0.1720: : 1022iter [00:29, 38.06iter/s]Best score: 0.1720: : 1022iter [00:29, 38.06iter/s]Best score: 0.1720: : 1023iter [00:29, 38.06iter/s]Best score: 0.1720: : 1024iter [00:29, 38.06iter/s]Best score: 0.1720: : 1025iter [00:29, 38.06iter/s]Best score: 0.1720: : 1026iter [00:29, 38.06iter/s]Best score: 0.1720: : 1027iter [00:29, 38.82iter/s]Best score: 0.1720: : 1027iter [00:29, 38.82iter/s]Best score: 0.1720: : 1028iter [00:29, 38.82iter/s]Best score: 0.1720: : 1029iter [00:29, 38.82iter/s]Best score: 0.1720: : 1030iter [00:29, 38.82iter/s]Best score: 0.1720: : 1031iter [00:29, 39.04iter/s]Best score: 0.1720: : 1031iter [00:29, 39.04iter/s]Best score: 0.1720: : 1032iter [00:29, 39.04iter/s]Best score: 0.1720: : 1033iter [00:29, 39.04iter/s]Best score: 0.1720: : 1034iter [00:29, 39.04iter/s]Best score: 0.1720: : 1035iter [00:29, 30.76iter/s]Best score: 0.1720: : 1035iter [00:29, 30.76iter/s]Best score: 0.1720: : 1036iter [00:29, 30.76iter/s]Best score: 0.1720: : 1037iter [00:29, 30.76iter/s]Best score: 0.1720: : 1038iter [00:29, 30.76iter/s]Best score: 0.1720: : 1039iter [00:29, 32.89iter/s]Best score: 0.1720: : 1039iter [00:29, 32.89iter/s]Best score: 0.1720: : 1040iter [00:29, 32.89iter/s]Best score: 0.1720: : 1041iter [00:29, 32.89iter/s]Best score: 0.1720: : 1042iter [00:29, 32.89iter/s]Best score: 0.1720: : 1043iter [00:29, 34.49iter/s]Best score: 0.1720: : 1043iter [00:29, 34.49iter/s]Best score: 0.1720: : 1044iter [00:29, 34.49iter/s]Best score: 0.1720: : 1045iter [00:29, 34.49iter/s]Best score: 0.1720: : 1046iter [00:29, 34.49iter/s]Best score: 0.1720: : 1047iter [00:30, 34.49iter/s]Best score: 0.1720: : 1048iter [00:30, 36.30iter/s]Best score: 0.1720: : 1048iter [00:30, 36.30iter/s]
[ITER 1050] Best: 0.1720
[PARAMS] Current best parameters:
  fx: 520.3891
  fy: 520.0076
  px: 1026.2840
  py: 753.9359
  k1: -0.00844711
  k2: 0.02673332
  k3: -0.01200791
  k4: 0.00106983
  p1: 0.00007240
  p2: 0.01293497
  p3: 0.00675716
  p4: -0.00171142
  s1: -0.0231
  s2: 0.0027
  s3: -0.0123
  s4: 0.0019
  tilt_x: -0.0230
  tilt_y: 0.0342
  scale: 3.0263
  rotation: 0.0071
Best score: 0.1720: : 1049iter [00:30, 36.30iter/s]Best score: 0.1720: : 1050iter [00:30, 36.30iter/s]Best score: 0.1720: : 1051iter [00:30, 36.30iter/s]Best score: 0.1720: : 1052iter [00:30, 30.91iter/s]Best score: 0.1720: : 1052iter [00:30, 30.91iter/s]Best score: 0.1720: : 1053iter [00:30, 30.91iter/s]Best score: 0.1720: : 1054iter [00:30, 30.91iter/s]Best score: 0.1720: : 1055iter [00:30, 30.91iter/s]Best score: 0.1720: : 1056iter [00:30, 30.91iter/s]Best score: 0.1720: : 1057iter [00:30, 33.51iter/s]Best score: 0.1720: : 1057iter [00:30, 33.51iter/s]Best score: 0.1720: : 1058iter [00:30, 33.51iter/s]Best score: 0.1720: : 1059iter [00:30, 33.51iter/s]Best score: 0.1720: : 1060iter [00:30, 33.51iter/s]Best score: 0.1720: : 1061iter [00:30, 34.82iter/s]Best score: 0.1720: : 1061iter [00:30, 34.82iter/s]Best score: 0.1720: : 1062iter [00:30, 34.82iter/s]Best score: 0.1720: : 1063iter [00:30, 34.82iter/s]Best score: 0.1720: : 1064iter [00:30, 34.82iter/s]Best score: 0.1720: : 1065iter [00:30, 34.82iter/s]Best score: 0.1720: : 1066iter [00:30, 36.43iter/s]Best score: 0.1720: : 1066iter [00:30, 36.43iter/s]Best score: 0.1720: : 1067iter [00:30, 36.43iter/s]Best score: 0.1720: : 1068iter [00:30, 36.43iter/s]Best score: 0.1719: : 1069iter [00:30, 36.43iter/s]Best score: 0.1719: : 1070iter [00:30, 37.24iter/s]Best score: 0.1719: : 1070iter [00:30, 