2026-09-03T03:59:26 - INFO: Slick 0.0.8a13

🟢 Starting Calibration Pipeline

=== Processing MDCP3D-SL-013_W046(6) ===
2026-09-03T03:59:26 - INFO: Camera ID: 0F7YM
2026-09-03T03:59:26 - INFO: Wand ID: 00001f0c51aa
2026-09-03T03:59:26 - INFO: Recorded At: 2026-09-02T01:41:02Z

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                        Step 1: Digitization                       
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[🔄] Full PTD mode: Processing ALL images then creating calibration subset
[📸] Digitizing ALL images...
[📸] Full dataset mode: Processing ALL images (no debug visualizations)
[INFO] Found 4 las0.zip files to process

Processing Rigs:   0%|          | 0/4 [00:00<?, ?it/s][INFO] Filtered 236 stationary frames, 328 remain


→ 2000L (328 images) Phase 1:   0%|          | 0/328 [00:00<?, ?it/s]

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→ 2000L (328 images) Phase 1:  33%|███▎      | 107/328 [00:02<00:03, 57.15it/s]

→ 2000L (328 images) Phase 1:  39%|███▉      | 129/328 [00:02<00:02, 79.98it/s]

→ 2000L (328 images) Phase 1:  43%|████▎     | 140/328 [00:02<00:03, 59.82it/s]

→ 2000L (328 images) Phase 1:  49%|████▉     | 161/328 [00:02<00:02, 80.66it/s]

→ 2000L (328 images) Phase 1:  53%|█████▎    | 173/328 [00:03<00:02, 61.40it/s]

→ 2000L (328 images) Phase 1:  59%|█████▊    | 192/328 [00:03<00:01, 80.41it/s]

→ 2000L (328 images) Phase 1:  62%|██████▏   | 204/328 [00:03<00:02, 60.74it/s]

→ 2000L (328 images) Phase 1:  68%|██████▊   | 224/328 [00:03<00:01, 80.51it/s]

→ 2000L (328 images) Phase 1:  72%|███████▏  | 237/328 [00:03<00:01, 61.52it/s]

→ 2000L (328 images) Phase 1:  78%|███████▊  | 256/328 [00:04<00:00, 79.44it/s]

→ 2000L (328 images) Phase 1:  82%|████████▏ | 269/328 [00:04<00:00, 61.96it/s]

→ 2000L (328 images) Phase 1:  88%|████████▊ | 288/328 [00:04<00:00, 79.04it/s]

→ 2000L (328 images) Phase 1:  91%|█████████▏| 300/328 [00:04<00:00, 61.76it/s]

→ 2000L (328 images) Phase 1:  97%|█████████▋| 319/328 [00:04<00:00, 79.66it/s]

                                                                               

→ 2000L Phase 2: corners:   0%|          | 0/327 [00:00<?, ?it/s]

→ 2000L Phase 2: corners:   0%|          | 1/327 [00:00<01:01,  5.29it/s]

→ 2000L Phase 2: corners:   6%|▌         | 18/327 [00:00<00:04, 73.62it/s]

→ 2000L Phase 2: corners:   9%|▉         | 31/327 [00:00<00:03, 94.18it/s]

→ 2000L Phase 2: corners:  13%|█▎        | 43/327 [00:00<00:02, 102.46it/s]

→ 2000L Phase 2: corners:  17%|█▋        | 56/327 [00:00<00:02, 106.21it/s]

→ 2000L Phase 2: corners:  22%|██▏       | 72/327 [00:00<00:02, 121.29it/s]

→ 2000L Phase 2: corners:  26%|██▌       | 85/327 [00:00<00:02, 113.69it/s]

→ 2000L Phase 2: corners:  30%|██▉       | 97/327 [00:00<00:02, 113.65it/s]

→ 2000L Phase 2: corners:  34%|███▎      | 110/327 [00:01<00:01, 115.27it/s]

→ 2000L Phase 2: corners:  38%|███▊      | 123/327 [00:01<00:01, 112.84it/s]

→ 2000L Phase 2: corners:  41%|████▏     | 135/327 [00:01<00:01, 113.41it/s]

→ 2000L Phase 2: corners:  46%|████▌     | 149/327 [00:01<00:01, 117.21it/s]

→ 2000L Phase 2: corners:  51%|█████     | 166/327 [00:01<00:01, 131.14it/s]

→ 2000L Phase 2: corners:  56%|█████▌    | 183/327 [00:01<00:01, 140.83it/s]

→ 2000L Phase 2: corners:  61%|██████▏   | 201/327 [00:01<00:00, 151.89it/s]

→ 2000L Phase 2: corners:  67%|██████▋   | 218/327 [00:01<00:00, 155.63it/s]

→ 2000L Phase 2: corners:  72%|███████▏  | 234/327 [00:01<00:00, 152.72it/s]

→ 2000L Phase 2: corners:  78%|███████▊  | 254/327 [00:02<00:00, 164.65it/s]

→ 2000L Phase 2: corners:  83%|████████▎ | 271/327 [00:02<00:00, 164.33it/s]

→ 2000L Phase 2: corners:  88%|████████▊ | 288/327 [00:02<00:00, 157.61it/s]

→ 2000L Phase 2: corners:  93%|█████████▎| 304/327 [00:02<00:00, 152.64it/s]

→ 2000L Phase 2: corners: 100%|█████████▉| 326/327 [00:02<00:00, 164.75it/s]

                                                                            [PASS2] Frame 0000153: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000627: fixed corners {0} (was_fixed=False, trusted=False)
[PASS2] Frame 0000635: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000636: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000637: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000638: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000678: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000679: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000681: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000682: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000684: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000685: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001042: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001043: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001044: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001045: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001050: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001051: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001052: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001053: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001054: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001060: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001061: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001062: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001066: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000627: fixed corners {0} (was_fixed=False, trusted=False)
[PASS2] Frame 0000681: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000684: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001061: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001062: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001066: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000627: fixed corners {0} (was_fixed=False, trusted=False)
[PASS2] Frame 0000681: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001053: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001054: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001060: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001062: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001066: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Summary: 15 frames fixed, 28 untrusted, 327 total


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→ 2000L Phase 3: finalize:  29%|██▉       | 95/327 [00:01<00:04, 48.67it/s]

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→ 2000L Phase 3: finalize:  71%|███████   | 231/327 [00:04<00:01, 51.74it/s]

→ 2000L Phase 3: finalize:  72%|███████▏  | 237/327 [00:04<00:01, 51.79it/s]

→ 2000L Phase 3: finalize:  74%|███████▍  | 243/327 [00:04<00:01, 51.72it/s]

→ 2000L Phase 3: finalize:  76%|███████▌  | 249/327 [00:04<00:01, 51.52it/s]

→ 2000L Phase 3: finalize:  78%|███████▊  | 255/327 [00:05<00:01, 51.31it/s]

→ 2000L Phase 3: finalize:  80%|███████▉  | 261/327 [00:05<00:01, 51.09it/s]

→ 2000L Phase 3: finalize:  82%|████████▏ | 267/327 [00:05<00:01, 50.55it/s]

→ 2000L Phase 3: finalize:  83%|████████▎ | 273/327 [00:05<00:01, 50.18it/s]

→ 2000L Phase 3: finalize:  85%|████████▌ | 279/327 [00:05<00:00, 49.94it/s]

→ 2000L Phase 3: finalize:  87%|████████▋ | 284/327 [00:05<00:00, 49.77it/s]

→ 2000L Phase 3: finalize:  88%|████████▊ | 289/327 [00:05<00:00, 49.46it/s]

→ 2000L Phase 3: finalize:  90%|████████▉ | 294/327 [00:05<00:00, 48.76it/s]

→ 2000L Phase 3: finalize:  92%|█████████▏| 300/327 [00:05<00:00, 49.66it/s]

→ 2000L Phase 3: finalize:  93%|█████████▎| 305/327 [00:06<00:00, 49.29it/s]

→ 2000L Phase 3: finalize:  95%|█████████▍| 310/327 [00:06<00:00, 49.08it/s]

→ 2000L Phase 3: finalize:  96%|█████████▋| 315/327 [00:06<00:00, 49.00it/s]

→ 2000L Phase 3: finalize:  98%|█████████▊| 320/327 [00:06<00:00, 49.00it/s]

→ 2000L Phase 3: finalize: 100%|█████████▉| 326/327 [00:06<00:00, 49.41it/s]

                                                                            
[TIMING] 2000L — 328 frames
  Phase 1  radial detect   (parallel)  :   5.23s  (15.9 ms/frame)
  Phase 2a corner detect   (parallel)  :   2.52s  (7.7 ms/frame)
  Phase 2b corner fix      (sequential):   0.79s
  Phase 3  finalize        (sequential):   6.55s  (20.0 ms/frame)
    decode + undistort                 :   3.57s  (10.9 ms/frame)
    corner apply + refinement          :   1.36s  (4.2 ms/frame)
    segment                            :   1.33s  (4.0 ms/frame)
    smooth                             :   0.19s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  15.09s


Processing Rigs:  25%|██▌       | 1/4 [00:18<00:54, 18.04s/it][INFO] Filtered 161 stationary frames, 296 remain


→ 2000R (296 images) Phase 1:   0%|          | 0/296 [00:00<?, ?it/s]

→ 2000R (296 images) Phase 1:   0%|          | 1/296 [00:00<02:15,  2.18it/s]

→ 2000R (296 images) Phase 1:   1%|          | 2/296 [00:00<01:28,  3.34it/s]

→ 2000R (296 images) Phase 1:  11%|█         | 33/296 [00:00<00:05, 52.28it/s]

→ 2000R (296 images) Phase 1:  13%|█▎        | 39/296 [00:01<00:05, 44.12it/s]

→ 2000R (296 images) Phase 1:  22%|██▏       | 65/296 [00:01<00:03, 65.32it/s]

→ 2000R (296 images) Phase 1:  24%|██▍       | 72/296 [00:01<00:04, 54.83it/s]

→ 2000R (296 images) Phase 1:  33%|███▎      | 97/296 [00:01<00:02, 69.20it/s]

→ 2000R (296 images) Phase 1:  35%|███▌      | 104/296 [00:02<00:03, 59.11it/s]

→ 2000R (296 images) Phase 1:  44%|████▎     | 129/296 [00:02<00:02, 73.90it/s]

→ 2000R (296 images) Phase 1:  46%|████▋     | 137/296 [00:02<00:02, 61.45it/s]

→ 2000R (296 images) Phase 1:  54%|█████▍    | 161/296 [00:02<00:01, 76.01it/s]

→ 2000R (296 images) Phase 1:  57%|█████▋    | 169/296 [00:02<00:02, 63.17it/s]

→ 2000R (296 images) Phase 1:  65%|██████▌   | 193/296 [00:03<00:01, 75.64it/s]

→ 2000R (296 images) Phase 1:  68%|██████▊   | 201/296 [00:03<00:01, 64.34it/s]

→ 2000R (296 images) Phase 1:  76%|███████▌  | 225/296 [00:03<00:00, 75.90it/s]

→ 2000R (296 images) Phase 1:  79%|███████▊  | 233/296 [00:03<00:00, 64.53it/s]

→ 2000R (296 images) Phase 1:  86%|████████▌ | 254/296 [00:03<00:00, 87.11it/s]

→ 2000R (296 images) Phase 1:  90%|████████▉ | 265/296 [00:04<00:00, 62.69it/s]

→ 2000R (296 images) Phase 1:  98%|█████████▊| 289/296 [00:04<00:00, 83.69it/s]

                                                                               

→ 2000R Phase 2: corners:   0%|          | 0/295 [00:00<?, ?it/s]

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→ 2000R Phase 2: corners:   4%|▍         | 12/295 [00:00<00:06, 44.37it/s]

→ 2000R Phase 2: corners:   8%|▊         | 23/295 [00:00<00:04, 65.65it/s]

→ 2000R Phase 2: corners:  13%|█▎        | 38/295 [00:00<00:02, 92.35it/s]

→ 2000R Phase 2: corners:  17%|█▋        | 51/295 [00:00<00:02, 99.13it/s]

→ 2000R Phase 2: corners:  22%|██▏       | 64/295 [00:00<00:02, 108.00it/s]

→ 2000R Phase 2: corners:  26%|██▌       | 76/295 [00:00<00:02, 107.42it/s]

→ 2000R Phase 2: corners:  31%|███       | 90/295 [00:00<00:01, 116.54it/s]

→ 2000R Phase 2: corners:  36%|███▋      | 107/295 [00:01<00:01, 130.06it/s]

→ 2000R Phase 2: corners:  41%|████      | 121/295 [00:01<00:01, 116.30it/s]

→ 2000R Phase 2: corners:  46%|████▌     | 135/295 [00:01<00:01, 117.57it/s]

→ 2000R Phase 2: corners:  50%|█████     | 148/295 [00:01<00:01, 113.33it/s]

→ 2000R Phase 2: corners:  56%|█████▌    | 165/295 [00:01<00:01, 126.45it/s]

→ 2000R Phase 2: corners:  60%|██████    | 178/295 [00:01<00:00, 126.53it/s]

→ 2000R Phase 2: corners:  65%|██████▍   | 191/295 [00:01<00:00, 125.42it/s]

→ 2000R Phase 2: corners:  71%|███████   | 208/295 [00:01<00:00, 135.25it/s]

→ 2000R Phase 2: corners:  76%|███████▌  | 223/295 [00:01<00:00, 137.88it/s]

→ 2000R Phase 2: corners:  82%|████████▏ | 242/295 [00:02<00:00, 150.05it/s]

→ 2000R Phase 2: corners:  88%|████████▊ | 260/295 [00:02<00:00, 157.88it/s]

→ 2000R Phase 2: corners:  94%|█████████▍| 278/295 [00:02<00:00, 161.83it/s]

                                                                            [PASS2] Frame 0000542: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000543: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000544: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000599: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000600: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000601: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000602: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000610: fixed corners {0, 2, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000183: fixed corners {1, 2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000543: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000183: fixed corners {1, 2} (was_fixed=False, trusted=False)
[PASS2] Summary: 3 frames fixed, 11 untrusted, 295 total


→ 2000R Phase 3: finalize:   0%|          | 0/295 [00:00<?, ?it/s]

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→ 2000R Phase 3: finalize:  14%|█▎        | 40/295 [00:00<00:05, 46.94it/s]

→ 2000R Phase 3: finalize:  15%|█▌        | 45/295 [00:00<00:05, 47.19it/s]

→ 2000R Phase 3: finalize:  17%|█▋        | 50/295 [00:01<00:05, 47.56it/s]

→ 2000R Phase 3: finalize:  19%|█▊        | 55/295 [00:01<00:05, 47.79it/s]

→ 2000R Phase 3: finalize:  20%|██        | 60/295 [00:01<00:04, 48.10it/s]

→ 2000R Phase 3: finalize:  22%|██▏       | 65/295 [00:01<00:04, 48.20it/s]

→ 2000R Phase 3: finalize:  24%|██▎       | 70/295 [00:01<00:04, 48.09it/s]

→ 2000R Phase 3: finalize:  25%|██▌       | 75/295 [00:01<00:04, 48.04it/s]

→ 2000R Phase 3: finalize:  27%|██▋       | 80/295 [00:01<00:04, 48.01it/s]

→ 2000R Phase 3: finalize:  29%|██▉       | 85/295 [00:01<00:04, 47.85it/s]

→ 2000R Phase 3: finalize:  31%|███       | 90/295 [00:01<00:04, 47.62it/s]

→ 2000R Phase 3: finalize:  32%|███▏      | 95/295 [00:02<00:04, 47.39it/s]

→ 2000R Phase 3: finalize:  34%|███▍      | 100/295 [00:02<00:04, 47.38it/s]

→ 2000R Phase 3: finalize:  36%|███▌      | 105/295 [00:02<00:04, 47.37it/s]

→ 2000R Phase 3: finalize:  37%|███▋      | 110/295 [00:02<00:03, 47.66it/s]

→ 2000R Phase 3: finalize:  39%|███▉      | 115/295 [00:02<00:03, 48.15it/s]

→ 2000R Phase 3: finalize:  41%|████      | 120/295 [00:02<00:03, 48.17it/s]

→ 2000R Phase 3: finalize:  42%|████▏     | 125/295 [00:02<00:03, 48.18it/s]

→ 2000R Phase 3: finalize:  44%|████▍     | 130/295 [00:02<00:03, 48.62it/s]

→ 2000R Phase 3: finalize:  46%|████▌     | 136/295 [00:02<00:03, 49.08it/s]

→ 2000R Phase 3: finalize:  48%|████▊     | 142/295 [00:02<00:03, 49.50it/s]

→ 2000R Phase 3: finalize:  50%|█████     | 148/295 [00:03<00:02, 49.85it/s]

→ 2000R Phase 3: finalize:  52%|█████▏    | 154/295 [00:03<00:02, 50.18it/s]

→ 2000R Phase 3: finalize:  54%|█████▍    | 160/295 [00:03<00:02, 50.01it/s]

→ 2000R Phase 3: finalize:  56%|█████▋    | 166/295 [00:03<00:02, 50.37it/s]

→ 2000R Phase 3: finalize:  58%|█████▊    | 172/295 [00:03<00:02, 50.58it/s]

→ 2000R Phase 3: finalize:  60%|██████    | 178/295 [00:03<00:02, 50.84it/s]

→ 2000R Phase 3: finalize:  62%|██████▏   | 184/295 [00:03<00:02, 50.94it/s]

→ 2000R Phase 3: finalize:  64%|██████▍   | 190/295 [00:03<00:02, 51.14it/s]

→ 2000R Phase 3: finalize:  66%|██████▋   | 196/295 [00:04<00:01, 51.30it/s]

→ 2000R Phase 3: finalize:  68%|██████▊   | 202/295 [00:04<00:01, 51.35it/s]

→ 2000R Phase 3: finalize:  71%|███████   | 208/295 [00:04<00:01, 51.26it/s]

→ 2000R Phase 3: finalize:  73%|███████▎  | 214/295 [00:04<00:01, 51.80it/s]

→ 2000R Phase 3: finalize:  75%|███████▍  | 220/295 [00:04<00:01, 51.90it/s]

→ 2000R Phase 3: finalize:  77%|███████▋  | 226/295 [00:04<00:01, 51.97it/s]

→ 2000R Phase 3: finalize:  79%|███████▊  | 232/295 [00:04<00:01, 52.05it/s]

→ 2000R Phase 3: finalize:  81%|████████  | 238/295 [00:04<00:01, 52.12it/s]

→ 2000R Phase 3: finalize:  83%|████████▎ | 244/295 [00:04<00:00, 52.03it/s]

→ 2000R Phase 3: finalize:  85%|████████▍ | 250/295 [00:05<00:00, 51.80it/s]

→ 2000R Phase 3: finalize:  87%|████████▋ | 256/295 [00:05<00:00, 51.53it/s]

→ 2000R Phase 3: finalize:  89%|████████▉ | 262/295 [00:05<00:00, 51.30it/s]

→ 2000R Phase 3: finalize:  91%|█████████ | 268/295 [00:05<00:00, 51.06it/s]

→ 2000R Phase 3: finalize:  93%|█████████▎| 274/295 [00:05<00:00, 50.82it/s]

→ 2000R Phase 3: finalize:  95%|█████████▍| 280/295 [00:05<00:00, 50.01it/s]

→ 2000R Phase 3: finalize:  97%|█████████▋| 286/295 [00:05<00:00, 49.44it/s]

→ 2000R Phase 3: finalize:  99%|█████████▊| 291/295 [00:05<00:00, 49.15it/s]

                                                                            
[TIMING] 2000R — 296 frames
  Phase 1  radial detect   (parallel)  :   4.69s  (15.8 ms/frame)
  Phase 2a corner detect   (parallel)  :   2.44s  (8.3 ms/frame)
  Phase 2b corner fix      (sequential):   0.32s
  Phase 3  finalize        (sequential):   5.98s  (20.2 ms/frame)
    decode + undistort                 :   3.25s  (11.0 ms/frame)
    corner apply + refinement          :   1.26s  (4.2 ms/frame)
    segment                            :   1.20s  (4.1 ms/frame)
    smooth                             :   0.17s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  13.42s


Processing Rigs:  50%|█████     | 2/4 [00:33<00:33, 16.72s/it][INFO] Filtered 294 stationary frames, 303 remain


→ 1000 (303 images) Phase 1:   0%|          | 0/303 [00:00<?, ?it/s]

→ 1000 (303 images) Phase 1:   0%|          | 1/303 [00:00<02:25,  2.07it/s]

→ 1000 (303 images) Phase 1:   1%|          | 2/303 [00:00<01:22,  3.65it/s]

→ 1000 (303 images) Phase 1:   7%|▋         | 21/303 [00:00<00:06, 46.61it/s]

→ 1000 (303 images) Phase 1:  11%|█         | 33/303 [00:00<00:05, 49.45it/s]

→ 1000 (303 images) Phase 1:  14%|█▎        | 41/303 [00:01<00:05, 46.65it/s]

→ 1000 (303 images) Phase 1:  21%|██        | 63/303 [00:01<00:02, 80.60it/s]

→ 1000 (303 images) Phase 1:  25%|██▍       | 75/303 [00:01<00:04, 56.58it/s]

→ 1000 (303 images) Phase 1:  32%|███▏      | 96/303 [00:01<00:02, 79.32it/s]

→ 1000 (303 images) Phase 1:  36%|███▌      | 108/303 [00:02<00:03, 60.12it/s]

→ 1000 (303 images) Phase 1:  42%|████▏     | 127/303 [00:02<00:02, 78.86it/s]

→ 1000 (303 images) Phase 1:  46%|████▌     | 139/303 [00:02<00:02, 59.36it/s]

→ 1000 (303 images) Phase 1:  52%|█████▏    | 159/303 [00:02<00:01, 80.03it/s]

→ 1000 (303 images) Phase 1:  57%|█████▋    | 172/303 [00:02<00:02, 61.90it/s]

→ 1000 (303 images) Phase 1:  63%|██████▎   | 191/303 [00:03<00:01, 80.04it/s]

→ 1000 (303 images) Phase 1:  67%|██████▋   | 203/303 [00:03<00:01, 59.83it/s]

→ 1000 (303 images) Phase 1:  73%|███████▎  | 222/303 [00:03<00:01, 76.06it/s]

→ 1000 (303 images) Phase 1:  77%|███████▋  | 234/303 [00:03<00:01, 54.44it/s]

→ 1000 (303 images) Phase 1:  84%|████████▍ | 256/303 [00:04<00:00, 74.72it/s]

→ 1000 (303 images) Phase 1:  88%|████████▊ | 268/303 [00:04<00:00, 58.93it/s]

→ 1000 (303 images) Phase 1:  95%|█████████▌| 288/303 [00:04<00:00, 77.65it/s]

→ 1000 (303 images) Phase 1:  99%|█████████▉| 300/303 [00:04<00:00, 75.31it/s]

                                                                              

→ 1000 Phase 2: corners:   0%|          | 0/302 [00:00<?, ?it/s]

→ 1000 Phase 2: corners:   0%|          | 1/302 [00:00<01:20,  3.76it/s]

→ 1000 Phase 2: corners:   6%|▌         | 18/302 [00:00<00:04, 59.11it/s]

→ 1000 Phase 2: corners:  10%|▉         | 30/302 [00:00<00:03, 77.56it/s]

→ 1000 Phase 2: corners:  15%|█▍        | 44/302 [00:00<00:02, 96.42it/s]

→ 1000 Phase 2: corners:  19%|█▊        | 56/302 [00:00<00:02, 101.62it/s]

→ 1000 Phase 2: corners:  23%|██▎       | 69/302 [00:00<00:02, 105.19it/s]

→ 1000 Phase 2: corners:  28%|██▊       | 84/302 [00:00<00:01, 117.90it/s]

→ 1000 Phase 2: corners:  32%|███▏      | 97/302 [00:01<00:01, 121.19it/s]

→ 1000 Phase 2: corners:  36%|███▋      | 110/302 [00:01<00:01, 116.64it/s]

→ 1000 Phase 2: corners:  42%|████▏     | 128/302 [00:01<00:01, 133.51it/s]

→ 1000 Phase 2: corners:  48%|████▊     | 144/302 [00:01<00:01, 137.19it/s]

→ 1000 Phase 2: corners:  52%|█████▏    | 158/302 [00:01<00:01, 131.21it/s]

→ 1000 Phase 2: corners:  57%|█████▋    | 173/302 [00:01<00:00, 135.09it/s]

→ 1000 Phase 2: corners:  62%|██████▏   | 188/302 [00:01<00:00, 138.41it/s]

→ 1000 Phase 2: corners:  68%|██████▊   | 206/302 [00:01<00:00, 149.91it/s]

→ 1000 Phase 2: corners:  74%|███████▎  | 222/302 [00:01<00:00, 121.02it/s]

→ 1000 Phase 2: corners:  78%|███████▊  | 237/302 [00:02<00:00, 126.82it/s]

→ 1000 Phase 2: corners:  84%|████████▍ | 255/302 [00:02<00:00, 138.55it/s]

→ 1000 Phase 2: corners:  89%|████████▉ | 270/302 [00:02<00:00, 140.37it/s]

→ 1000 Phase 2: corners:  94%|█████████▍| 285/302 [00:02<00:00, 139.10it/s]

→ 1000 Phase 2: corners: 100%|██████████| 302/302 [00:02<00:00, 146.71it/s]

                                                                           [PASS2] Frame 0000506: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000529: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000530: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000531: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000532: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Summary: 3 frames fixed, 4 untrusted, 302 total


→ 1000 Phase 3: finalize:   0%|          | 0/302 [00:00<?, ?it/s]

→ 1000 Phase 3: finalize:   2%|▏         | 6/302 [00:00<00:05, 53.30it/s]

→ 1000 Phase 3: finalize:   4%|▍         | 12/302 [00:00<00:05, 52.30it/s]

→ 1000 Phase 3: finalize:   6%|▌         | 18/302 [00:00<00:05, 52.38it/s]

→ 1000 Phase 3: finalize:   8%|▊         | 24/302 [00:00<00:05, 51.90it/s]

→ 1000 Phase 3: finalize:  10%|▉         | 30/302 [00:00<00:05, 51.96it/s]

→ 1000 Phase 3: finalize:  12%|█▏        | 36/302 [00:00<00:05, 51.65it/s]

→ 1000 Phase 3: finalize:  14%|█▍        | 42/302 [00:00<00:05, 51.42it/s]

→ 1000 Phase 3: finalize:  16%|█▌        | 48/302 [00:00<00:04, 51.15it/s]

→ 1000 Phase 3: finalize:  18%|█▊        | 54/302 [00:01<00:04, 51.08it/s]

→ 1000 Phase 3: finalize:  20%|█▉        | 60/302 [00:01<00:04, 50.86it/s]

→ 1000 Phase 3: finalize:  22%|██▏       | 66/302 [00:01<00:04, 50.85it/s]

→ 1000 Phase 3: finalize:  24%|██▍       | 72/302 [00:01<00:04, 50.91it/s]

→ 1000 Phase 3: finalize:  26%|██▌       | 78/302 [00:01<00:04, 50.88it/s]

→ 1000 Phase 3: finalize:  28%|██▊       | 84/302 [00:01<00:04, 51.28it/s]

→ 1000 Phase 3: finalize:  30%|██▉       | 90/302 [00:01<00:04, 51.44it/s]

→ 1000 Phase 3: finalize:  32%|███▏      | 96/302 [00:01<00:03, 51.74it/s]

→ 1000 Phase 3: finalize:  34%|███▍      | 102/302 [00:01<00:03, 51.76it/s]

→ 1000 Phase 3: finalize:  36%|███▌      | 108/302 [00:02<00:03, 51.57it/s]

→ 1000 Phase 3: finalize:  38%|███▊      | 114/302 [00:02<00:03, 51.41it/s]

→ 1000 Phase 3: finalize:  40%|███▉      | 120/302 [00:02<00:03, 51.13it/s]

→ 1000 Phase 3: finalize:  42%|████▏     | 126/302 [00:02<00:03, 51.26it/s]

→ 1000 Phase 3: finalize:  44%|████▎     | 132/302 [00:02<00:03, 50.96it/s]

→ 1000 Phase 3: finalize:  46%|████▌     | 138/302 [00:02<00:03, 51.38it/s]

→ 1000 Phase 3: finalize:  48%|████▊     | 144/302 [00:02<00:03, 51.44it/s]

→ 1000 Phase 3: finalize:  50%|████▉     | 150/302 [00:02<00:02, 51.43it/s]

→ 1000 Phase 3: finalize:  52%|█████▏    | 156/302 [00:03<00:02, 51.46it/s]

→ 1000 Phase 3: finalize:  54%|█████▎    | 162/302 [00:03<00:02, 51.47it/s]

→ 1000 Phase 3: finalize:  56%|█████▌    | 168/302 [00:03<00:02, 51.25it/s]

→ 1000 Phase 3: finalize:  58%|█████▊    | 174/302 [00:03<00:02, 51.37it/s]

→ 1000 Phase 3: finalize:  60%|█████▉    | 180/302 [00:03<00:02, 51.50it/s]

→ 1000 Phase 3: finalize:  62%|██████▏   | 186/302 [00:03<00:02, 51.49it/s]

→ 1000 Phase 3: finalize:  64%|██████▎   | 192/302 [00:03<00:02, 51.47it/s]

→ 1000 Phase 3: finalize:  66%|██████▌   | 198/302 [00:03<00:02, 51.64it/s]

→ 1000 Phase 3: finalize:  68%|██████▊   | 204/302 [00:03<00:01, 51.95it/s]

→ 1000 Phase 3: finalize:  70%|██████▉   | 210/302 [00:04<00:01, 52.10it/s]

→ 1000 Phase 3: finalize:  72%|███████▏  | 216/302 [00:04<00:01, 52.27it/s]

→ 1000 Phase 3: finalize:  74%|███████▎  | 222/302 [00:04<00:01, 52.30it/s]

→ 1000 Phase 3: finalize:  75%|███████▌  | 228/302 [00:04<00:01, 52.03it/s]

→ 1000 Phase 3: finalize:  77%|███████▋  | 234/302 [00:04<00:01, 51.63it/s]

→ 1000 Phase 3: finalize:  79%|███████▉  | 240/302 [00:04<00:01, 51.33it/s]

→ 1000 Phase 3: finalize:  81%|████████▏ | 246/302 [00:04<00:01, 51.03it/s]

→ 1000 Phase 3: finalize:  83%|████████▎ | 252/302 [00:04<00:00, 51.22it/s]

→ 1000 Phase 3: finalize:  85%|████████▌ | 258/302 [00:05<00:00, 51.25it/s]

→ 1000 Phase 3: finalize:  87%|████████▋ | 264/302 [00:05<00:00, 51.13it/s]

→ 1000 Phase 3: finalize:  89%|████████▉ | 270/302 [00:05<00:00, 51.13it/s]

→ 1000 Phase 3: finalize:  91%|█████████▏| 276/302 [00:05<00:00, 51.36it/s]

→ 1000 Phase 3: finalize:  93%|█████████▎| 282/302 [00:05<00:00, 51.65it/s]

→ 1000 Phase 3: finalize:  95%|█████████▌| 288/302 [00:05<00:00, 51.75it/s]

→ 1000 Phase 3: finalize:  97%|█████████▋| 294/302 [00:05<00:00, 52.05it/s]

→ 1000 Phase 3: finalize:  99%|█████████▉| 300/302 [00:05<00:00, 52.24it/s]

                                                                           
[TIMING] 1000 — 303 frames
  Phase 1  radial detect   (parallel)  :   4.89s  (16.1 ms/frame)
  Phase 2a corner detect   (parallel)  :   2.56s  (8.5 ms/frame)
  Phase 2b corner fix      (sequential):   0.18s
  Phase 3  finalize        (sequential):   5.86s  (19.3 ms/frame)
    decode + undistort                 :   3.30s  (10.9 ms/frame)
    corner apply + refinement          :   1.09s  (3.6 ms/frame)
    segment                            :   1.20s  (4.0 ms/frame)
    smooth                             :   0.17s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  13.49s


Processing Rigs:  75%|███████▌  | 3/4 [00:50<00:16, 16.52s/it][INFO] Filtered 400 stationary frames, 474 remain


→ 1500 (474 images) Phase 1:   0%|          | 0/474 [00:00<?, ?it/s]

→ 1500 (474 images) Phase 1:   0%|          | 1/474 [00:00<04:08,  1.91it/s]

→ 1500 (474 images) Phase 1:   0%|          | 2/474 [00:00<02:23,  3.28it/s]

→ 1500 (474 images) Phase 1:   7%|▋         | 33/474 [00:00<00:09, 47.20it/s]

→ 1500 (474 images) Phase 1:   8%|▊         | 38/474 [00:01<00:10, 41.62it/s]

→ 1500 (474 images) Phase 1:  14%|█▎        | 65/474 [00:01<00:06, 62.65it/s]

→ 1500 (474 images) Phase 1:  15%|█▌        | 72/474 [00:01<00:07, 55.75it/s]

→ 1500 (474 images) Phase 1:  20%|██        | 97/474 [00:01<00:05, 68.69it/s]

→ 1500 (474 images) Phase 1:  22%|██▏       | 104/474 [00:02<00:06, 59.53it/s]

→ 1500 (474 images) Phase 1:  27%|██▋       | 129/474 [00:02<00:04, 71.56it/s]

→ 1500 (474 images) Phase 1:  29%|██▊       | 136/474 [00:02<00:05, 61.60it/s]

→ 1500 (474 images) Phase 1:  34%|███▍      | 161/474 [00:02<00:04, 72.76it/s]

→ 1500 (474 images) Phase 1:  35%|███▌      | 168/474 [00:03<00:04, 61.91it/s]