37.24iter/s]Best score: 0.1719: : 1071iter [00:30, 37.24iter/s]Best score: 0.1719: : 1072iter [00:30, 37.24iter/s]Best score: 0.1719: : 1073iter [00:30, 37.24iter/s]Best score: 0.1719: : 1074iter [00:30, 37.24iter/s]Best score: 0.1719: : 1075iter [00:30, 38.22iter/s]Best score: 0.1719: : 1075iter [00:30, 38.22iter/s]Best score: 0.1719: : 1076iter [00:30, 38.22iter/s]Best score: 0.1719: : 1077iter [00:30, 38.22iter/s]Best score: 0.1719: : 1078iter [00:30, 38.22iter/s]Best score: 0.1719: : 1079iter [00:30, 38.22iter/s]Best score: 0.1719: : 1080iter [00:30, 38.63iter/s]Best score: 0.1719: : 1080iter [00:30, 38.63iter/s]Best score: 0.1719: : 1081iter [00:30, 38.63iter/s]Best score: 0.1719: : 1082iter [00:30, 38.63iter/s]Best score: 0.1719: : 1083iter [00:30, 38.63iter/s]Best score: 0.1719: : 1084iter [00:31, 38.63iter/s]Best score: 0.1719: : 1085iter [00:31, 39.19iter/s]Best score: 0.1719: : 1085iter [00:31, 39.19iter/s]Best score: 0.1719: : 1086iter [00:31, 39.19iter/s]Best score: 0.1719: : 1087iter [00:31, 39.19iter/s]Best score: 0.1719: : 1088iter [00:31, 39.19iter/s]Best score: 0.1719: : 1089iter [00:31, 39.19iter/s]Best score: 0.1719: : 1090iter [00:31, 39.21iter/s]Best score: 0.1719: : 1090iter [00:31, 39.21iter/s]Best score: 0.1719: : 1091iter [00:31, 39.21iter/s]Best score: 0.1719: : 1092iter [00:31, 39.21iter/s]Best score: 0.1719: : 1093iter [00:31, 39.21iter/s]Best score: 0.1719: : 1094iter [00:31, 39.21iter/s]Best score: 0.1719: : 1095iter [00:31, 39.57iter/s]Best score: 0.1719: : 1095iter [00:31, 39.57iter/s]Best score: 0.1719: : 1096iter [00:31, 39.57iter/s]Best score: 0.1719: : 1097iter [00:31, 39.57iter/s]Best score: 0.1719: : 1098iter [00:31, 39.57iter/s]
[ITER 1100] Best: 0.1717
[PARAMS] Current best parameters:
  fx: 520.5347
  fy: 520.1330
  px: 1026.3568
  py: 753.9611
  k1: -0.01118239
  k2: 0.02997360
  k3: -0.01339824
  k4: 0.00127469
  p1: -0.00012865
  p2: 0.01251701
  p3: 0.00626452
  p4: -0.00139199
  s1: -0.0222
  s2: 0.0024
  s3: -0.0116
  s4: 0.0015
  tilt_x: -0.0224
  tilt_y: 0.0330
  scale: 3.0294
  rotation: 0.0078
Best score: 0.1717: : 1099iter [00:31, 39.57iter/s]Best score: 0.1717: : 1100iter [00:31, 39.36iter/s]Best score: 0.1717: : 1100iter [00:31, 34.96iter/s]

[📈] Running L-BFGS-B polish after 1100 DE iterations...
  Polish improved score: 0.171724 -> 0.171713

[⭕] Ring refinement pass (3500mm diameter)...
  Points: 25,950 → 25,950 within 3500mm ring
  Ring polish improved score: 0.171713 -> 0.171588
  Success: True
  Tangential distortion: p1=-0.000131, p2=0.012516, p3=0.006263, p4=-0.001392
  ✓ Tangential correction is significant for corner improvement
[✅] Square reference optimization complete. Score: 0.1716
[✅] Parameters copied to: /working/MDC021_W042_2026-09-09/calibration/params.json
[📌] Selecting best parameters...
[✅] Saved final refined parameters.


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


[DEBUG] Parameters being applied to PTD conversion:
    fx: 520.5346636436414
    fy: 520.1329706715834
    px: 1026.356792912945
    py: 753.9611062055194
    k1: -0.011181574707364314
    k2: 0.029974249973293426
    k3: -0.013398119540408536
    k4: 0.0012743105913651915
    p1: -0.00013114175541921062
    p2: 0.012515933137175018
    p3: 0.006263139094613596
    p4: -0.0013918448637827545
    scale: 3.0293638333630217
    rotation: 0.007775193646056353
    mmpp: 1.2738296388917667

[🔄] Converting 1283 frames to PTD, creating debug images for 200 calibration frames...