→ 1500 (474 images) Phase 1:  41%|████      | 193/474 [00:03<00:03, 74.06it/s]

→ 1500 (474 images) Phase 1:  42%|████▏     | 201/474 [00:03<00:04, 63.05it/s]

→ 1500 (474 images) Phase 1:  47%|████▋     | 225/474 [00:03<00:03, 74.29it/s]

→ 1500 (474 images) Phase 1:  49%|████▉     | 233/474 [00:03<00:03, 63.60it/s]

→ 1500 (474 images) Phase 1:  54%|█████▍    | 257/474 [00:04<00:02, 74.34it/s]

→ 1500 (474 images) Phase 1:  56%|█████▌    | 265/474 [00:04<00:03, 64.05it/s]

→ 1500 (474 images) Phase 1:  61%|██████    | 289/474 [00:04<00:02, 74.22it/s]

→ 1500 (474 images) Phase 1:  63%|██████▎   | 297/474 [00:04<00:02, 64.03it/s]

→ 1500 (474 images) Phase 1:  68%|██████▊   | 321/474 [00:05<00:02, 74.21it/s]

→ 1500 (474 images) Phase 1:  69%|██████▉   | 329/474 [00:05<00:02, 63.99it/s]

→ 1500 (474 images) Phase 1:  74%|███████▍  | 353/474 [00:05<00:01, 74.32it/s]

→ 1500 (474 images) Phase 1:  76%|███████▌  | 361/474 [00:05<00:01, 64.06it/s]

→ 1500 (474 images) Phase 1:  81%|████████  | 383/474 [00:05<00:01, 88.46it/s]

→ 1500 (474 images) Phase 1:  83%|████████▎ | 394/474 [00:06<00:01, 62.07it/s]

→ 1500 (474 images) Phase 1:  88%|████████▊ | 415/474 [00:06<00:00, 83.83it/s]

→ 1500 (474 images) Phase 1:  90%|█████████ | 428/474 [00:06<00:00, 62.62it/s]

→ 1500 (474 images) Phase 1:  94%|█████████▍| 447/474 [00:06<00:00, 79.95it/s]

→ 1500 (474 images) Phase 1:  97%|█████████▋| 459/474 [00:07<00:00, 66.67it/s]

                                                                              

→ 1500 Phase 2: corners:   0%|          | 0/473 [00:00<?, ?it/s]

→ 1500 Phase 2: corners:   0%|          | 1/473 [00:00<01:36,  4.91it/s]

→ 1500 Phase 2: corners:   3%|▎         | 12/473 [00:00<00:09, 47.97it/s]

→ 1500 Phase 2: corners:   5%|▌         | 26/473 [00:00<00:05, 80.19it/s]

→ 1500 Phase 2: corners:   8%|▊         | 39/473 [00:00<00:04, 94.29it/s]

→ 1500 Phase 2: corners:  11%|█         | 50/473 [00:00<00:04, 94.54it/s]

→ 1500 Phase 2: corners:  13%|█▎        | 61/473 [00:00<00:04, 96.68it/s]

→ 1500 Phase 2: corners:  16%|█▌        | 74/473 [00:00<00:03, 104.95it/s]

→ 1500 Phase 2: corners:  18%|█▊        | 85/473 [00:00<00:03, 105.67it/s]

→ 1500 Phase 2: corners:  21%|██        | 98/473 [00:01<00:03, 110.62it/s]

→ 1500 Phase 2: corners:  23%|██▎       | 111/473 [00:01<00:03, 115.15it/s]

→ 1500 Phase 2: corners:  27%|██▋       | 126/473 [00:01<00:02, 125.17it/s]

→ 1500 Phase 2: corners:  29%|██▉       | 139/473 [00:01<00:02, 124.72it/s]

→ 1500 Phase 2: corners:  32%|███▏      | 153/473 [00:01<00:02, 128.69it/s]

→ 1500 Phase 2: corners:  36%|███▌      | 169/473 [00:01<00:02, 137.68it/s]

→ 1500 Phase 2: corners:  39%|███▊      | 183/473 [00:01<00:02, 134.85it/s]

→ 1500 Phase 2: corners:  43%|████▎     | 202/473 [00:01<00:01, 149.44it/s]

→ 1500 Phase 2: corners:  46%|████▋     | 219/473 [00:01<00:01, 154.85it/s]

→ 1500 Phase 2: corners:  50%|████▉     | 236/473 [00:01<00:01, 156.08it/s]

→ 1500 Phase 2: corners:  53%|█████▎    | 253/473 [00:02<00:01, 158.63it/s]

→ 1500 Phase 2: corners:  57%|█████▋    | 271/473 [00:02<00:01, 158.16it/s]

→ 1500 Phase 2: corners:  61%|██████▏   | 290/473 [00:02<00:01, 166.85it/s]

→ 1500 Phase 2: corners:  66%|██████▌   | 310/473 [00:02<00:00, 175.15it/s]

→ 1500 Phase 2: corners:  70%|██████▉   | 329/473 [00:02<00:00, 179.02it/s]

→ 1500 Phase 2: corners:  74%|███████▎  | 348/473 [00:02<00:00, 181.97it/s]

→ 1500 Phase 2: corners:  78%|███████▊  | 367/473 [00:02<00:00, 172.08it/s]

→ 1500 Phase 2: corners:  81%|████████▏ | 385/473 [00:02<00:00, 171.62it/s]

→ 1500 Phase 2: corners:  85%|████████▌ | 403/473 [00:02<00:00, 170.52it/s]

→ 1500 Phase 2: corners:  89%|████████▉ | 422/473 [00:03<00:00, 172.51it/s]

→ 1500 Phase 2: corners:  93%|█████████▎| 440/473 [00:03<00:00, 170.86it/s]

→ 1500 Phase 2: corners:  97%|█████████▋| 458/473 [00:03<00:00, 164.38it/s]

                                                                           [PASS2] Frame 0000543: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000544: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000545: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000546: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Summary: 2 frames fixed, 21 untrusted, 473 total


→ 1500 Phase 3: finalize:   0%|          | 0/473 [00:00<?, ?it/s]

→ 1500 Phase 3: finalize:   1%|▏         | 7/473 [00:00<00:07, 65.65it/s]

→ 1500 Phase 3: finalize:   3%|▎         | 14/473 [00:00<00:07, 57.66it/s]

→ 1500 Phase 3: finalize:   4%|▍         | 20/473 [00:00<00:08, 52.93it/s]

→ 1500 Phase 3: finalize:   5%|▌         | 26/473 [00:00<00:08, 51.46it/s]

→ 1500 Phase 3: finalize:   7%|▋         | 32/473 [00:00<00:08, 50.35it/s]

→ 1500 Phase 3: finalize:   8%|▊         | 38/473 [00:00<00:08, 50.01it/s]

→ 1500 Phase 3: finalize:   9%|▉         | 44/473 [00:00<00:08, 49.49it/s]

→ 1500 Phase 3: finalize:  10%|█         | 49/473 [00:00<00:08, 49.39it/s]

→ 1500 Phase 3: finalize:  11%|█▏        | 54/473 [00:01<00:08, 49.19it/s]

→ 1500 Phase 3: finalize:  12%|█▏        | 59/473 [00:01<00:08, 48.96it/s]

→ 1500 Phase 3: finalize:  14%|█▎        | 64/473 [00:01<00:08, 48.77it/s]

→ 1500 Phase 3: finalize:  15%|█▍        | 69/473 [00:01<00:08, 48.68it/s]

→ 1500 Phase 3: finalize:  16%|█▌        | 74/473 [00:01<00:08, 48.70it/s]

→ 1500 Phase 3: finalize:  17%|█▋        | 79/473 [00:01<00:08, 48.66it/s]

→ 1500 Phase 3: finalize:  18%|█▊        | 84/473 [00:01<00:07, 48.67it/s]

→ 1500 Phase 3: finalize:  19%|█▉        | 89/473 [00:01<00:07, 48.63it/s]

→ 1500 Phase 3: finalize:  20%|█▉        | 94/473 [00:01<00:07, 48.79it/s]

→ 1500 Phase 3: finalize:  21%|██        | 99/473 [00:01<00:07, 48.77it/s]

→ 1500 Phase 3: finalize:  22%|██▏       | 104/473 [00:02<00:07, 48.79it/s]

→ 1500 Phase 3: finalize:  23%|██▎       | 109/473 [00:02<00:07, 48.69it/s]

→ 1500 Phase 3: finalize:  24%|██▍       | 114/473 [00:02<00:07, 48.85it/s]

→ 1500 Phase 3: finalize:  25%|██▌       | 119/473 [00:02<00:07, 49.12it/s]

→ 1500 Phase 3: finalize:  26%|██▋       | 125/473 [00:02<00:07, 49.55it/s]

→ 1500 Phase 3: finalize:  28%|██▊       | 131/473 [00:02<00:06, 49.70it/s]

→ 1500 Phase 3: finalize:  29%|██▉       | 136/473 [00:02<00:06, 49.60it/s]

→ 1500 Phase 3: finalize:  30%|██▉       | 141/473 [00:02<00:06, 49.60it/s]

→ 1500 Phase 3: finalize:  31%|███       | 146/473 [00:02<00:06, 49.61it/s]

→ 1500 Phase 3: finalize:  32%|███▏      | 151/473 [00:03<00:06, 49.69it/s]

→ 1500 Phase 3: finalize:  33%|███▎      | 157/473 [00:03<00:06, 49.92it/s]

→ 1500 Phase 3: finalize:  34%|███▍      | 163/473 [00:03<00:06, 50.13it/s]

→ 1500 Phase 3: finalize:  36%|███▌      | 169/473 [00:03<00:06, 50.35it/s]

→ 1500 Phase 3: finalize:  37%|███▋      | 175/473 [00:03<00:05, 50.50it/s]

→ 1500 Phase 3: finalize:  38%|███▊      | 181/473 [00:03<00:05, 50.61it/s]

→ 1500 Phase 3: finalize:  40%|███▉      | 187/473 [00:03<00:05, 50.72it/s]

→ 1500 Phase 3: finalize:  41%|████      | 193/473 [00:03<00:05, 50.81it/s]

→ 1500 Phase 3: finalize:  42%|████▏     | 199/473 [00:03<00:05, 50.76it/s]

→ 1500 Phase 3: finalize:  43%|████▎     | 205/473 [00:04<00:05, 50.68it/s]

→ 1500 Phase 3: finalize:  45%|████▍     | 211/473 [00:04<00:05, 50.58it/s]

→ 1500 Phase 3: finalize:  46%|████▌     | 217/473 [00:04<00:05, 50.40it/s]

→ 1500 Phase 3: finalize:  47%|████▋     | 223/473 [00:04<00:04, 50.45it/s]

→ 1500 Phase 3: finalize:  48%|████▊     | 229/473 [00:04<00:04, 50.53it/s]

→ 1500 Phase 3: finalize:  50%|████▉     | 235/473 [00:04<00:04, 50.47it/s]

→ 1500 Phase 3: finalize:  51%|█████     | 241/473 [00:04<00:04, 50.23it/s]

→ 1500 Phase 3: finalize:  52%|█████▏    | 247/473 [00:04<00:04, 50.38it/s]

→ 1500 Phase 3: finalize:  53%|█████▎    | 253/473 [00:05<00:04, 50.18it/s]

→ 1500 Phase 3: finalize:  55%|█████▍    | 259/473 [00:05<00:04, 50.02it/s]

→ 1500 Phase 3: finalize:  56%|█████▌    | 265/473 [00:05<00:04, 49.94it/s]

→ 1500 Phase 3: finalize:  57%|█████▋    | 271/473 [00:05<00:04, 49.92it/s]

→ 1500 Phase 3: finalize:  58%|█████▊    | 276/473 [00:05<00:03, 49.87it/s]

→ 1500 Phase 3: finalize:  59%|█████▉    | 281/473 [00:05<00:03, 49.84it/s]

→ 1500 Phase 3: finalize:  61%|██████    | 287/473 [00:05<00:03, 49.95it/s]

→ 1500 Phase 3: finalize:  62%|██████▏   | 292/473 [00:05<00:03, 49.95it/s]

→ 1500 Phase 3: finalize:  63%|██████▎   | 298/473 [00:05<00:03, 50.01it/s]

→ 1500 Phase 3: finalize:  64%|██████▍   | 304/473 [00:06<00:03, 49.95it/s]

→ 1500 Phase 3: finalize:  65%|██████▌   | 309/473 [00:06<00:03, 49.85it/s]

→ 1500 Phase 3: finalize:  66%|██████▋   | 314/473 [00:06<00:03, 49.71it/s]

→ 1500 Phase 3: finalize:  67%|██████▋   | 319/473 [00:06<00:03, 49.49it/s]

→ 1500 Phase 3: finalize:  68%|██████▊   | 324/473 [00:06<00:03, 49.35it/s]

→ 1500 Phase 3: finalize:  70%|██████▉   | 329/473 [00:06<00:02, 49.04it/s]

→ 1500 Phase 3: finalize:  71%|███████   | 334/473 [00:06<00:02, 48.90it/s]

→ 1500 Phase 3: finalize:  72%|███████▏  | 339/473 [00:06<00:02, 48.77it/s]

→ 1500 Phase 3: finalize:  73%|███████▎  | 344/473 [00:06<00:02, 48.67it/s]

→ 1500 Phase 3: finalize:  74%|███████▍  | 349/473 [00:06<00:02, 48.76it/s]

→ 1500 Phase 3: finalize:  75%|███████▍  | 354/473 [00:07<00:02, 48.92it/s]

→ 1500 Phase 3: finalize:  76%|███████▌  | 359/473 [00:07<00:02, 48.97it/s]

→ 1500 Phase 3: finalize:  77%|███████▋  | 364/473 [00:07<00:02, 49.04it/s]

→ 1500 Phase 3: finalize:  78%|███████▊  | 369/473 [00:07<00:02, 48.93it/s]

→ 1500 Phase 3: finalize:  79%|███████▉  | 374/473 [00:07<00:02, 48.77it/s]

→ 1500 Phase 3: finalize:  80%|████████  | 379/473 [00:07<00:01, 48.54it/s]

→ 1500 Phase 3: finalize:  81%|████████  | 384/473 [00:07<00:01, 48.38it/s]

→ 1500 Phase 3: finalize:  82%|████████▏ | 389/473 [00:07<00:01, 48.39it/s]

→ 1500 Phase 3: finalize:  83%|████████▎ | 394/473 [00:07<00:01, 48.49it/s]

→ 1500 Phase 3: finalize:  84%|████████▍ | 399/473 [00:08<00:01, 48.50it/s]

→ 1500 Phase 3: finalize:  85%|████████▌ | 404/473 [00:08<00:01, 48.60it/s]

→ 1500 Phase 3: finalize:  86%|████████▋ | 409/473 [00:08<00:01, 48.65it/s]

→ 1500 Phase 3: finalize:  88%|████████▊ | 414/473 [00:08<00:01, 48.79it/s]

→ 1500 Phase 3: finalize:  89%|████████▊ | 419/473 [00:08<00:01, 48.64it/s]

→ 1500 Phase 3: finalize:  90%|████████▉ | 424/473 [00:08<00:01, 48.49it/s]

→ 1500 Phase 3: finalize:  91%|█████████ | 429/473 [00:08<00:00, 48.56it/s]

→ 1500 Phase 3: finalize:  92%|█████████▏| 434/473 [00:08<00:00, 48.71it/s]

→ 1500 Phase 3: finalize:  93%|█████████▎| 439/473 [00:08<00:00, 49.05it/s]

→ 1500 Phase 3: finalize:  94%|█████████▍| 444/473 [00:08<00:00, 49.22it/s]

→ 1500 Phase 3: finalize:  95%|█████████▍| 449/473 [00:09<00:00, 49.07it/s]

→ 1500 Phase 3: finalize:  96%|█████████▌| 454/473 [00:09<00:00, 49.28it/s]

→ 1500 Phase 3: finalize:  97%|█████████▋| 459/473 [00:09<00:00, 49.41it/s]

→ 1500 Phase 3: finalize:  98%|█████████▊| 464/473 [00:09<00:00, 49.39it/s]

→ 1500 Phase 3: finalize:  99%|█████████▉| 469/473 [00:09<00:00, 49.45it/s]

                                                                           
[TIMING] 1500 — 474 frames
  Phase 1  radial detect   (parallel)  :   7.31s  (15.4 ms/frame)
  Phase 2a corner detect   (parallel)  :   3.39s  (7.2 ms/frame)
  Phase 2b corner fix      (sequential):   0.24s
  Phase 3  finalize        (sequential):   9.53s  (20.1 ms/frame)
    decode + undistort                 :   5.32s  (11.2 ms/frame)
    corner apply + refinement          :   1.82s  (3.8 ms/frame)
    segment                            :   1.92s  (4.1 ms/frame)
    smooth                             :   0.32s  (0.7 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  20.47s