📁 Rigs:   0%|          | 0/2 [00:00<?, ?rig/s]
   🔄 1000:   0%|          | 0/574 [00:00<?, ?frame/s][A
   🔄 1000:   3%|▎         | 19/574 [00:00<00:03, 179.85frame/s][A
   🔄 1000:   6%|▋         | 37/574 [00:00<00:03, 176.27frame/s][A
   🔄 1000:  10%|▉         | 55/574 [00:00<00:02, 176.15frame/s][A
   🔄 1000:  13%|█▎        | 73/574 [00:00<00:02, 177.03frame/s][A
   🔄 1000:  16%|█▌        | 91/574 [00:00<00:02, 177.41frame/s][A
   🔄 1000:  19%|█▉        | 109/574 [00:00<00:02, 177.67frame/s][A
   🔄 1000:  22%|██▏       | 127/574 [00:00<00:02, 177.71frame/s][A
   🔄 1000:  25%|██▌       | 145/574 [00:00<00:02, 177.97frame/s][A
   🔄 1000:  28%|██▊       | 163/574 [00:00<00:02, 177.69frame/s][A
   🔄 1000:  32%|███▏      | 181/574 [00:01<00:02, 177.40frame/s][A
   🔄 1000:  35%|███▍      | 199/574 [00:01<00:02, 177.31frame/s][A
   🔄 1000:  38%|███▊      | 217/574 [00:01<00:02, 176.49frame/s][A
   🔄 1000:  41%|████      | 235/574 [00:01<00:01, 175.44frame/s][A
   🔄 1000:  44%|████▍     | 253/574 [00:01<00:01, 174.90frame/s][A
   🔄 1000:  47%|████▋     | 271/574 [00:01<00:01, 174.51frame/s][A
   🔄 1000:  50%|█████     | 289/574 [00:01<00:01, 173.54frame/s][A
   🔄 1000:  53%|█████▎    | 307/574 [00:01<00:01, 173.47frame/s][A
   🔄 1000:  57%|█████▋    | 325/574 [00:01<00:01, 173.56frame/s][A
   🔄 1000:  60%|█████▉    | 343/574 [00:01<00:01, 173.65frame/s][A
   🔄 1000:  63%|██████▎   | 361/574 [00:02<00:01, 173.52frame/s][A
   🔄 1000:  66%|██████▌   | 379/574 [00:02<00:01, 173.57frame/s][A
   🔄 1000:  69%|██████▉   | 397/574 [00:02<00:01, 173.90frame/s][A
   🔄 1000:  72%|███████▏  | 415/574 [00:02<00:00, 174.81frame/s][A
   🔄 1000:  75%|███████▌  | 433/574 [00:02<00:00, 175.71frame/s][A
   🔄 1000:  79%|███████▊  | 451/574 [00:02<00:00, 176.27frame/s][A
   🔄 1000:  82%|████████▏ | 469/574 [00:02<00:00, 176.79frame/s][A
   🔄 1000:  85%|████████▍ | 487/574 [00:02<00:00, 177.15frame/s][A
   🔄 1000:  88%|████████▊ | 505/574 [00:02<00:00, 177.36frame/s][A
   🔄 1000:  91%|█████████ | 523/574 [00:02<00:00, 177.46frame/s][A
   🔄 1000:  94%|█████████▍| 541/574 [00:03<00:00, 177.24frame/s][A
   🔄 1000:  97%|█████████▋| 559/574 [00:03<00:00, 176.93frame/s][A
                                                                 [A📁 Rigs:  50%|█████     | 1/2 [00:05<00:05,  5.95s/rig]
   🔄 500:   0%|          | 0/709 [00:00<?, ?frame/s][A
   🔄 500:   3%|▎         | 18/709 [00:00<00:03, 175.84frame/s][A
   🔄 500:   5%|▌         | 36/709 [00:00<00:03, 176.17frame/s][A
   🔄 500:   8%|▊         | 54/709 [00:00<00:03, 176.71frame/s][A
   🔄 500:  10%|█         | 72/709 [00:00<00:03, 177.24frame/s][A
   🔄 500:  13%|█▎        | 90/709 [00:00<00:03, 177.59frame/s][A
   🔄 500:  15%|█▌        | 108/709 [00:00<00:03, 177.68frame/s][A
   🔄 500:  18%|█▊        | 126/709 [00:00<00:03, 177.70frame/s][A
   🔄 500:  20%|██        | 144/709 [00:00<00:03, 177.67frame/s][A
   🔄 500:  23%|██▎       | 162/709 [00:00<00:03, 177.70frame/s][A
   🔄 500:  25%|██▌       | 180/709 [00:01<00:02, 177.82frame/s][A
   🔄 500:  28%|██▊       | 198/709 [00:01<00:02, 176.87frame/s][A