Processing Rigs: 100%|██████████| 4/4 [01:15<00:00, 19.87s/it]
Processing Rigs: 100%|██████████| 4/4 [01:15<00:00, 18.78s/it]
[💾] Saved RigFrameDataset to /working/MDCP3D-SL-013_W046(6)/calibration/debug/1_digitized_full/rig_frames_full.json
[✅] Saved full dataset: 1397 frames from 4 rigs to /working/MDCP3D-SL-013_W046(6)/calibration/debug/1_digitized_full/rig_frames_full.json
[💾] Saved RigFrameDataset to /working/MDCP3D-SL-013_W046(6)/calibration/debug/1_digitized_full/rig_frames_full.json
[📋] Creating calibration subset (100 frames/rig) with visualizations...
[📋] 2000L: 100 frames selected from 327
[📋] 2000R: 100 frames selected from 295
[📋] 1000: 100 frames selected from 302
[📋] 1500: 100 frames selected from 473
[💾] Saved RigFrameDataset to /working/MDCP3D-SL-013_W046(6)/calibration/debug/1_digitized/rig_frames.json
[INFO] Reloading dataset from disk to ensure clean state for multiprocessing...
[📂] Loaded RigFrameDataset from /working/MDCP3D-SL-013_W046(6)/calibration/debug/1_digitized/rig_frames.json

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

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

Computing max image from bright frames:   0%|          | 0/80 [00:00<?, ?it/s]
Computing max image from bright frames:   1%|▏         | 1/80 [00:04<05:18,  4.03s/it]
Computing max image from bright frames:   2%|▎         | 2/80 [00:04<02:15,  1.73s/it]
Computing max image from bright frames:   4%|▍         | 3/80 [00:04<01:19,  1.03s/it]
Computing max image from bright frames:   5%|▌         | 4/80 [00:04<00:51,  1.48it/s]
Computing max image from bright frames:   8%|▊         | 6/80 [00:04<00:26,  2.82it/s]
Computing max image from bright frames:  10%|█         | 8/80 [00:04<00:16,  4.38it/s]
Computing max image from bright frames:  12%|█▎        | 10/80 [00:04<00:11,  5.89it/s]
Computing max image from bright frames:  15%|█▌        | 12/80 [00:05<00:10,  6.62it/s]
Computing max image from bright frames:  18%|█▊        | 14/80 [00:05<00:08,  7.59it/s]
Computing max image from bright frames:  20%|██        | 16/80 [00:05<00:09,  6.61it/s]
Computing max image from bright frames:  22%|██▎       | 18/80 [00:05<00:08,  7.73it/s]
Computing max image from bright frames:  25%|██▌       | 20/80 [00:06<00:06,  8.66it/s]
Computing max image from bright frames:  28%|██▊       | 22/80 [00:06<00:05,  9.74it/s]
Computing max image from bright frames:  30%|███       | 24/80 [00:06<00:05, 11.15it/s]
Computing max image from bright frames:  32%|███▎      | 26/80 [00:06<00:04, 11.18it/s]
Computing max image from bright frames:  36%|███▋      | 29/80 [00:06<00:03, 13.03it/s]
Computing max image from bright frames:  39%|███▉      | 31/80 [00:06<00:03, 12.49it/s]
Computing max image from bright frames:  41%|████▏     | 33/80 [00:09<00:17,  2.66it/s]
Computing max image from bright frames:  42%|████▎     | 34/80 [00:09<00:15,  3.02it/s]
Computing max image from bright frames:  44%|████▍     | 35/80 [00:09<00:13,  3.37it/s]
Computing max image from bright frames:  46%|████▋     | 37/80 [00:09<00:09,  4.59it/s]
Computing max image from bright frames:  49%|████▉     | 39/80 [00:09<00:06,  5.94it/s]
Computing max image from bright frames:  51%|█████▏    | 41/80 [00:09<00:05,  7.48it/s]
Computing max image from bright frames:  54%|█████▍    | 43/80 [00:09<00:04,  8.54it/s]
Computing max image from bright frames:  56%|█████▋    | 45/80 [00:10<00:03,  9.17it/s]
Computing max image from bright frames:  59%|█████▉    | 47/80 [00:10<00:04,  8.17it/s]
Computing max image from bright frames:  61%|██████▏   | 49/80 [00:10<00:04,  7.46it/s]
Computing max image from bright frames:  65%|██████▌   | 52/80 [00:10<00:02,  9.34it/s]
Computing max image from bright frames:  68%|██████▊   | 54/80 [00:11<00:02, 10.21it/s]
Computing max image from bright frames:  71%|███████▏  | 57/80 [00:11<00:01, 12.88it/s]
Computing max image from bright frames:  74%|███████▍  | 59/80 [00:11<00:01, 12.70it/s]
Computing max image from bright frames:  76%|███████▋  | 61/80 [00:11<00:01, 13.91it/s]
Computing max image from bright frames:  79%|███████▉  | 63/80 [00:11<00:01, 11.96it/s]
Computing max image from bright frames:  81%|████████▏ | 65/80 [00:12<00:02,  5.13it/s]
Computing max image from bright frames:  84%|████████▍ | 67/80 [00:12<00:02,  5.79it/s]
Computing max image from bright frames:  88%|████████▊ | 70/80 [00:13<00:01,  8.27it/s]
Computing max image from bright frames:  92%|█████████▎| 74/80 [00:13<00:00, 12.28it/s]
Computing max image from bright frames:  96%|█████████▋| 77/80 [00:13<00:00, 13.58it/s]
Computing max image from bright frames: 100%|██████████| 80/80 [00:13<00:00, 13.38it/s]
                                                                                       
[✅] Casing detection complete: cx=863.0, cy=995.0

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


  0%|          | 0/100 [00:00<?, ?it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   0%|          | 0/100 [00:00<?, ?it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   1%|          | 1/100 [00:00<00:25,  3.83it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.000 | Best: {'fx': 307.071} (0.000):   1%|          | 1/100 [00:00<00:25,  3.83it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   2%|▏         | 2/100 [00:00<00:25,  3.83it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.001 | Best: {'fx': 321.212} (0.001):   3%|▎         | 3/100 [00:00<00:25,  3.83it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.001 | Best: {'fx': 321.212} (0.001):   4%|▍         | 4/100 [00:00<00:07, 12.77it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.001 | Best: {'fx': 328.283} (0.001):   4%|▍         | 4/100 [00:00<00:07, 12.77it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.001 | Best: {'fx': 335.354} (0.001):   5%|▌         | 5/100 [00:00<00:07, 12.77it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.001 | Best: {'fx': 349.495} (0.001):   6%|▌         | 6/100 [00:00<00:07, 12.77it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.001 | Best: {'fx': 349.495} (0.001):   7%|▋         | 7/100 [00:00<00:05, 16.69it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.001 | Best: {'fx': 349.495} (0.001):   7%|▋         | 7/100 [00:00<00:05, 16.69it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.001 | Best: {'fx': 356.566} (0.001):   8%|▊         | 8/100 [00:00<00:05, 16.69it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.002 | Best: {'fx': 363.636} (0.002):   9%|▉         | 9/100 [00:00<00:05, 16.69it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.002 | Best: {'fx': 370.707} (0.002):  10%|█         | 10/100 [00:00<00:05, 16.69it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.002 | Best: {'fx': 370.707} (0.002):  11%|█         | 11/100 [00:00<00:03, 23.25it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.003 | Best: {'fx': 377.778} (0.003):  11%|█         | 11/100 [00:00<00:03, 23.25it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.003 | Best: {'fx': 384.848} (0.003):  12%|█▏        | 12/100 [00:00<00:03, 23.25it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.004 | Best: {'fx': 391.919} (0.004):  13%|█▎        | 13/100 [00:00<00:03, 23.25it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.004 | Best: {'fx': 391.919} (0.004):  14%|█▍        | 14/100 [00:00<00:03, 24.36it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.004 | Best: {'fx': 398.99} (0.004):  14%|█▍        | 14/100 [00:00<00:03, 24.36it/s] 
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.005 | Best: {'fx': 406.061} (0.005):  15%|█▌        | 15/100 [00:00<00:03, 24.36it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.006 | Best: {'fx': 420.202} (0.006):  16%|█▌        | 16/100 [00:00<00:03, 24.36it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.006 | Best: {'fx': 420.202} (0.006):  17%|█▋        | 17/100 [00:00<00:03, 24.73it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.005 | Best: {'fx': 420.202} (0.006):  17%|█▋        | 17/100 [00:00<00:03, 24.73it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.006 | Best: {'fx': 427.273} (0.006):  18%|█▊        | 18/100 [00:00<00:03, 24.73it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.008 | Best: {'fx': 434.343} (0.008):  19%|█▉        | 19/100 [00:00<00:03, 24.73it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.008 | Best: {'fx': 441.414} (0.008):  20%|██        | 20/100 [00:00<00:03, 24.73it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.008 | Best: {'fx': 441.414} (0.008):  21%|██        | 21/100 [00:00<00:03, 25.20it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.010 | Best: {'fx': 448.485} (0.010):  21%|██        | 21/100 [00:00<00:03, 25.20it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.012 | Best: {'fx': 455.556} (0.012):  22%|██▏       | 22/100 [00:01<00:03, 25.20it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.014 | Best: {'fx': 462.626} (0.014):  23%|██▎       | 23/100 [00:01<00:03, 25.20it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.014 | Best: {'fx': 462.626} (0.014):  24%|██▍       | 24/100 [00:01<00:03, 24.06it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.017 | Best: {'fx': 469.697} (0.017):  24%|██▍       | 24/100 [00:01<00:03, 24.06it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.021 | Best: {'fx': 476.768} (0.021):  25%|██▌       | 25/100 [00:01<00:03, 24.06it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.024 | Best: {'fx': 483.838} (0.024):  26%|██▌       | 26/100 [00:01<00:03, 24.06it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.030 | Best: {'fx': 490.909} (0.030):  27%|██▋       | 27/100 [00:01<00:03, 24.06it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.030 | Best: {'fx': 490.909} (0.030):  28%|██▊       | 28/100 [00:01<00:02, 27.00it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.047 | Best: {'fx': 505.051} (0.047):  28%|██▊       | 28/100 [00:01<00:02, 27.00it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.038 | Best: {'fx': 505.051} (0.047):  29%|██▉       | 29/100 [00:01<00:02, 27.00it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.057 | Best: {'fx': 512.121} (0.057):  30%|███       | 30/100 [00:01<00:02, 27.00it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.057 | Best: {'fx': 512.121} (0.057):  31%|███       | 31/100 [00:01<00:03, 21.95it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.068 | Best: {'fx': 519.192} (0.068):  31%|███       | 31/100 [00:01<00:03, 21.95it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.078 | Best: {'fx': 526.263} (0.078):  32%|███▏      | 32/100 [00:01<00:03, 21.95it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.065 | Best: {'fx': 526.263} (0.078):  33%|███▎      | 33/100 [00:01<00:03, 21.95it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.065 | Best: {'fx': 526.263} (0.078):  34%|███▍      | 34/100 [00:01<00:03, 18.27it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.083 | Best: {'fx': 533.333} (0.083):  34%|███▍      | 34/100 [00:01<00:03, 18.27it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.074 | Best: {'fx': 533.333} (0.083):  35%|███▌      | 35/100 [00:01<00:03, 18.27it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.056 | Best: {'fx': 533.333} (0.083):  36%|███▌      | 36/100 [00:01<00:03, 18.27it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.046 | Best: {'fx': 533.333} (0.083):  37%|███▋      | 37/100 [00:01<00:03, 18.27it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.046 | Best: {'fx': 533.333} (0.083):  38%|███▊      | 38/100 [00:01<00:02, 21.86it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.043 | Best: {'fx': 533.333} (0.083):  38%|███▊      | 38/100 [00:01<00:02, 21.86it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.039 | Best: {'fx': 533.333} (0.083):  39%|███▉      | 39/100 [00:01<00:02, 21.86it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.049 | Best: {'fx': 533.333} (0.083):  40%|████      | 40/100 [00:01<00:02, 21.86it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.049 | Best: {'fx': 533.333} (0.083):  41%|████      | 41/100 [00:01<00:02, 20.24it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.037 | Best: {'fx': 533.333} (0.083):  41%|████      | 41/100 [00:02<00:02, 20.24it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.027 | Best: {'fx': 533.333} (0.083):  42%|████▏     | 42/100 [00:02<00:02, 20.24it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.027 | Best: {'fx': 533.333} (0.083):  43%|████▎     | 43/100 [00:02<00:02, 20.24it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.027 | Best: {'fx': 533.333} (0.083):  44%|████▍     | 44/100 [00:02<00:02, 19.61it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.035 | Best: {'fx': 533.333} (0.083):  44%|████▍     | 44/100 [00:02<00:02, 19.61it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.030 | Best: {'fx': 533.333} (0.083):  45%|████▌     | 45/100 [00:02<00:02, 19.61it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.033 | Best: {'fx': 533.333} (0.083):  46%|████▌     | 46/100 [00:02<00:02, 19.61it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.032 | Best: {'fx': 533.333} (0.083):  47%|████▋     | 47/100 [00:02<00:02, 19.61it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.029 | Best: {'fx': 533.333} (0.083):  48%|████▊     | 48/100 [00:02<00:02, 19.61it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.028 | Best: {'fx': 533.333} (0.083):  49%|████▉     | 49/100 [00:02<00:02, 19.61it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.031 | Best: {'fx': 533.333} (0.083):  50%|█████     | 50/100 [00:02<00:02, 19.61it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.026 | Best: {'fx': 533.333} (0.083):  51%|█████     | 51/100 [00:02<00:02, 19.61it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.026 | Best: {'fx': 533.333} (0.083):  52%|█████▏    | 52/100 [00:02<00:01, 26.38it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.024 | Best: {'fx': 533.333} (0.083):  52%|█████▏    | 52/100 [00:02<00:01, 26.38it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.025 | Best: {'fx': 533.333} (0.083):  53%|█████▎    | 53/100 [00:02<00:01, 26.38it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.023 | Best: {'fx': 533.333} (0.083):  54%|█████▍    | 54/100 [00:02<00:01, 26.38it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.022 | Best: {'fx': 533.333} (0.083):  55%|█████▌    | 55/100 [00:02<00:01, 26.38it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.026 | Best: {'fx': 533.333} (0.083):  56%|█████▌    | 56/100 [00:02<00:01, 26.38it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.024 | Best: {'fx': 533.333} (0.083):  57%|█████▋    | 57/100 [00:02<00:01, 26.38it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.021 | Best: {'fx': 533.333} (0.083):  58%|█████▊    | 58/100 [00:02<00:01, 26.38it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.025 | Best: {'fx': 533.333} (0.083):  59%|█████▉    | 59/100 [00:02<00:01, 26.38it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.025 | Best: {'fx': 533.333} (0.083):  60%|██████    | 60/100 [00:02<00:01, 34.98it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.023 | Best: {'fx': 533.333} (0.083):  60%|██████    | 60/100 [00:02<00:01, 34.98it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.022 | Best: {'fx': 533.333} (0.083):  61%|██████    | 61/100 [00:02<00:01, 34.98it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.021 | Best: {'fx': 533.333} (0.083):  62%|██████▏   | 62/100 [00:02<00:01, 34.98it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.022 | Best: {'fx': 533.333} (0.083):  63%|██████▎   | 63/100 [00:02<00:01, 34.98it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.023 | Best: {'fx': 533.333} (0.083):  64%|██████▍   | 64/100 [00:02<00:01, 34.98it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.021 | Best: {'fx': 533.333} (0.083):  65%|██████▌   | 65/100 [00:02<00:01, 34.98it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.021 | Best: {'fx': 533.333} (0.083):  66%|██████▌   | 66/100 [00:02<00:00, 34.98it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.023 | Best: {'fx': 533.333} (0.083):  67%|██████▋   | 67/100 [00:02<00:00, 34.98it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.023 | Best: {'fx': 533.333} (0.083):  68%|██████▊   | 68/100 [00:02<00:00, 43.34it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.021 | Best: {'fx': 533.333} (0.083):  68%|██████▊   | 68/100 [00:02<00:00, 43.34it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.021 | Best: {'fx': 533.333} (0.083):  69%|██████▉   | 69/100 [00:02<00:00, 43.34it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.022 | Best: {'fx': 533.333} (0.083):  70%|███████   | 70/100 [00:02<00:00, 43.34it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.020 | Best: {'fx': 533.333} (0.083):  71%|███████   | 71/100 [00:02<00:00, 43.34it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.020 | Best: {'fx': 533.333} (0.083):  72%|███████▏  | 72/100 [00:02<00:00, 43.34it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.020 | Best: {'fx': 533.333} (0.083):  73%|███████▎  | 73/100 [00:02<00:00, 41.04it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.020 | Best: {'fx': 533.333} (0.083):  73%|███████▎  | 73/100 [00:02<00:00, 41.04it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.020 | Best: {'fx': 533.333} (0.083):  74%|███████▍  | 74/100 [00:02<00:00, 41.04it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.020 | Best: {'fx': 533.333} (0.083):  75%|███████▌  | 75/100 [00:02<00:00, 41.04it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.020 | Best: {'fx': 533.333} (0.083):  76%|███████▌  | 76/100 [00:02<00:00, 41.04it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 533.333} (0.083):  77%|███████▋  | 77/100 [00:02<00:00, 41.04it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 533.333} (0.083):  78%|███████▊  | 78/100 [00:02<00:00, 35.21it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.020 | Best: {'fx': 533.333} (0.083):  78%|███████▊  | 78/100 [00:02<00:00, 35.21it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.020 | Best: {'fx': 533.333} (0.083):  79%|███████▉  | 79/100 [00:02<00:00, 35.21it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 533.333} (0.083):  80%|████████  | 80/100 [00:02<00:00, 35.21it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 533.333} (0.083):  81%|████████  | 81/100 [00:02<00:00, 35.21it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 533.333} (0.083):  82%|████████▏ | 82/100 [00:02<00:00, 35.21it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.020 | Best: {'fx': 533.333} (0.083):  83%|████████▎ | 83/100 [00:02<00:00, 35.21it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 533.333} (0.083):  84%|████████▍ | 84/100 [00:03<00:00, 35.21it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 533.333} (0.083):  85%|████████▌ | 85/100 [00:03<00:00, 35.29it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 533.333} (0.083):  85%|████████▌ | 85/100 [00:03<00:00, 35.29it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 533.333} (0.083):  86%|████████▌ | 86/100 [00:03<00:00, 35.29it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 533.333} (0.083):  87%|████████▋ | 87/100 [00:03<00:00, 35.29it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 533.333} (0.083):  88%|████████▊ | 88/100 [00:03<00:00, 35.29it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 533.333} (0.083):  89%|████████▉ | 89/100 [00:03<00:00, 35.29it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 533.333} (0.083):  90%|█████████ | 90/100 [00:03<00:00, 35.29it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 533.333} (0.083):  91%|█████████ | 91/100 [00:03<00:00, 35.29it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 533.333} (0.083):  92%|█████████▏| 92/100 [00:03<00:00, 37.68it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 533.333} (0.083):  92%|█████████▏| 92/100 [00:03<00:00, 37.68it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 533.333} (0.083):  93%|█████████▎| 93/100 [00:03<00:00, 37.68it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.018 | Best: {'fx': 533.333} (0.083):  94%|█████████▍| 94/100 [00:03<00:00, 37.68it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 533.333} (0.083):  95%|█████████▌| 95/100 [00:03<00:00, 37.68it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 533.333} (0.083):  96%|█████████▌| 96/100 [00:03<00:00, 31.79it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.019 | Best: {'fx': 533.333} (0.083):  96%|█████████▌| 96/100 [00:03<00:00, 31.79it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.018 | Best: {'fx': 533.333} (0.083):  97%|█████████▋| 97/100 [00:03<00:00, 31.79it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.018 | Best: {'fx': 533.333} (0.083):  98%|█████████▊| 98/100 [00:03<00:00, 31.79it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.018 | Best: {'fx': 533.333} (0.083):  99%|█████████▉| 99/100 [00:03<00:00, 31.79it/s]
Brute | Start: {'fx': 500.0} (0.041) | Current: 0.018 | Best: {'fx': 533.333} (0.083): 100%|██████████| 100/100 [00:03<00:00, 32.95it/s]
                                                                                                                                        

  0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.050 | Best: {'fx': 508.333} (0.050):   0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.050 | Best: {'fx': 508.333} (0.050):   2%|▏         | 1/50 [00:00<00:25,  1.93it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.052 | Best: {'fx': 509.354} (0.052):   2%|▏         | 1/50 [00:00<00:25,  1.93it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.053 | Best: {'fx': 510.374} (0.053):   4%|▍         | 2/50 [00:00<00:24,  1.93it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.055 | Best: {'fx': 511.395} (0.055):   6%|▌         | 3/50 [00:00<00:24,  1.93it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.055 | Best: {'fx': 511.395} (0.055):   8%|▊         | 4/50 [00:00<00:05,  7.83it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.058 | Best: {'fx': 512.415} (0.058):   8%|▊         | 4/50 [00:00<00:05,  7.83it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.059 | Best: {'fx': 513.435} (0.059):  10%|█         | 5/50 [00:00<00:05,  7.83it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.063 | Best: {'fx': 515.476} (0.063):  12%|█▏        | 6/50 [00:00<00:05,  7.83it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.063 | Best: {'fx': 515.476} (0.063):  14%|█▍        | 7/50 [00:00<00:04,  9.77it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.066 | Best: {'fx': 517.517} (0.066):  14%|█▍        | 7/50 [00:00<00:04,  9.77it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.066 | Best: {'fx': 518.537} (0.066):  16%|█▌        | 8/50 [00:00<00:04,  9.77it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.061 | Best: {'fx': 518.537} (0.066):  18%|█▊        | 9/50 [00:00<00:04,  9.77it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.061 | Best: {'fx': 518.537} (0.066):  20%|██        | 10/50 [00:00<00:02, 13.74it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.067 | Best: {'fx': 519.558} (0.067):  20%|██        | 10/50 [00:00<00:02, 13.74it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.065 | Best: {'fx': 519.558} (0.067):  22%|██▏       | 11/50 [00:01<00:02, 13.74it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.069 | Best: {'fx': 521.599} (0.069):  24%|██▍       | 12/50 [00:01<00:02, 13.74it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.071 | Best: {'fx': 522.619} (0.071):  26%|██▌       | 13/50 [00:01<00:02, 13.74it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.071 | Best: {'fx': 522.619} (0.071):  28%|██▊       | 14/50 [00:01<00:01, 19.08it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.068 | Best: {'fx': 522.619} (0.071):  28%|██▊       | 14/50 [00:01<00:01, 19.08it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.073 | Best: {'fx': 524.66} (0.073):  30%|███       | 15/50 [00:01<00:01, 19.08it/s] 
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.077 | Best: {'fx': 525.68} (0.077):  32%|███▏      | 16/50 [00:01<00:01, 19.08it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.077 | Best: {'fx': 525.68} (0.077):  34%|███▍      | 17/50 [00:01<00:01, 19.82it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.073 | Best: {'fx': 525.68} (0.077):  34%|███▍      | 17/50 [00:01<00:01, 19.82it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.081 | Best: {'fx': 528.741} (0.081):  36%|███▌      | 18/50 [00:01<00:01, 19.82it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.077 | Best: {'fx': 528.741} (0.081):  38%|███▊      | 19/50 [00:01<00:01, 19.82it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.077 | Best: {'fx': 528.741} (0.081):  40%|████      | 20/50 [00:01<00:01, 21.04it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.079 | Best: {'fx': 528.741} (0.081):  40%|████      | 20/50 [00:01<00:01, 21.04it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.081 | Best: {'fx': 529.762} (0.081):  42%|████▏     | 21/50 [00:01<00:01, 21.04it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.082 | Best: {'fx': 531.803} (0.082):  44%|████▍     | 22/50 [00:01<00:01, 21.04it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.081 | Best: {'fx': 531.803} (0.082):  46%|████▌     | 23/50 [00:01<00:01, 21.04it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.081 | Best: {'fx': 531.803} (0.082):  48%|████▊     | 24/50 [00:01<00:01, 24.73it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.082 | Best: {'fx': 531.803} (0.082):  48%|████▊     | 24/50 [00:01<00:01, 24.73it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.083 | Best: {'fx': 533.844} (0.083):  50%|█████     | 25/50 [00:01<00:01, 24.73it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.075 | Best: {'fx': 533.844} (0.083):  52%|█████▏    | 26/50 [00:01<00:00, 24.73it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.075 | Best: {'fx': 533.844} (0.083):  54%|█████▍    | 27/50 [00:01<00:00, 24.97it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.072 | Best: {'fx': 533.844} (0.083):  54%|█████▍    | 27/50 [00:01<00:00, 24.97it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.081 | Best: {'fx': 533.844} (0.083):  56%|█████▌    | 28/50 [00:01<00:00, 24.97it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.079 | Best: {'fx': 533.844} (0.083):  58%|█████▊    | 29/50 [00:01<00:00, 24.97it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.071 | Best: {'fx': 533.844} (0.083):  60%|██████    | 30/50 [00:01<00:00, 24.97it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.071 | Best: {'fx': 533.844} (0.083):  62%|██████▏   | 31/50 [00:01<00:00, 28.31it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.067 | Best: {'fx': 533.844} (0.083):  62%|██████▏   | 31/50 [00:01<00:00, 28.31it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.070 | Best: {'fx': 533.844} (0.083):  64%|██████▍   | 32/50 [00:01<00:00, 28.31it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.072 | Best: {'fx': 533.844} (0.083):  66%|██████▌   | 33/50 [00:01<00:00, 28.31it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.081 | Best: {'fx': 533.844} (0.083):  68%|██████▊   | 34/50 [00:01<00:00, 28.31it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.077 | Best: {'fx': 533.844} (0.083):  70%|███████   | 35/50 [00:01<00:00, 28.31it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.068 | Best: {'fx': 533.844} (0.083):  72%|███████▏  | 36/50 [00:01<00:00, 28.31it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.064 | Best: {'fx': 533.844} (0.083):  74%|███████▍  | 37/50 [00:01<00:00, 28.31it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.065 | Best: {'fx': 533.844} (0.083):  76%|███████▌  | 38/50 [00:01<00:00, 28.31it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.065 | Best: {'fx': 533.844} (0.083):  78%|███████▊  | 39/50 [00:01<00:00, 41.92it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.061 | Best: {'fx': 533.844} (0.083):  78%|███████▊  | 39/50 [00:01<00:00, 41.92it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.078 | Best: {'fx': 533.844} (0.083):  80%|████████  | 40/50 [00:01<00:00, 41.92it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.060 | Best: {'fx': 533.844} (0.083):  82%|████████▏ | 41/50 [00:01<00:00, 41.92it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.059 | Best: {'fx': 533.844} (0.083):  84%|████████▍ | 42/50 [00:01<00:00, 41.92it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.062 | Best: {'fx': 533.844} (0.083):  86%|████████▌ | 43/50 [00:01<00:00, 41.92it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.062 | Best: {'fx': 533.844} (0.083):  88%|████████▊ | 44/50 [00:01<00:00, 43.29it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.057 | Best: {'fx': 533.844} (0.083):  88%|████████▊ | 44/50 [00:01<00:00, 43.29it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.055 | Best: {'fx': 533.844} (0.083):  90%|█████████ | 45/50 [00:01<00:00, 43.29it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.057 | Best: {'fx': 533.844} (0.083):  92%|█████████▏| 46/50 [00:01<00:00, 43.29it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.054 | Best: {'fx': 533.844} (0.083):  94%|█████████▍| 47/50 [00:02<00:00, 43.29it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.053 | Best: {'fx': 533.844} (0.083):  96%|█████████▌| 48/50 [00:02<00:00, 43.29it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.053 | Best: {'fx': 533.844} (0.083):  98%|█████████▊| 49/50 [00:02<00:00, 38.04it/s]
Brute | Start: {'fx': 533.333} (0.083) | Current: 0.052 | Best: {'fx': 533.844} (0.083):  98%|█████████▊| 49/50 [00:02<00:00, 38.04it/s]
                                                                                                                                        
[DEBUG] Parameters after Step 5 (before square optimization):
    fx: 533.3333333333334
    px: 863.0
    py: 995.0
    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 1 incomplete frames): 79 frames will be used for optimization
  Rigs: 2000L(2000mm):20/20, 2000R(2000mm):20/20, 1000(1000mm):20/20, 1500(1500mm):19/20
  Total: 79/80 frames used for optimization

Initial score: 51.0273: 0iter [00:00, ?iter/s][DEBUG] objective(x0) = 51.0273, picklable_objective(x0) = 51.0536

Best score: 51.0536: : 0iter [00:02, ?iter/s] 
Best score: 51.0536: : 1iter [00:02,  2.00s/iter]
Best score: 51.0536: : 1iter [00:02,  2.00s/iter]
Best score: 51.0536: : 2iter [00:02,  2.00s/iter]
Best score: 51.0536: : 3iter [00:02,  1.71iter/s]
Best score: 51.0536: : 3iter [00:02,  1.71iter/s]
Best score: 51.0536: : 4iter [00:02,  1.71iter/s]
Best score: 51.0536: : 5iter [00:02,  3.05iter/s]
Best score: 51.0536: : 5iter [00:02,  3.05iter/s]
Best score: 51.0536: : 6iter [00:02,  3.05iter/s]
Best score: 51.0536: : 7iter [00:02,  4.43iter/s]
Best score: 51.0536: : 7iter [00:02,  4.43iter/s]
Best score: 51.0536: : 8iter [00:02,  4.43iter/s]
Best score: 51.0536: : 9iter [00:02,  5.76iter/s]
Best score: 51.0536: : 9iter [00:02,  5.76iter/s]
Best score: 51.0536: : 10iter [00:02,  5.76iter/s]
Best score: 51.0536: : 11iter [00:02,  6.93iter/s]
Best score: 51.0536: : 11iter [00:02,  6.93iter/s]
Best score: 51.0536: : 12iter [00:03,  6.93iter/s]
Best score: 51.0536: : 13iter [00:03,  8.00iter/s]
Best score: 51.0536: : 13iter [00:03,  8.00iter/s]
Best score: 51.0536: : 14iter [00:03,  8.00iter/s]
Best score: 51.0536: : 15iter [00:03,  8.87iter/s]
Best score: 51.0536: : 15iter [00:03,  8.87iter/s]
Best score: 51.0536: : 16iter [00:03,  8.87iter/s]
Best score: 51.0536: : 17iter [00:03,  9.60iter/s]
Best score: 51.0536: : 17iter [00:03,  9.60iter/s]
Best score: 51.0536: : 18iter [00:03,  9.60iter/s]
Best score: 51.0536: : 19iter [00:03, 10.15iter/s]
Best score: 51.0536: : 19iter [00:03, 10.15iter/s]
Best score: 51.0536: : 20iter [00:03, 10.15iter/s]
Best score: 51.0536: : 21iter [00:03, 10.41iter/s]
Best score: 51.0536: : 21iter [00:03, 10.41iter/s]
Best score: 51.0536: : 22iter [00:03, 10.41iter/s]
Best score: 51.0536: : 23iter [00:03, 10.74iter/s]
Best score: 51.0536: : 23iter [00:04, 10.74iter/s]
Best score: 51.0536: : 24iter [00:04, 10.74iter/s]
Best score: 51.0536: : 25iter [00:04, 10.98iter/s]
Best score: 51.0536: : 25iter [00:04, 10.98iter/s]
Best score: 51.0536: : 26iter [00:04, 10.98iter/s]
Best score: 51.0536: : 27iter [00:04, 11.15iter/s]
Best score: 51.0536: : 27iter [00:04, 11.15iter/s]
Best score: 51.0536: : 28iter [00:04, 11.15iter/s]
Best score: 51.0536: : 29iter [00:04, 11.29iter/s]
Best score: 51.0536: : 29iter [00:04, 11.29iter/s]
Best score: 51.0536: : 30iter [00:04, 11.29iter/s]
Best score: 51.0536: : 31iter [00:04, 11.27iter/s]
Best score: 51.0536: : 31iter [00:04, 11.27iter/s]
Best score: 51.0536: : 32iter [00:04, 11.27iter/s]
Best score: 51.0536: : 33iter [00:04, 11.38iter/s]
Best score: 51.0536: : 33iter [00:04, 11.38iter/s]
Best score: 51.0536: : 34iter [00:04, 11.38iter/s]
Best score: 51.0536: : 35iter [00:04, 11.48iter/s]
Best score: 51.0536: : 35iter [00:05, 11.48iter/s]
Best score: 51.0536: : 36iter [00:05, 11.48iter/s]
Best score: 51.0536: : 37iter [00:05, 11.52iter/s]
Best score: 51.0536: : 37iter [00:05, 11.52iter/s]
Best score: 51.0536: : 38iter [00:05, 11.52iter/s]
Best score: 51.0536: : 39iter [00:05, 11.63iter/s]
Best score: 51.0536: : 39iter [00:05, 11.63iter/s]
Best score: 51.0536: : 40iter [00:05, 11.63iter/s]
Best score: 51.0536: : 41iter [00:05, 11.50iter/s]
Best score: 51.0536: : 41iter [00:05, 11.50iter/s]
Best score: 51.0536: : 42iter [00:05, 11.50iter/s]
Best score: 51.0536: : 43iter [00:05, 11.59iter/s]
Best score: 51.0536: : 43iter [00:05, 11.59iter/s]
Best score: 51.0536: : 44iter [00:05, 11.59iter/s]
Best score: 51.0536: : 45iter [00:05, 11.59iter/s]
Best score: 51.0536: : 45iter [00:05, 11.59iter/s]
Best score: 51.0536: : 46iter [00:05, 11.59iter/s]
Best score: 51.0536: : 47iter [00:05, 11.63iter/s]
Best score: 51.0536: : 47iter [00:06, 11.63iter/s]
Best score: 51.0536: : 48iter [00:06, 11.63iter/s]
Best score: 51.0536: : 49iter [00:06, 11.65iter/s]
[ITER 50] Best: 6.0001
[PARAMS] Current best parameters:
  fx: 506.5168
  fy: 505.0106
  px: 850.3754
  py: 1006.0491
  k1: 0.01241682
  k2: 0.01340621
  k3: -0.00172256
  k4: -0.00226655
  p1: -0.00099506
  p2: 0.00312623
  p3: 0.00858139
  p4: -0.01348212
  s1: -0.0044
  s2: -0.0105
  s3: 0.0056
  s4: 0.0072
  tilt_x: 0.0127
  tilt_y: 0.0043
  scale: 3.0811
  rotation: -0.9773