   🔄 500:  30%|███       | 216/709 [00:01<00:02, 175.97frame/s][A
   🔄 500:  33%|███▎      | 234/709 [00:01<00:02, 175.59frame/s][A
   🔄 500:  36%|███▌      | 252/709 [00:01<00:02, 175.77frame/s][A
   🔄 500:  38%|███▊      | 270/709 [00:01<00:02, 176.83frame/s][A
   🔄 500:  41%|████      | 289/709 [00:01<00:02, 177.81frame/s][A
   🔄 500:  43%|████▎     | 308/709 [00:01<00:02, 178.52frame/s][A
   🔄 500:  46%|████▌     | 327/709 [00:01<00:02, 179.47frame/s][A
   🔄 500:  49%|████▊     | 345/709 [00:01<00:02, 179.50frame/s][A
   🔄 500:  51%|█████     | 363/709 [00:02<00:01, 179.06frame/s][A
   🔄 500:  54%|█████▎    | 381/709 [00:02<00:01, 178.41frame/s][A
   🔄 500:  56%|█████▋    | 399/709 [00:02<00:01, 177.62frame/s][A
   🔄 500:  59%|█████▉    | 417/709 [00:02<00:01, 176.59frame/s][A
   🔄 500:  61%|██████▏   | 435/709 [00:02<00:01, 175.93frame/s][A
   🔄 500:  64%|██████▍   | 453/709 [00:02<00:01, 175.66frame/s][A
   🔄 500:  66%|██████▋   | 471/709 [00:02<00:01, 175.48frame/s][A
   🔄 500:  69%|██████▉   | 489/709 [00:02<00:01, 175.23frame/s][A
   🔄 500:  72%|███████▏  | 507/709 [00:02<00:01, 175.40frame/s][A
   🔄 500:  74%|███████▍  | 525/709 [00:02<00:01, 175.66frame/s][A
   🔄 500:  77%|███████▋  | 543/709 [00:03<00:00, 175.87frame/s][A
   🔄 500:  79%|███████▉  | 561/709 [00:03<00:00, 175.94frame/s][A
   🔄 500:  82%|████████▏ | 579/709 [00:03<00:00, 175.97frame/s][A
   🔄 500:  84%|████████▍ | 597/709 [00:03<00:00, 175.99frame/s][A
   🔄 500:  87%|████████▋ | 615/709 [00:03<00:00, 175.91frame/s][A
   🔄 500:  89%|████████▉ | 633/709 [00:03<00:00, 175.51frame/s][A
   🔄 500:  92%|█████████▏| 651/709 [00:03<00:00, 175.29frame/s][A
   🔄 500:  94%|█████████▍| 669/709 [00:03<00:00, 174.89frame/s][A
   🔄 500:  97%|█████████▋| 687/709 [00:03<00:00, 174.65frame/s][A
   🔄 500:  99%|█████████▉| 705/709 [00:03<00:00, 174.55frame/s][A
                                                                [A📁 Rigs: 100%|██████████| 2/2 [00:13<00:00,  6.70s/rig]📁 Rigs: 100%|██████████| 2/2 [00:13<00:00,  6.59s/rig]
[✅] Saved PTDs: /working/MDC021_W042_2026-09-09/calibration/debug/4_undistorted/output/ptd
📁 Rigs:   0%|          | 0/2 [00:00<?, ?rig/s]
   🔄 1000:   0%|          | 0/100 [00:00<?, ?frame/s][A
   🔄 1000:  18%|█▊        | 18/100 [00:00<00:00, 174.68frame/s][A
   🔄 1000:  36%|███▌      | 36/100 [00:00<00:00, 175.66frame/s][A
   🔄 1000:  54%|█████▍    | 54/100 [00:00<00:00, 174.13frame/s][A
   🔄 1000:  72%|███████▏  | 72/100 [00:00<00:00, 173.44frame/s][A
   🔄 1000:  90%|█████████ | 90/100 [00:00<00:00, 174.84frame/s][A
                                                                [A📁 Rigs:  50%|█████     | 1/2 [00:00<00:00,  1.08rig/s]
   🔄 500:   0%|          | 0/100 [00:00<?, ?frame/s][A
   🔄 500:  18%|█▊        | 18/100 [00:00<00:00, 175.64frame/s][A
   🔄 500:  36%|███▌      | 36/100 [00:00<00:00, 174.87frame/s][A
   🔄 500:  54%|█████▍    | 54/100 [00:00<00:00, 175.69frame/s][A
   🔄 500:  72%|███████▏  | 72/100 [00:00<00:00, 174.23frame/s][A
   🔄 500:  90%|█████████ | 90/100 [00:00<00:00, 174.65frame/s][A