Best score: 6.0001: : 49iter [00:06, 11.65iter/s] 
Best score: 6.0001: : 50iter [00:06, 11.65iter/s]
Best score: 6.0001: : 51iter [00:06, 11.49iter/s]
Best score: 6.0001: : 51iter [00:06, 11.49iter/s]
Best score: 6.0001: : 52iter [00:06, 11.49iter/s]
Best score: 6.0001: : 53iter [00:06, 11.53iter/s]
Best score: 6.0001: : 53iter [00:06, 11.53iter/s]
Best score: 6.0001: : 54iter [00:06, 11.53iter/s]
Best score: 6.0001: : 55iter [00:06, 11.62iter/s]
Best score: 6.0001: : 55iter [00:06, 11.62iter/s]
Best score: 6.0001: : 56iter [00:06, 11.62iter/s]
Best score: 6.0001: : 57iter [00:06, 11.68iter/s]
Best score: 6.0001: : 57iter [00:06, 11.68iter/s]
Best score: 6.0001: : 58iter [00:07, 11.68iter/s]
Best score: 6.0001: : 59iter [00:07, 11.72iter/s]
Best score: 6.0001: : 59iter [00:07, 11.72iter/s]
Best score: 6.0001: : 60iter [00:07, 11.72iter/s]
Best score: 6.0001: : 61iter [00:07, 11.56iter/s]
Best score: 6.0001: : 61iter [00:07, 11.56iter/s]
Best score: 6.0001: : 62iter [00:07, 11.56iter/s]
Best score: 6.0001: : 63iter [00:07, 11.66iter/s]
Best score: 6.0001: : 63iter [00:07, 11.66iter/s]
Best score: 6.0001: : 64iter [00:07, 11.66iter/s]
Best score: 6.0001: : 65iter [00:07, 11.73iter/s]
Best score: 6.0001: : 65iter [00:07, 11.73iter/s]
Best score: 6.0001: : 66iter [00:07, 11.73iter/s]
Best score: 6.0001: : 67iter [00:07, 11.74iter/s]
Best score: 6.0001: : 67iter [00:07, 11.74iter/s]
Best score: 6.0001: : 68iter [00:07, 11.74iter/s]
Best score: 6.0001: : 69iter [00:07, 11.72iter/s]
Best score: 6.0001: : 69iter [00:07, 11.72iter/s]
Best score: 6.0001: : 70iter [00:08, 11.72iter/s]
Best score: 6.0001: : 71iter [00:08, 11.51iter/s]
Best score: 6.0001: : 71iter [00:08, 11.51iter/s]
Best score: 6.0001: : 72iter [00:08, 11.51iter/s]
Best score: 6.0001: : 73iter [00:08, 11.64iter/s]
Best score: 6.0001: : 73iter [00:08, 11.64iter/s]
Best score: 6.0001: : 74iter [00:08, 11.64iter/s]
Best score: 6.0001: : 75iter [00:08, 11.69iter/s]
Best score: 6.0001: : 75iter [00:08, 11.69iter/s]
Best score: 6.0001: : 76iter [00:08, 11.69iter/s]
Best score: 6.0001: : 77iter [00:08, 11.73iter/s]
Best score: 6.0001: : 77iter [00:08, 11.73iter/s]
Best score: 6.0001: : 78iter [00:08, 11.73iter/s]
Best score: 6.0001: : 79iter [00:08, 11.77iter/s]
Best score: 4.6433: : 79iter [00:08, 11.77iter/s]
Best score: 4.6433: : 80iter [00:08, 11.77iter/s]
Best score: 4.6433: : 81iter [00:08, 11.57iter/s]
Best score: 4.6433: : 81iter [00:08, 11.57iter/s]
Best score: 4.6433: : 82iter [00:09, 11.57iter/s]
Best score: 4.6433: : 83iter [00:09, 11.65iter/s]
Best score: 4.6433: : 83iter [00:09, 11.65iter/s]
Best score: 4.6433: : 84iter [00:09, 11.65iter/s]
Best score: 4.6433: : 85iter [00:09, 11.68iter/s]
Best score: 4.6433: : 85iter [00:09, 11.68iter/s]
Best score: 4.6433: : 86iter [00:09, 11.68iter/s]
Best score: 4.6433: : 87iter [00:09, 11.71iter/s]
Best score: 4.6433: : 87iter [00:09, 11.71iter/s]
Best score: 4.6433: : 88iter [00:09, 11.71iter/s]
Best score: 4.6433: : 89iter [00:09, 11.73iter/s]
Best score: 4.6433: : 89iter [00:09, 11.73iter/s]
Best score: 4.6433: : 90iter [00:09, 11.73iter/s]
Best score: 4.6433: : 91iter [00:09, 11.56iter/s]
Best score: 4.6433: : 91iter [00:09, 11.56iter/s]
Best score: 4.6433: : 92iter [00:09, 11.56iter/s]
Best score: 4.6433: : 93iter [00:09, 11.64iter/s]
Best score: 4.6433: : 93iter [00:10, 11.64iter/s]
Best score: 4.6433: : 94iter [00:10, 11.64iter/s]
Best score: 4.6433: : 95iter [00:10, 11.72iter/s]
Best score: 4.6433: : 95iter [00:10, 11.72iter/s]
Best score: 4.6433: : 96iter [00:10, 11.72iter/s]
Best score: 4.6433: : 97iter [00:10, 11.75iter/s]
Best score: 4.6433: : 97iter [00:10, 11.75iter/s]
Best score: 4.6433: : 98iter [00:10, 11.75iter/s]
Best score: 4.6433: : 99iter [00:10, 11.78iter/s]
[ITER 100] Best: 1.9156
[PARAMS] Current best parameters:
  fx: 496.0242
  fy: 496.0838
  px: 863.2426
  py: 1005.5233
  k1: 0.01564366
  k2: 0.01723832
  k3: 0.00188770
  k4: -0.00444357
  p1: -0.00867168
  p2: 0.01556392
  p3: 0.00186877
  p4: -0.00635298
  s1: -0.0027
  s2: -0.0040
  s3: 0.0060
  s4: 0.0147
  tilt_x: 0.0264
  tilt_y: -0.0210
  scale: 3.0944
  rotation: -0.0881

Best score: 1.9156: : 99iter [00:10, 11.78iter/s]
Best score: 1.9156: : 100iter [00:10, 11.78iter/s]
Best score: 1.9156: : 101iter [00:10, 10.08iter/s]
Best score: 1.9156: : 101iter [00:10, 10.08iter/s]
Best score: 1.9156: : 102iter [00:10, 10.08iter/s]
Best score: 1.9156: : 103iter [00:10, 10.45iter/s]
Best score: 1.9156: : 103iter [00:10, 10.45iter/s]
Best score: 1.9156: : 104iter [00:11, 10.45iter/s]
Best score: 1.9156: : 105iter [00:11, 10.73iter/s]
Best score: 1.9156: : 105iter [00:11, 10.73iter/s]
Best score: 1.9156: : 106iter [00:11, 10.73iter/s]
Best score: 1.9156: : 107iter [00:11, 10.93iter/s]
Best score: 1.9156: : 107iter [00:11, 10.93iter/s]
Best score: 1.9156: : 108iter [00:11, 10.93iter/s]
Best score: 1.9156: : 109iter [00:11, 11.09iter/s]
Best score: 1.9156: : 109iter [00:11, 11.09iter/s]
Best score: 1.9156: : 110iter [00:11, 11.09iter/s]
Best score: 1.9156: : 111iter [00:11, 11.01iter/s]
Best score: 1.9156: : 111iter [00:11, 11.01iter/s]
Best score: 1.9156: : 112iter [00:11, 11.01iter/s]
Best score: 1.9156: : 113iter [00:11, 11.15iter/s]
Best score: 1.9156: : 113iter [00:11, 11.15iter/s]
Best score: 1.9156: : 114iter [00:11, 11.15iter/s]
Best score: 1.9156: : 115iter [00:11, 11.25iter/s]
Best score: 1.9156: : 115iter [00:12, 11.25iter/s]
Best score: 1.9156: : 116iter [00:12, 11.25iter/s]
Best score: 1.9156: : 117iter [00:12, 11.30iter/s]
Best score: 1.9156: : 117iter [00:12, 11.30iter/s]
Best score: 1.9156: : 118iter [00:12, 11.30iter/s]
Best score: 1.9156: : 119iter [00:12, 11.36iter/s]
Best score: 1.9156: : 119iter [00:12, 11.36iter/s]
Best score: 1.9156: : 120iter [00:12, 11.36iter/s]
Best score: 1.9156: : 121iter [00:12, 11.26iter/s]
Best score: 1.9156: : 121iter [00:12, 11.26iter/s]
Best score: 1.9156: : 122iter [00:12, 11.26iter/s]
Best score: 1.9156: : 123iter [00:12, 11.34iter/s]
Best score: 1.9156: : 123iter [00:12, 11.34iter/s]
Best score: 1.9156: : 124iter [00:12, 11.34iter/s]
Best score: 1.9156: : 125iter [00:12, 11.45iter/s]
Best score: 1.9156: : 125iter [00:12, 11.45iter/s]
Best score: 1.9156: : 126iter [00:12, 11.45iter/s]
Best score: 1.9156: : 127iter [00:12, 11.46iter/s]
Best score: 1.9156: : 127iter [00:13, 11.46iter/s]
Best score: 1.9156: : 128iter [00:13, 11.46iter/s]
Best score: 1.9156: : 129iter [00:13, 11.53iter/s]
Best score: 1.9156: : 129iter [00:13, 11.53iter/s]
Best score: 1.9156: : 130iter [00:13, 11.53iter/s]
Best score: 1.9156: : 131iter [00:13, 11.38iter/s]
Best score: 1.9156: : 131iter [00:13, 11.38iter/s]
Best score: 1.9156: : 132iter [00:13, 11.38iter/s]
Best score: 1.9156: : 133iter [00:13, 11.54iter/s]
Best score: 1.9156: : 133iter [00:13, 11.54iter/s]
Best score: 1.9156: : 134iter [00:13, 11.54iter/s]
Best score: 1.9156: : 135iter [00:13, 11.56iter/s]
Best score: 1.9156: : 135iter [00:13, 11.56iter/s]
Best score: 1.9156: : 136iter [00:13, 11.56iter/s]
Best score: 1.9156: : 137iter [00:13, 11.63iter/s]
Best score: 1.9156: : 137iter [00:13, 11.63iter/s]
Best score: 1.9156: : 138iter [00:14, 11.63iter/s]
Best score: 1.9156: : 139iter [00:14, 11.64iter/s]
Best score: 1.9156: : 139iter [00:14, 11.64iter/s]
Best score: 1.9156: : 140iter [00:14, 11.64iter/s]
Best score: 1.9156: : 141iter [00:14, 11.46iter/s]
Best score: 1.9156: : 141iter [00:14, 11.46iter/s]
Best score: 1.9156: : 142iter [00:14, 11.46iter/s]
Best score: 1.9156: : 143iter [00:14, 11.59iter/s]
Best score: 1.9156: : 143iter [00:14, 11.59iter/s]
Best score: 1.9156: : 144iter [00:14, 11.59iter/s]
Best score: 1.9156: : 145iter [00:14, 11.66iter/s]
Best score: 1.9156: : 145iter [00:14, 11.66iter/s]
Best score: 1.9156: : 146iter [00:14, 11.66iter/s]
Best score: 1.9156: : 147iter [00:14, 11.66iter/s]
Best score: 1.9156: : 147iter [00:14, 11.66iter/s]
Best score: 1.9156: : 148iter [00:14, 11.66iter/s]
Best score: 1.9156: : 149iter [00:14, 11.64iter/s]
[ITER 150] Best: 1.9156
[PARAMS] Current best parameters:
  fx: 496.0242
  fy: 496.0838
  px: 863.2426
  py: 1005.5233
  k1: 0.01564366
  k2: 0.01723832
  k3: 0.00188770
  k4: -0.00444357
  p1: -0.00867168
  p2: 0.01556392
  p3: 0.00186877
  p4: -0.00635298
  s1: -0.0027
  s2: -0.0040
  s3: 0.0060
  s4: 0.0147
  tilt_x: 0.0264
  tilt_y: -0.0210
  scale: 3.0944
  rotation: -0.0881

Best score: 1.9156: : 149iter [00:14, 11.64iter/s]
Best score: 1.9156: : 150iter [00:15, 11.64iter/s]
Best score: 1.9156: : 151iter [00:15,  7.57iter/s]
Best score: 1.9156: : 151iter [00:15,  7.57iter/s]
Best score: 1.9156: : 152iter [00:15,  7.57iter/s]
Best score: 1.9156: : 153iter [00:15,  8.49iter/s]
Best score: 1.9156: : 153iter [00:15,  8.49iter/s]
Best score: 1.9156: : 154iter [00:15,  8.49iter/s]
Best score: 1.9156: : 155iter [00:15,  9.29iter/s]
Best score: 1.9156: : 155iter [00:15,  9.29iter/s]
Best score: 1.9156: : 156iter [00:15,  9.29iter/s]
Best score: 1.9156: : 157iter [00:15,  9.88iter/s]
Best score: 1.9156: : 157iter [00:15,  9.88iter/s]
Best score: 1.9156: : 158iter [00:16,  9.88iter/s]
Best score: 1.9156: : 159iter [00:16, 10.36iter/s]
Best score: 1.9156: : 159iter [00:16, 10.36iter/s]
Best score: 1.9156: : 160iter [00:16, 10.36iter/s]
Best score: 1.9156: : 161iter [00:16, 10.62iter/s]
Best score: 1.9156: : 161iter [00:16, 10.62iter/s]
Best score: 1.9156: : 162iter [00:16, 10.62iter/s]
Best score: 1.9156: : 163iter [00:16, 10.92iter/s]
Best score: 1.9156: : 163iter [00:16, 10.92iter/s]
Best score: 1.9156: : 164iter [00:16, 10.92iter/s]
Best score: 1.9156: : 165iter [00:16, 11.14iter/s]
Best score: 1.9156: : 165iter [00:16, 11.14iter/s]
Best score: 1.9156: : 166iter [00:16, 11.14iter/s]
Best score: 1.9156: : 167iter [00:16, 11.33iter/s]
Best score: 1.9156: : 167iter [00:16, 11.33iter/s]
Best score: 1.9156: : 168iter [00:16, 11.33iter/s]
Best score: 1.9156: : 169iter [00:16, 11.47iter/s]
Best score: 1.9156: : 169iter [00:16, 11.47iter/s]
Best score: 1.9156: : 170iter [00:17, 11.47iter/s]
Best score: 1.9156: : 171iter [00:17, 11.41iter/s]
Best score: 1.9156: : 171iter [00:17, 11.41iter/s]
Best score: 1.9156: : 172iter [00:17, 11.41iter/s]
Best score: 1.9156: : 173iter [00:17, 11.57iter/s]
Best score: 1.9156: : 173iter [00:17, 11.57iter/s]
Best score: 1.9156: : 174iter [00:17, 11.57iter/s]
Best score: 1.9156: : 175iter [00:17,  9.10iter/s]
Best score: 1.9156: : 175iter [00:17,  9.10iter/s]
Best score: 1.9156: : 176iter [00:17,  9.10iter/s]
Best score: 1.9156: : 177iter [00:17,  9.79iter/s]
Best score: 1.9156: : 177iter [00:17,  9.79iter/s]
Best score: 1.9156: : 178iter [00:17,  9.79iter/s]
Best score: 1.9156: : 179iter [00:17, 10.30iter/s]
Best score: 1.9156: : 179iter [00:18, 10.30iter/s]
Best score: 1.9156: : 180iter [00:18, 10.30iter/s]
Best score: 1.9156: : 181iter [00:18, 10.52iter/s]
Best score: 1.9156: : 181iter [00:18, 10.52iter/s]
Best score: 1.9156: : 182iter [00:18, 10.52iter/s]
Best score: 1.9156: : 183iter [00:18, 10.89iter/s]
Best score: 1.9156: : 183iter [00:18, 10.89iter/s]
Best score: 1.9156: : 184iter [00:18, 10.89iter/s]
Best score: 1.9156: : 185iter [00:18, 11.20iter/s]
Best score: 1.9156: : 185iter [00:18, 11.20iter/s]
Best score: 1.9156: : 186iter [00:18, 11.20iter/s]
Best score: 1.9156: : 187iter [00:18, 11.42iter/s]
Best score: 1.9156: : 187iter [00:18, 11.42iter/s]
Best score: 1.9156: : 188iter [00:18, 11.42iter/s]
Best score: 1.9156: : 189iter [00:18, 11.57iter/s]
Best score: 1.6786: : 189iter [00:18, 11.57iter/s]
Best score: 1.6786: : 190iter [00:18, 11.57iter/s]
Best score: 1.6786: : 191iter [00:18, 11.43iter/s]
Best score: 1.6786: : 191iter [00:19, 11.43iter/s]
Best score: 1.6786: : 192iter [00:19, 11.43iter/s]
Best score: 1.6786: : 193iter [00:19, 11.58iter/s]
Best score: 1.6786: : 193iter [00:19, 11.58iter/s]
Best score: 1.6786: : 194iter [00:19, 11.58iter/s]
Best score: 1.6786: : 195iter [00:19, 11.66iter/s]
Best score: 1.6786: : 195iter [00:19, 11.66iter/s]
Best score: 1.6786: : 196iter [00:19, 11.66iter/s]
Best score: 1.6786: : 197iter [00:19, 11.73iter/s]
Best score: 1.6786: : 197iter [00:19, 11.73iter/s]
Best score: 1.6786: : 198iter [00:19, 11.73iter/s]
Best score: 1.6786: : 199iter [00:19, 11.80iter/s]
[ITER 200] Best: 1.3868
[PARAMS] Current best parameters:
  fx: 487.6896
  fy: 487.2582
  px: 865.2564
  py: 1007.3980
  k1: 0.06280047
  k2: -0.02811117
  k3: 0.01642357
  k4: -0.00451431
  p1: -0.01659798
  p2: 0.00624632
  p3: 0.00397609
  p4: -0.01045875
  s1: -0.0022
  s2: 0.0091
  s3: 0.0320
  s4: 0.0008
  tilt_x: 0.0537
  tilt_y: -0.0403
  scale: 3.0516
  rotation: -0.1070

Best score: 1.3868: : 199iter [00:19, 11.80iter/s]
Best score: 1.3868: : 200iter [00:20, 11.80iter/s]
Best score: 1.3868: : 201iter [00:20,  7.59iter/s]
Best score: 1.3868: : 201iter [00:20,  7.59iter/s]
Best score: 1.3868: : 202iter [00:20,  7.59iter/s]
Best score: 1.3868: : 203iter [00:20,  8.48iter/s]
Best score: 1.3868: : 203iter [00:20,  8.48iter/s]
Best score: 1.3868: : 204iter [00:20,  8.48iter/s]
Best score: 1.3868: : 205iter [00:20,  9.28iter/s]
Best score: 1.3868: : 205iter [00:20,  9.28iter/s]
Best score: 1.3868: : 206iter [00:20,  9.28iter/s]
Best score: 1.3868: : 207iter [00:20,  9.94iter/s]
Best score: 1.3868: : 207iter [00:20,  9.94iter/s]
Best score: 1.3868: : 208iter [00:20,  9.94iter/s]
Best score: 1.3868: : 209iter [00:20, 10.44iter/s]
Best score: 1.3868: : 209iter [00:20, 10.44iter/s]
Best score: 1.3868: : 210iter [00:20, 10.44iter/s]
Best score: 1.3868: : 211iter [00:20, 10.62iter/s]
Best score: 1.3868: : 211iter [00:21, 10.62iter/s]
Best score: 1.3868: : 212iter [00:21, 10.62iter/s]
Best score: 1.3868: : 213iter [00:21, 10.90iter/s]
Best score: 1.3868: : 213iter [00:21, 10.90iter/s]
Best score: 1.3868: : 214iter [00:21, 10.90iter/s]
Best score: 1.3868: : 215iter [00:21, 11.14iter/s]
Best score: 1.3868: : 215iter [00:21, 11.14iter/s]
Best score: 1.3868: : 216iter [00:21, 11.14iter/s]
Best score: 1.3868: : 217iter [00:21, 11.34iter/s]
Best score: 1.3868: : 217iter [00:21, 11.34iter/s]
Best score: 1.3868: : 218iter [00:21, 11.34iter/s]
Best score: 1.3868: : 219iter [00:21, 11.50iter/s]
Best score: 1.0755: : 219iter [00:21, 11.50iter/s]
Best score: 1.0755: : 220iter [00:21, 11.50iter/s]
Best score: 1.0755: : 221iter [00:21, 11.42iter/s]
Best score: 1.0755: : 221iter [00:21, 11.42iter/s]
Best score: 1.0755: : 222iter [00:21, 11.42iter/s]
Best score: 1.0755: : 223iter [00:21, 11.54iter/s]
Best score: 1.0755: : 223iter [00:22, 11.54iter/s]
Best score: 1.0755: : 224iter [00:22, 11.54iter/s]
Best score: 1.0755: : 225iter [00:22, 11.62iter/s]
Best score: 1.0755: : 225iter [00:22, 11.62iter/s]
Best score: 1.0755: : 226iter [00:22, 11.62iter/s]
Best score: 1.0755: : 227iter [00:22, 11.70iter/s]
Best score: 1.0755: : 227iter [00:22, 11.70iter/s]
Best score: 1.0755: : 228iter [00:22, 11.70iter/s]
Best score: 1.0755: : 229iter [00:22, 11.75iter/s]
Best score: 1.0277: : 229iter [00:22, 11.75iter/s]
Best score: 1.0277: : 230iter [00:22, 11.75iter/s]
Best score: 1.0277: : 231iter [00:22, 11.56iter/s]
Best score: 1.0277: : 231iter [00:22, 11.56iter/s]
Best score: 1.0277: : 232iter [00:22, 11.56iter/s]
Best score: 1.0277: : 233iter [00:22, 11.66iter/s]
Best score: 1.0277: : 233iter [00:22, 11.66iter/s]
Best score: 1.0277: : 234iter [00:23, 11.66iter/s]
Best score: 1.0277: : 235iter [00:23, 11.71iter/s]
Best score: 1.0277: : 235iter [00:23, 11.71iter/s]
Best score: 1.0277: : 236iter [00:23, 11.71iter/s]
Best score: 1.0277: : 237iter [00:23, 11.76iter/s]
Best score: 1.0277: : 237iter [00:23, 11.76iter/s]
Best score: 1.0277: : 238iter [00:23, 11.76iter/s]
Best score: 1.0277: : 239iter [00:23, 11.80iter/s]
Best score: 1.0277: : 239iter [00:23, 11.80iter/s]
Best score: 1.0277: : 240iter [00:23, 11.80iter/s]
Best score: 1.0277: : 241iter [00:23, 11.59iter/s]
Best score: 1.0277: : 241iter [00:23, 11.59iter/s]
Best score: 1.0277: : 242iter [00:23, 11.59iter/s]
Best score: 1.0277: : 243iter [00:23, 11.68iter/s]
Best score: 1.0277: : 243iter [00:23, 11.68iter/s]
Best score: 1.0277: : 244iter [00:23, 11.68iter/s]
Best score: 1.0277: : 245iter [00:23, 11.74iter/s]
Best score: 1.0277: : 245iter [00:23, 11.74iter/s]
Best score: 1.0277: : 246iter [00:24, 11.74iter/s]
Best score: 1.0277: : 247iter [00:24, 11.73iter/s]
Best score: 1.0277: : 247iter [00:24, 11.73iter/s]
Best score: 1.0277: : 248iter [00:24, 11.73iter/s]
Best score: 1.0277: : 249iter [00:24, 11.79iter/s]
[ITER 250] Best: 0.7234
[PARAMS] Current best parameters:
  fx: 473.0527
  fy: 473.0694
  px: 869.3573
  py: 1007.8528
  k1: 0.05954575
  k2: -0.01343908
  k3: 0.01753813
  k4: -0.00697546
  p1: -0.01175338
  p2: 0.01242560
  p3: 0.00355077
  p4: -0.00671599
  s1: -0.0065
  s2: 0.0063
  s3: 0.0087
  s4: 0.0106
  tilt_x: 0.0456
  tilt_y: -0.0416
  scale: 3.0747
  rotation: -0.5769

Best score: 0.7234: : 249iter [00:24, 11.79iter/s]
Best score: 0.7234: : 250iter [00:24, 11.79iter/s]
Best score: 0.7234: : 251iter [00:24,  7.63iter/s]
Best score: 0.7234: : 251iter [00:24,  7.63iter/s]
Best score: 0.7234: : 252iter [00:24,  7.63iter/s]
Best score: 0.7234: : 253iter [00:24,  8.52iter/s]
Best score: 0.7234: : 253iter [00:24,  8.52iter/s]
Best score: 0.7234: : 254iter [00:25,  8.52iter/s]
Best score: 0.7234: : 255iter [00:25,  9.32iter/s]
Best score: 0.7234: : 255iter [00:25,  9.32iter/s]
Best score: 0.7234: : 256iter [00:25,  9.32iter/s]
Best score: 0.7234: : 257iter [00:25,  9.93iter/s]
Best score: 0.7234: : 257iter [00:25,  9.93iter/s]
Best score: 0.7234: : 258iter [00:25,  9.93iter/s]
Best score: 0.7234: : 259iter [00:25, 10.41iter/s]
Best score: 0.7234: : 259iter [00:25, 10.41iter/s]
Best score: 0.7234: : 260iter [00:25, 10.41iter/s]
Best score: 0.7234: : 261iter [00:25, 10.65iter/s]
Best score: 0.7234: : 261iter [00:25, 10.65iter/s]
Best score: 0.7234: : 262iter [00:25, 10.65iter/s]
Best score: 0.7234: : 263iter [00:25, 11.00iter/s]
Best score: 0.7234: : 263iter [00:25, 11.00iter/s]
Best score: 0.7234: : 264iter [00:25, 11.00iter/s]
Best score: 0.7234: : 265iter [00:25, 11.26iter/s]
Best score: 0.7234: : 265iter [00:25, 11.26iter/s]
Best score: 0.7234: : 266iter [00:26, 11.26iter/s]
Best score: 0.7234: : 267iter [00:26, 11.44iter/s]
Best score: 0.7234: : 267iter [00:26, 11.44iter/s]
Best score: 0.7234: : 268iter [00:26, 11.44iter/s]
Best score: 0.7234: : 269iter [00:26, 11.58iter/s]
Best score: 0.6798: : 269iter [00:26, 11.58iter/s]
Best score: 0.6798: : 270iter [00:26, 11.58iter/s]
Best score: 0.6798: : 271iter [00:26, 11.47iter/s]
Best score: 0.6798: : 271iter [00:26, 11.47iter/s]
Best score: 0.6798: : 272iter [00:26, 11.47iter/s]
Best score: 0.6798: : 273iter [00:26, 11.60iter/s]
Best score: 0.6798: : 273iter [00:26, 11.60iter/s]
Best score: 0.6798: : 274iter [00:26, 11.60iter/s]
Best score: 0.6798: : 275iter [00:26, 11.64iter/s]
Best score: 0.6798: : 275iter [00:26, 11.64iter/s]
Best score: 0.6798: : 276iter [00:26, 11.64iter/s]
Best score: 0.6798: : 277iter [00:26, 11.67iter/s]
Best score: 0.6798: : 277iter [00:26, 11.67iter/s]
Best score: 0.6798: : 278iter [00:27, 11.67iter/s]
Best score: 0.6798: : 279iter [00:27, 11.72iter/s]
Best score: 0.6798: : 279iter [00:27, 11.72iter/s]
Best score: 0.6798: : 280iter [00:27, 11.72iter/s]
Best score: 0.6798: : 281iter [00:27, 11.57iter/s]
Best score: 0.6798: : 281iter [00:27, 11.57iter/s]
Best score: 0.6798: : 282iter [00:27, 11.57iter/s]
Best score: 0.6798: : 283iter [00:27, 11.64iter/s]
Best score: 0.6798: : 283iter [00:27, 11.64iter/s]
Best score: 0.6798: : 284iter [00:27, 11.64iter/s]
Best score: 0.6798: : 285iter [00:27, 11.72iter/s]
Best score: 0.6798: : 285iter [00:27, 11.72iter/s]
Best score: 0.6798: : 286iter [00:27, 11.72iter/s]
Best score: 0.6798: : 287iter [00:27, 11.76iter/s]
Best score: 0.6798: : 287iter [00:27, 11.76iter/s]
Best score: 0.6798: : 288iter [00:27, 11.76iter/s]
Best score: 0.6798: : 289iter [00:27, 11.72iter/s]
Best score: 0.6288: : 289iter [00:28, 11.72iter/s]
Best score: 0.6288: : 290iter [00:28, 11.72iter/s]
Best score: 0.6288: : 291iter [00:28, 11.56iter/s]
Best score: 0.6288: : 291iter [00:28, 11.56iter/s]
Best score: 0.6288: : 292iter [00:28, 11.56iter/s]
Best score: 0.6288: : 293iter [00:28, 11.66iter/s]
Best score: 0.6288: : 293iter [00:28, 11.66iter/s]
Best score: 0.6288: : 294iter [00:28, 11.66iter/s]
Best score: 0.6288: : 295iter [00:28, 11.75iter/s]
Best score: 0.6288: : 295iter [00:28, 11.75iter/s]
Best score: 0.6288: : 296iter [00:28, 11.75iter/s]
Best score: 0.6288: : 297iter [00:28, 11.71iter/s]
Best score: 0.6288: : 297iter [00:28, 11.71iter/s]
Best score: 0.6288: : 298iter [00:28, 11.71iter/s]
Best score: 0.6288: : 299iter [00:28, 11.77iter/s]
[ITER 300] Best: 0.4439
[PARAMS] Current best parameters:
  fx: 473.7701
  fy: 472.7378
  px: 871.8679
  py: 1003.5974
  k1: 0.06588774
  k2: -0.00843862
  k3: 0.00760606
  k4: -0.00392432
  p1: -0.01617609
  p2: 0.00928314
  p3: 0.00738252
  p4: -0.00795300
  s1: -0.0063
  s2: 0.0094
  s3: 0.0167
  s4: 0.0042
  tilt_x: 0.0363
  tilt_y: -0.0624
  scale: 3.0595
  rotation: -0.5263