                                                               [A📁 Rigs: 100%|██████████| 2/2 [00:01<00:00,  1.00s/rig]📁 Rigs: 100%|██████████| 2/2 [00:01<00:00,  1.01rig/s]
[✅] Saved PTDs: /working/MDC021_W042_2026-09-09/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%|▎         | 79391/3080448 [00:00<00:03, 793901.29px/s]📤 Writing LUT:   5%|▌         | 167333/3080448 [00:00<00:03, 844200.74px/s]📤 Writing LUT:   8%|▊         | 256115/3080448 [00:00<00:03, 864116.59px/s]📤 Writing LUT:  11%|█▏        | 346681/3080448 [00:00<00:03, 880516.89px/s]📤 Writing LUT:  14%|█▍        | 436469/3080448 [00:00<00:02, 886776.15px/s]📤 Writing LUT:  17%|█▋        | 526438/3080448 [00:00<00:02, 891164.25px/s]📤 Writing LUT:  20%|██        | 616142/3080448 [00:00<00:02, 893083.35px/s]📤 Writing LUT:  23%|██▎       | 705890/3080448 [00:00<00:02, 894482.62px/s]📤 Writing LUT:  26%|██▌       | 795339/3080448 [00:00<00:02, 891119.14px/s]📤 Writing LUT:  29%|██▊       | 884454/3080448 [00:01<00:02, 887403.81px/s]📤 Writing LUT:  32%|███▏      | 973754/3080448 [00:01<00:02, 889106.78px/s]📤 Writing LUT:  35%|███▍      | 1063056/3080448 [00:01<00:02, 890289.71px/s]📤 Writing LUT:  37%|███▋      | 1154098/3080448 [00:01<00:02, 896371.56px/s]📤 Writing LUT:  40%|████      | 1244952/3080448 [00:01<00:02, 900038.15px/s]📤 Writing LUT:  43%|████▎     | 1335428/3080448 [00:01<00:01, 901456.89px/s]📤 Writing LUT:  46%|████▋     | 1425576/3080448 [00:01<00:01, 898368.08px/s]📤 Writing LUT:  49%|████▉     | 1515417/3080448 [00:01<00:01, 891158.54px/s]📤 Writing LUT:  52%|█████▏    | 1604547/3080448 [00:01<00:01, 888439.63px/s]📤 Writing LUT:  55%|█████▍    | 1693401/3080448 [00:01<00:01, 888248.86px/s]📤 Writing LUT:  58%|█████▊    | 1783260/3080448 [00:02<00:01, 891334.39px/s]📤 Writing LUT:  61%|██████    | 1874067/3080448 [00:02<00:01, 896338.20px/s]📤 Writing LUT:  64%|██████▍   | 1964349/3080448 [00:02<00:01, 898277.24px/s]📤 Writing LUT:  67%|██████▋   | 2056136/3080448 [00:02<00:01, 904143.91px/s]📤 Writing LUT:  70%|██████▉   | 2146555/3080448 [00:02<00:01, 903539.56px/s]📤 Writing LUT:  73%|███████▎  | 2236913/3080448 [00:02<00:00, 903454.48px/s]📤 Writing LUT:  76%|███████▌  | 2327261/3080448 [00:02<00:00, 896051.06px/s]📤 Writing LUT:  78%|███████▊  | 2416881/3080448 [00:02<00:00, 891104.28px/s]📤 Writing LUT:  81%|████████▏ | 2507411/3080448 [00:02<00:00, 895324.28px/s]📤 Writing LUT:  84%|████████▍ | 2597176/3080448 [00:02<00:00, 896014.95px/s]📤 Writing LUT:  87%|████████▋ | 2686788/3080448 [00:03<00:00, 895524.81px/s]📤 Writing LUT:  90%|█████████ | 2778492/3080448 [00:03<00:00, 901956.98px/s]📤 Writing LUT:  93%|█████████▎| 2870215/3080448 [00:03<00:00, 906527.23px/s]📤 Writing LUT:  96%|█████████▌| 2960874/3080448 [00:03<00:00, 905028.83px/s]📤 Writing LUT:  99%|█████████▉| 3052942/3080448 [00:03<00:00, 909712.30px/s]📤 Writing LUT: 100%|██████████| 3080448/3080448 [00:03<00:00, 894626.62px/s]
[✅] LUT written to: /working/MDC021_W042_2026-09-09/calibration/debug/4_undistorted/output/LUT.lut
[WARN] Folder name 'MDC021_W042_2026-09-09' does not match expected pattern MDC042_W007_5_28_2025. Using simple naming convention.
[✅] LUT copied to: /working/MDC021_W042_2026-09-09/calibration/MDC021_W042_2026-09-09_unknown.lut

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

[ℹ️] Detected device type: MD (rigs: [500, 1000]mm)
📁 Rigs (heatmap):   0%|          | 0/2 [00:00<?, ?rig/s]
   🔥 1000:   0%|          | 0/574 [00:00<?, ?frame/s][A
   🔥 1000:   2%|▏         | 9/574 [00:00<00:06, 83.20frame/s][A
   🔥 1000:   3%|▎         | 18/574 [00:00<00:06, 85.68frame/s][A
   🔥 1000:   5%|▍         | 27/574 [00:00<00:06, 86.61frame/s][A
   🔥 1000:   6%|▋         | 36/574 [00:00<00:06, 86.87frame/s][A
   🔥 1000:   8%|▊         | 46/574 [00:00<00:05, 88.16frame/s][A
   🔥 1000:  10%|▉         | 55/574 [00:00<00:05, 88.62frame/s][A
   🔥 1000:  11%|█         | 64/574 [00:00<00:05, 88.25frame/s][A
   🔥 1000:  13%|█▎        | 73/574 [00:00<00:05, 87.90frame/s][A
   🔥 1000:  14%|█▍        | 82/574 [00:00<00:05, 86.79frame/s][A
   🔥 1000:  16%|█▌        | 91/574 [00:01<00:05, 86.42frame/s][A
   🔥 1000:  17%|█▋        | 100/574 [00:01<00:05, 85.94frame/s][A
   🔥 1000:  19%|█▉        | 109/574 [00:01<00:05, 86.42frame/s][A
   🔥 1000:  21%|██        | 118/574 [00:01<00:05, 86.05frame/s][A
   🔥 1000:  22%|██▏       | 127/574 [00:01<00:05, 85.64frame/s][A
   🔥 1000:  24%|██▎       | 136/574 [00:01<00:05, 86.38frame/s][A
   🔥 1000:  25%|██▌       | 145/574 [00:01<00:04, 87.10frame/s][A
   🔥 1000:  27%|██▋       | 155/574 [00:01<00:04, 88.71frame/s][A
   🔥 1000:  29%|██▊       | 165/574 [00:01<00:04, 89.54frame/s][A
   🔥 1000:  30%|███       | 175/574 [00:01<00:04, 89.78frame/s][A
   🔥 1000:  32%|███▏      | 185/574 [00:02<00:04, 89.94frame/s][A
   🔥 1000:  34%|███▍      | 195/574 [00:02<00:04, 89.98frame/s][A
   🔥 1000:  36%|███▌      | 204/574 [00:02<00:04, 89.92frame/s][A
   🔥 1000:  37%|███▋      | 213/574 [00:02<00:04, 89.89frame/s][A
   🔥 1000:  39%|███▊      | 222/574 [00:02<00:03, 89.74frame/s][A
   🔥 1000:  40%|████      | 231/574 [00:02<00:03, 89.01frame/s][A
   🔥 1000:  42%|████▏     | 240/574 [00:02<00:03, 87.94frame/s][A
   🔥 1000:  43%|████▎     | 249/574 [00:02<00:03, 86.23frame/s][A
   🔥 1000:  45%|████▍     | 258/574 [00:02<00:03, 84.11frame/s][A
   🔥 1000:  47%|████▋     | 267/574 [00:03<00:03, 82.74frame/s][A
   🔥 1000:  48%|████▊     | 276/574 [00:03<00:03, 81.71frame/s][A
   🔥 1000:  50%|████▉     | 285/574 [00:03<00:03, 81.14frame/s][A
   🔥 1000:  51%|█████     | 294/574 [00:03<00:03, 80.91frame/s][A
   🔥 1000:  53%|█████▎    | 303/574 [00:03<00:03, 81.73frame/s][A
   🔥 1000:  54%|█████▍    | 312/574 [00:03<00:03, 83.38frame/s][A
   🔥 1000:  56%|█████▌    | 321/574 [00:03<00:02, 84.81frame/s][A
   🔥 1000:  58%|█████▊    | 331/574 [00:03<00:02, 86.51frame/s][A
   🔥 1000:  59%|█████▉    | 341/574 [00:03<00:02, 87.73frame/s][A
   🔥 1000:  61%|██████    | 350/574 [00:04<00:02, 87.42frame/s][A
   🔥 1000:  63%|██████▎   | 359/574 [00:04<00:02, 87.72frame/s][A
   🔥 1000:  64%|██████▍   | 368/574 [00:04<00:02, 88.31frame/s][A
   🔥 1000:  66%|██████▌   | 378/574 [00:04<00:02, 89.04frame/s][A
   🔥 1000:  68%|██████▊   | 388/574 [00:04<00:02, 89.42frame/s][A
   🔥 1000:  69%|██████▉   | 398/574 [00:04<00:01, 89.90frame/s][A
   🔥 1000:  71%|███████   | 408/574 [00:04<00:01, 90.76frame/s][A
   🔥 1000:  73%|███████▎  | 418/574 [00:04<00:01, 90.97frame/s][A
   🔥 1000:  75%|███████▍  | 428/574 [00:04<00:01, 90.63frame/s][A
   🔥 1000:  76%|███████▋  | 438/574 [00:05<00:01, 90.07frame/s][A
   🔥 1000:  78%|███████▊  | 448/574 [00:05<00:01, 90.09frame/s][A
   🔥 1000:  80%|███████▉  | 458/574 [00:05<00:01, 89.49frame/s][A
   🔥 1000:  81%|████████▏ | 467/574 [00:05<00:01, 88.55frame/s][A
   🔥 1000:  83%|████████▎ | 476/574 [00:05<00:01, 88.65frame/s][A
   🔥 1000:  84%|████████▍ | 485/574 [00:05<00:01, 88.94frame/s][A
   🔥 1000:  86%|████████▌ | 494/574 [00:05<00:00, 89.01frame/s][A
   🔥 1000:  88%|████████▊ | 503/574 [00:05<00:00, 89.17frame/s][A
   🔥 1000:  89%|████████▉ | 512/574 [00:05<00:00, 89.06frame/s][A
   🔥 1000:  91%|█████████ | 521/574 [00:05<00:00, 89.20frame/s][A
   🔥 1000:  92%|█████████▏| 530/574 [00:06<00:00, 89.40frame/s][A
   🔥 1000:  94%|█████████▍| 539/574 [00:06<00:00, 89.28frame/s][A
   🔥 1000:  95%|█████████▌| 548/574 [00:06<00:00, 89.09frame/s][A
   🔥 1000:  97%|█████████▋| 557/574 [00:06<00:00, 88.57frame/s][A
   🔥 1000:  99%|█████████▊| 566/574 [00:06<00:00, 88.78frame/s][A
                                                                [A[✅] 1000: /working/MDC021_W042_2026-09-09/calibration/debug/5_heatmap/1000_heatmap.png
[✅] 1000 (fitted): /working/MDC021_W042_2026-09-09/calibration/debug/5_heatmap/1000_heatmap_fitted.png
📁 Rigs (heatmap):  50%|█████     | 1/2 [00:09<00:09,  9.58s/rig]
   🔥 500:   0%|          | 0/709 [00:00<?, ?frame/s][A
   🔥 500:   1%|          | 8/709 [00:00<00:09, 76.77frame/s][A
   🔥 500:   2%|▏         | 17/709 [00:00<00:08, 79.36frame/s][A
   🔥 500:   4%|▎         | 26/709 [00:00<00:08, 80.34frame/s][A
   🔥 500:   5%|▍         | 35/709 [00:00<00:08, 80.69frame/s][A
   🔥 500:   6%|▌         | 44/709 [00:00<00:08, 80.65frame/s][A
   🔥 500:   7%|▋         | 53/709 [00:00<00:08, 80.73frame/s][A
   🔥 500:   9%|▊         | 62/709 [00:00<00:08, 80.20frame/s][A
   🔥 500:  10%|█         | 71/709 [00:00<00:07, 79.87frame/s][A
   🔥 500:  11%|█         | 79/709 [00:00<00:07, 79.79frame/s][A
   🔥 500:  12%|█▏        | 87/709 [00:01<00:07, 79.82frame/s][A
   🔥 500:  14%|█▎        | 96/709 [00:01<00:07, 80.62frame/s][A
   🔥 500:  15%|█▍        | 105/709 [00:01<00:07, 81.11frame/s][A
   🔥 500:  16%|█▌        | 114/709 [00:01<00:07, 80.91frame/s][A
   🔥 500:  17%|█▋        | 123/709 [00:01<00:07, 80.75frame/s][A
   🔥 500:  19%|█▊        | 132/709 [00:01<00:07, 80.96frame/s][A
   🔥 500:  20%|█▉        | 141/709 [00:01<00:06, 81.29frame/s][A
   🔥 500:  21%|██        | 150/709 [00:01<00:06, 82.30frame/s][A
   🔥 500:  22%|██▏       | 159/709 [00:01<00:06, 84.35frame/s][A
   🔥 500:  24%|██▎       | 168/709 [00:02<00:06, 85.65frame/s][A
   🔥 500:  25%|██▍       | 177/709 [00:02<00:06, 85.52frame/s][A
   🔥 500:  26%|██▌       | 186/709 [00:02<00:06, 84.60frame/s][A
   🔥 500:  28%|██▊       | 195/709 [00:02<00:06, 84.41frame/s][A
   🔥 500:  29%|██▉       | 204/709 [00:02<00:06, 83.96frame/s][A
   🔥 500:  30%|███       | 213/709 [00:02<00:05, 83.20frame/s][A
   🔥 500:  31%|███▏      | 222/709 [00:02<00:05, 82.49frame/s][A
   🔥 500:  33%|███▎      | 231/709 [00:02<00:05, 82.43frame/s][A
   🔥 500:  34%|███▍      | 240/709 [00:02<00:05, 81.87frame/s][A
   🔥 500:  35%|███▌      | 249/709 [00:03<00:05, 81.23frame/s][A
   🔥 500:  36%|███▋      | 258/709 [00:03<00:05, 81.29frame/s][A
   🔥 500:  38%|███▊      | 267/709 [00:03<00:05, 82.20frame/s][A
   🔥 500:  39%|███▉      | 276/709 [00:03<00:05, 83.24frame/s][A
   🔥 500:  40%|████      | 285/709 [00:03<00:05, 84.72frame/s][A
   🔥 500:  41%|████▏     | 294/709 [00:03<00:04, 85.06frame/s][A
   🔥 500:  43%|████▎     | 303/709 [00:03<00:04, 84.31frame/s][A
   🔥 500:  44%|████▍     | 312/709 [00:03<00:04, 83.77frame/s][A
   🔥 500:  45%|████▌     | 321/709 [00:03<00:04, 82.95frame/s][A
   🔥 500:  47%|████▋     | 330/709 [00:04<00:04, 81.96frame/s][A
   🔥 500:  48%|████▊     | 339/709 [00:04<00:04, 81.13frame/s][A
   🔥 500:  49%|████▉     | 348/709 [00:04<00:04, 80.65frame/s][A
   🔥 500:  50%|█████     | 357/709 [00:04<00:04, 79.87frame/s][A
   🔥 500:  51%|█████▏    | 365/709 [00:04<00:04, 79.32frame/s][A
   🔥 500:  53%|█████▎    | 374/709 [00:04<00:04, 79.91frame/s][A
   🔥 500:  54%|█████▍    | 383/709 [00:04<00:04, 80.13frame/s][A
   🔥 500:  55%|█████▌    | 392/709 [00:04<00:03, 79.57frame/s][A
   🔥 500:  56%|█████▋    | 400/709 [00:04<00:03, 79.07frame/s][A
   🔥 500:  58%|█████▊    | 408/709 [00:05<00:03, 78.32frame/s][A
   🔥 500:  59%|█████▊    | 416/709 [00:05<00:03, 76.93frame/s][A
   🔥 500:  60%|█████▉    | 424/709 [00:05<00:03, 77.26frame/s][A
   🔥 500:  61%|██████    | 432/709 [00:05<00:03, 77.64frame/s][A
   🔥 500:  62%|██████▏   | 440/709 [00:05<00:03, 77.68frame/s][A
   🔥 500:  63%|██████▎   | 448/709 [00:05<00:03, 77.74frame/s][A
   🔥 500:  64%|██████▍   | 456/709 [00:05<00:03, 78.17frame/s][A
   🔥 500:  65%|██████▌   | 464/709 [00:05<00:03, 77.63frame/s][A
   🔥 500:  67%|██████▋   | 472/709 [00:05<00:03, 76.52frame/s][A
   🔥 500:  68%|██████▊   | 480/709 [00:05<00:02, 76.56frame/s][A
   🔥 500:  69%|██████▉   | 488/709 [00:06<00:02, 76.75frame/s][A
   🔥 500:  70%|██████▉   | 496/709 [00:06<00:02, 76.61frame/s][A
   🔥 500:  71%|███████   | 504/709 [00:06<00:02, 76.51frame/s][A
   🔥 500:  72%|███████▏  | 512/709 [00:06<00:02, 76.27frame/s][A
   🔥 500:  73%|███████▎  | 520/709 [00:06<00:02, 76.45frame/s][A
   🔥 500:  74%|███████▍  | 528/709 [00:06<00:02, 76.46frame/s][A
   🔥 500:  76%|███████▌  | 536/709 [00:06<00:02, 77.38frame/s][A
   🔥 500:  77%|███████▋  | 544/709 [00:06<00:02, 77.64frame/s][A
   🔥 500:  78%|███████▊  | 552/709 [00:06<00:02, 78.10frame/s][A
   🔥 500:  79%|███████▉  | 561/709 [00:06<00:01, 78.90frame/s][A
   🔥 500:  80%|████████  | 570/709 [00:07<00:01, 79.79frame/s][A
   🔥 500:  82%|████████▏ | 579/709 [00:07<00:01, 80.57frame/s][A
   🔥 500:  83%|████████▎ | 588/709 [00:07<00:01, 81.04frame/s][A
   🔥 500:  84%|████████▍ | 597/709 [00:07<00:01, 80.85frame/s][A
   🔥 500:  85%|████████▌ | 606/709 [00:07<00:01, 80.90frame/s][A
   🔥 500:  87%|████████▋ | 615/709 [00:07<00:01, 80.64frame/s][A
   🔥 500:  88%|████████▊ | 624/709 [00:07<00:01, 81.09frame/s][A
   🔥 500:  89%|████████▉ | 633/709 [00:07<00:00, 80.25frame/s][A
   🔥 500:  91%|█████████ | 642/709 [00:07<00:00, 80.00frame/s][A
   🔥 500:  92%|█████████▏| 651/709 [00:08<00:00, 80.13frame/s][A
   🔥 500:  93%|█████████▎| 660/709 [00:08<00:00, 80.02frame/s][A
   🔥 500:  94%|█████████▍| 669/709 [00:08<00:00, 80.03frame/s][A
   🔥 500:  96%|█████████▌| 678/709 [00:08<00:00, 80.90frame/s][A
   🔥 500:  97%|█████████▋| 687/709 [00:08<00:00, 81.52frame/s][A
   🔥 500:  98%|█████████▊| 696/709 [00:08<00:00, 81.65frame/s][A
   🔥 500:  99%|█████████▉| 705/709 [00:08<00:00, 81.74frame/s][A
                                                               [A[✅] 500: /working/MDC021_W042_2026-09-09/calibration/debug/5_heatmap/500_heatmap.png
[✅] 500 (fitted): /working/MDC021_W042_2026-09-09/calibration/debug/5_heatmap/500_heatmap_fitted.png
📁 Rigs (heatmap): 100%|██████████| 2/2 [00:19<00:00,  9.81s/rig]📁 Rigs (heatmap): 100%|██████████| 2/2 [00:19<00:00,  9.78s/rig]
[✅] all_rigs_average.png
[✅] all_rigs_best.png
[✅] all_rigs_average_fitted.png
[✅] all_rigs_best_fitted.png
[✅] Heatmaps saved to: /working/MDC021_W042_2026-09-09/calibration/debug/5_heatmap
[🏁] Finished processing MDC021_W042_2026-09-09


================================================================================================================================
================================================================================================================================