Best score: 0.4439: : 299iter [00:28, 11.77iter/s]
Best score: 0.4439: : 300iter [00:29, 11.77iter/s]
Best score: 0.4439: : 301iter [00:29,  7.61iter/s]
Best score: 0.4439: : 301iter [00:29,  7.61iter/s]
Best score: 0.4439: : 302iter [00:29,  7.61iter/s]
Best score: 0.4439: : 303iter [00:29,  8.54iter/s]
Best score: 0.4439: : 303iter [00:29,  8.54iter/s]
Best score: 0.4439: : 304iter [00:29,  8.54iter/s]
Best score: 0.4439: : 305iter [00:29,  9.32iter/s]
Best score: 0.4439: : 305iter [00:29,  9.32iter/s]
Best score: 0.4439: : 306iter [00:29,  9.32iter/s]
Best score: 0.4439: : 307iter [00:29,  9.94iter/s]
Best score: 0.4439: : 307iter [00:29,  9.94iter/s]
Best score: 0.4439: : 308iter [00:29,  9.94iter/s]
Best score: 0.4439: : 309iter [00:29, 10.39iter/s]
Best score: 0.4439: : 309iter [00:30, 10.39iter/s]
Best score: 0.4439: : 310iter [00:30, 10.39iter/s]
Best score: 0.4439: : 311iter [00:30, 10.60iter/s]
Best score: 0.4439: : 311iter [00:30, 10.60iter/s]
Best score: 0.4439: : 312iter [00:30, 10.60iter/s]
Best score: 0.4439: : 313iter [00:30, 10.96iter/s]
Best score: 0.4439: : 313iter [00:30, 10.96iter/s]
Best score: 0.4439: : 314iter [00:30, 10.96iter/s]
Best score: 0.4439: : 315iter [00:30, 11.22iter/s]
Best score: 0.4439: : 315iter [00:30, 11.22iter/s]
Best score: 0.4439: : 316iter [00:30, 11.22iter/s]
Best score: 0.4439: : 317iter [00:30, 11.43iter/s]
Best score: 0.4439: : 317iter [00:30, 11.43iter/s]
Best score: 0.4439: : 318iter [00:30, 11.43iter/s]
Best score: 0.4439: : 319iter [00:30, 11.58iter/s]
Best score: 0.4439: : 319iter [00:30, 11.58iter/s]
Best score: 0.4439: : 320iter [00:30, 11.58iter/s]
Best score: 0.4439: : 321iter [00:30, 11.46iter/s]
Best score: 0.4439: : 321iter [00:31, 11.46iter/s]
Best score: 0.4439: : 322iter [00:31, 11.46iter/s]
Best score: 0.4439: : 323iter [00:31, 11.58iter/s]
Best score: 0.4439: : 323iter [00:31, 11.58iter/s]
Best score: 0.4439: : 324iter [00:31, 11.58iter/s]
Best score: 0.4439: : 325iter [00:31, 11.68iter/s]
Best score: 0.4439: : 325iter [00:31, 11.68iter/s]
Best score: 0.4439: : 326iter [00:31, 11.68iter/s]
Best score: 0.4439: : 327iter [00:31, 11.75iter/s]
Best score: 0.4439: : 327iter [00:31, 11.75iter/s]
Best score: 0.4439: : 328iter [00:31, 11.75iter/s]
Best score: 0.4439: : 329iter [00:31, 11.77iter/s]
Best score: 0.3581: : 329iter [00:31, 11.77iter/s]
Best score: 0.3581: : 330iter [00:31, 11.77iter/s]
Best score: 0.3581: : 331iter [00:31, 11.60iter/s]
Best score: 0.3581: : 331iter [00:31, 11.60iter/s]
Best score: 0.3581: : 332iter [00:31, 11.60iter/s]
Best score: 0.3581: : 333iter [00:31, 11.69iter/s]
Best score: 0.3581: : 333iter [00:32, 11.69iter/s]
Best score: 0.3581: : 334iter [00:32, 11.69iter/s]
Best score: 0.3581: : 335iter [00:32, 11.77iter/s]
Best score: 0.3581: : 335iter [00:32, 11.77iter/s]
Best score: 0.3581: : 336iter [00:32, 11.77iter/s]
Best score: 0.3581: : 337iter [00:32, 11.81iter/s]
Best score: 0.3581: : 337iter [00:32, 11.81iter/s]
Best score: 0.3581: : 338iter [00:32, 11.81iter/s]
Best score: 0.3581: : 339iter [00:32, 11.83iter/s]
Best score: 0.3581: : 339iter [00:32, 11.83iter/s]
Best score: 0.3581: : 340iter [00:32, 11.83iter/s]
Best score: 0.3581: : 341iter [00:32, 11.65iter/s]
Best score: 0.3581: : 341iter [00:32, 11.65iter/s]
Best score: 0.3581: : 342iter [00:32, 11.65iter/s]
Best score: 0.3581: : 343iter [00:32, 11.68iter/s]
Best score: 0.3581: : 343iter [00:32, 11.68iter/s]
Best score: 0.3581: : 344iter [00:33, 11.68iter/s]
Best score: 0.3581: : 345iter [00:33, 11.71iter/s]
Best score: 0.3581: : 345iter [00:33, 11.71iter/s]
Best score: 0.3581: : 346iter [00:33, 11.71iter/s]
Best score: 0.3581: : 347iter [00:33, 11.74iter/s]
Best score: 0.3581: : 347iter [00:33, 11.74iter/s]
Best score: 0.3581: : 348iter [00:33, 11.74iter/s]
Best score: 0.3581: : 349iter [00:33, 11.78iter/s]
[ITER 350] Best: 0.3581
[PARAMS] Current best parameters:
  fx: 469.9789
  fy: 469.2525
  px: 869.2960
  py: 1005.5954
  k1: 0.07797451
  k2: -0.02307566
  k3: 0.01659952
  k4: -0.00586079
  p1: -0.01579657
  p2: 0.00783578
  p3: 0.00314356
  p4: -0.00635441
  s1: -0.0020
  s2: 0.0053
  s3: 0.0187
  s4: 0.0077
  tilt_x: 0.0409
  tilt_y: -0.0535
  scale: 3.0566
  rotation: -0.4530

Best score: 0.3581: : 349iter [00:33, 11.78iter/s]
[Periodic outlier @ iter 250] Removing 2000R frame 18 (score=2.83, threshold=2.30)
  Remaining frames: 78

Best score: 0.3581: : 350iter [00:33, 11.78iter/s]
Best score: 0.3581: : 351iter [00:33,  6.59iter/s]
Best score: 0.3581: : 351iter [00:34,  6.59iter/s]
Best score: 0.3581: : 352iter [00:34,  6.59iter/s]
Best score: 0.3581: : 353iter [00:34,  7.58iter/s]
Best score: 0.3581: : 353iter [00:34,  7.58iter/s]
Best score: 0.3581: : 354iter [00:34,  7.58iter/s]
Best score: 0.3581: : 355iter [00:34,  8.46iter/s]
Best score: 0.3581: : 355iter [00:34,  8.46iter/s]
Best score: 0.3581: : 356iter [00:34,  8.46iter/s]
Best score: 0.3581: : 357iter [00:34,  9.22iter/s]
Best score: 0.3581: : 357iter [00:34,  9.22iter/s]
Best score: 0.3581: : 358iter [00:34,  9.22iter/s]
Best score: 0.3581: : 359iter [00:34,  9.86iter/s]
Best score: 0.3295: : 359iter [00:34,  9.86iter/s]
Best score: 0.3295: : 360iter [00:34,  9.86iter/s]
Best score: 0.3295: : 361iter [00:34, 10.19iter/s]
Best score: 0.3295: : 361iter [00:34, 10.19iter/s]
Best score: 0.3295: : 362iter [00:34, 10.19iter/s]
Best score: 0.3295: : 363iter [00:34, 10.59iter/s]
Best score: 0.3295: : 363iter [00:35, 10.59iter/s]
Best score: 0.3295: : 364iter [00:35, 10.59iter/s]
Best score: 0.3295: : 365iter [00:35, 10.88iter/s]
Best score: 0.3295: : 365iter [00:35, 10.88iter/s]
Best score: 0.3295: : 366iter [00:35, 10.88iter/s]
Best score: 0.3295: : 367iter [00:35, 11.08iter/s]
Best score: 0.3295: : 367iter [00:35, 11.08iter/s]
Best score: 0.3295: : 368iter [00:35, 11.08iter/s]
Best score: 0.3295: : 369iter [00:35, 11.24iter/s]
Best score: 0.3295: : 369iter [00:35, 11.24iter/s]
Best score: 0.3295: : 370iter [00:35, 11.24iter/s]
Best score: 0.3295: : 371iter [00:35, 11.17iter/s]
Best score: 0.3295: : 371iter [00:35, 11.17iter/s]
Best score: 0.3295: : 372iter [00:35, 11.17iter/s]
Best score: 0.3295: : 373iter [00:35, 11.33iter/s]
Best score: 0.3295: : 373iter [00:35, 11.33iter/s]
Best score: 0.3295: : 374iter [00:36, 11.33iter/s]
Best score: 0.3295: : 375iter [00:36, 11.41iter/s]
Best score: 0.3295: : 375iter [00:36, 11.41iter/s]
Best score: 0.3295: : 376iter [00:36, 11.41iter/s]
Best score: 0.3295: : 377iter [00:36, 11.52iter/s]
Best score: 0.3295: : 377iter [00:36, 11.52iter/s]
Best score: 0.3295: : 378iter [00:36, 11.52iter/s]
Best score: 0.3295: : 379iter [00:36, 11.56iter/s]
Best score: 0.3295: : 379iter [00:36, 11.56iter/s]
Best score: 0.3295: : 380iter [00:36, 11.56iter/s]
Best score: 0.3295: : 381iter [00:36, 11.44iter/s]
Best score: 0.3295: : 381iter [00:36, 11.44iter/s]
Best score: 0.3295: : 382iter [00:36, 11.44iter/s]
Best score: 0.3295: : 383iter [00:36, 11.53iter/s]
Best score: 0.3295: : 383iter [00:36, 11.53iter/s]
Best score: 0.3295: : 384iter [00:36, 11.53iter/s]
Best score: 0.3295: : 385iter [00:36, 11.57iter/s]
Best score: 0.3295: : 385iter [00:36, 11.57iter/s]
Best score: 0.3295: : 386iter [00:37, 11.57iter/s]
Best score: 0.3295: : 387iter [00:37, 11.57iter/s]
Best score: 0.3295: : 387iter [00:37, 11.57iter/s]
Best score: 0.3295: : 388iter [00:37, 11.57iter/s]
Best score: 0.3295: : 389iter [00:37, 11.60iter/s]
Best score: 0.3295: : 389iter [00:37, 11.60iter/s]
Best score: 0.3295: : 390iter [00:37, 11.60iter/s]
Best score: 0.3295: : 391iter [00:37, 11.44iter/s]
Best score: 0.3295: : 391iter [00:37, 11.44iter/s]
Best score: 0.3295: : 392iter [00:37, 11.44iter/s]
Best score: 0.3295: : 393iter [00:37, 11.48iter/s]
Best score: 0.3295: : 393iter [00:37, 11.48iter/s]
Best score: 0.3295: : 394iter [00:37, 11.48iter/s]
Best score: 0.3295: : 395iter [00:37, 11.55iter/s]
Best score: 0.3295: : 395iter [00:37, 11.55iter/s]
Best score: 0.3295: : 396iter [00:37, 11.55iter/s]
Best score: 0.3295: : 397iter [00:37, 11.60iter/s]
Best score: 0.3295: : 397iter [00:38, 11.60iter/s]
Best score: 0.3295: : 398iter [00:38, 11.60iter/s]
Best score: 0.3295: : 399iter [00:38, 11.66iter/s]
[ITER 400] Best: 0.3295
[PARAMS] Current best parameters:
  fx: 469.9789
  fy: 469.2525
  px: 869.2960
  py: 1005.5954
  k1: 0.07797451
  k2: -0.02307566
  k3: 0.01659952
  k4: -0.00586079
  p1: -0.01579657
  p2: 0.00783578
  p3: 0.00314356
  p4: -0.00635441
  s1: -0.0020
  s2: 0.0053
  s3: 0.0187
  s4: 0.0077
  tilt_x: 0.0409
  tilt_y: -0.0535
  scale: 3.0566
  rotation: -0.4530

Best score: 0.3295: : 399iter [00:38, 11.66iter/s]
[Periodic outlier @ iter 300] Removing 2000R frame 17 (score=2.40, threshold=2.28)
  Remaining frames: 77

Best score: 0.3295: : 400iter [00:38, 11.66iter/s]
Best score: 0.3295: : 401iter [00:38,  6.58iter/s]
Best score: 0.3295: : 401iter [00:38,  6.58iter/s]
Best score: 0.3295: : 402iter [00:38,  6.58iter/s]
Best score: 0.3295: : 403iter [00:38,  7.58iter/s]
Best score: 0.3295: : 403iter [00:38,  7.58iter/s]
Best score: 0.3295: : 404iter [00:39,  7.58iter/s]
Best score: 0.3295: : 405iter [00:39,  8.48iter/s]
Best score: 0.3295: : 405iter [00:39,  8.48iter/s]
Best score: 0.3295: : 406iter [00:39,  8.48iter/s]
Best score: 0.3295: : 407iter [00:39,  9.25iter/s]
Best score: 0.3295: : 407iter [00:39,  9.25iter/s]
Best score: 0.3295: : 408iter [00:39,  9.25iter/s]
Best score: 0.3295: : 409iter [00:39,  9.90iter/s]
Best score: 0.3069: : 409iter [00:39,  9.90iter/s]
Best score: 0.3069: : 410iter [00:39,  9.90iter/s]
Best score: 0.3069: : 411iter [00:39, 10.22iter/s]
Best score: 0.3069: : 411iter [00:39, 10.22iter/s]
Best score: 0.3069: : 412iter [00:39, 10.22iter/s]
Best score: 0.3069: : 413iter [00:39, 10.65iter/s]
Best score: 0.3069: : 413iter [00:39, 10.65iter/s]
Best score: 0.3069: : 414iter [00:39, 10.65iter/s]
Best score: 0.3069: : 415iter [00:39, 10.97iter/s]
Best score: 0.3069: : 415iter [00:40, 10.97iter/s]
Best score: 0.3069: : 416iter [00:40, 10.97iter/s]
Best score: 0.3069: : 417iter [00:40, 11.20iter/s]
Best score: 0.3069: : 417iter [00:40, 11.20iter/s]
Best score: 0.3069: : 418iter [00:40, 11.20iter/s]
Best score: 0.3069: : 419iter [00:40, 11.37iter/s]
Best score: 0.3069: : 419iter [00:40, 11.37iter/s]
Best score: 0.3069: : 420iter [00:40, 11.37iter/s]
Best score: 0.3069: : 421iter [00:40, 11.33iter/s]
Best score: 0.3069: : 421iter [00:40, 11.33iter/s]
Best score: 0.3069: : 422iter [00:40, 11.33iter/s]
Best score: 0.3069: : 423iter [00:40, 11.48iter/s]
Best score: 0.3069: : 423iter [00:40, 11.48iter/s]
Best score: 0.3069: : 424iter [00:40, 11.48iter/s]
Best score: 0.3069: : 425iter [00:40, 11.57iter/s]
Best score: 0.3069: : 425iter [00:40, 11.57iter/s]
Best score: 0.3069: : 426iter [00:40, 11.57iter/s]
Best score: 0.3069: : 427iter [00:40, 11.61iter/s]
Best score: 0.3069: : 427iter [00:41, 11.61iter/s]
Best score: 0.3069: : 428iter [00:41, 11.61iter/s]
Best score: 0.3069: : 429iter [00:41, 11.67iter/s]
Best score: 0.3069: : 429iter [00:41, 11.67iter/s]
Best score: 0.3069: : 430iter [00:41, 11.67iter/s]
Best score: 0.3069: : 431iter [00:41, 11.53iter/s]
Best score: 0.3069: : 431iter [00:41, 11.53iter/s]
Best score: 0.3069: : 432iter [00:41, 11.53iter/s]
Best score: 0.3069: : 433iter [00:41, 11.65iter/s]
Best score: 0.3069: : 433iter [00:41, 11.65iter/s]
Best score: 0.3069: : 434iter [00:41, 11.65iter/s]
Best score: 0.3069: : 435iter [00:41, 11.78iter/s]
Best score: 0.3069: : 435iter [00:41, 11.78iter/s]
Best score: 0.3069: : 436iter [00:41, 11.78iter/s]
Best score: 0.3069: : 437iter [00:41, 11.81iter/s]
Best score: 0.3069: : 437iter [00:41, 11.81iter/s]
Best score: 0.3069: : 438iter [00:41, 11.81iter/s]
Best score: 0.3069: : 439iter [00:41, 11.83iter/s]
Best score: 0.3069: : 439iter [00:42, 11.83iter/s]
Best score: 0.3069: : 440iter [00:42, 11.83iter/s]
Best score: 0.3069: : 441iter [00:42, 11.67iter/s]
Best score: 0.3069: : 441iter [00:42, 11.67iter/s]
Best score: 0.3069: : 442iter [00:42, 11.67iter/s]
Best score: 0.3069: : 443iter [00:42, 11.74iter/s]
Best score: 0.3069: : 443iter [00:42, 11.74iter/s]
Best score: 0.3069: : 444iter [00:42, 11.74iter/s]
Best score: 0.3069: : 445iter [00:42, 11.77iter/s]
Best score: 0.3069: : 445iter [00:42, 11.77iter/s]
Best score: 0.3069: : 446iter [00:42, 11.77iter/s]
Best score: 0.3069: : 447iter [00:42, 11.80iter/s]
Best score: 0.3069: : 447iter [00:42, 11.80iter/s]
Best score: 0.3069: : 448iter [00:42, 11.80iter/s]
Best score: 0.3069: : 449iter [00:42, 11.81iter/s]
[ITER 450] Best: 0.3069
[PARAMS] Current best parameters:
  fx: 469.9789
  fy: 469.2525
  px: 869.2960
  py: 1005.5954
  k1: 0.07797451
  k2: -0.02307566
  k3: 0.01659952
  k4: -0.00586079
  p1: -0.01579657
  p2: 0.00783578
  p3: 0.00314356
  p4: -0.00635441
  s1: -0.0020
  s2: 0.0053
  s3: 0.0187
  s4: 0.0077
  tilt_x: 0.0409
  tilt_y: -0.0535
  scale: 3.0566
  rotation: -0.4530

Best score: 0.3069: : 449iter [00:42, 11.81iter/s]
Best score: 0.3069: : 450iter [00:43, 11.81iter/s]
Best score: 0.3069: : 451iter [00:43,  7.66iter/s]
Best score: 0.3069: : 451iter [00:43,  7.66iter/s]
Best score: 0.3069: : 452iter [00:43,  7.66iter/s]
Best score: 0.3069: : 453iter [00:43,  8.57iter/s]
Best score: 0.3069: : 453iter [00:43,  8.57iter/s]
Best score: 0.3069: : 454iter [00:43,  8.57iter/s]
Best score: 0.3069: : 455iter [00:43,  9.34iter/s]
Best score: 0.3069: : 455iter [00:43,  9.34iter/s]
Best score: 0.3069: : 456iter [00:43,  9.34iter/s]
Best score: 0.3069: : 457iter [00:43,  9.99iter/s]
Best score: 0.3069: : 457iter [00:43,  9.99iter/s]
Best score: 0.3069: : 458iter [00:43,  9.99iter/s]
Best score: 0.3069: : 459iter [00:43, 10.52iter/s]
Best score: 0.3069: : 459iter [00:44, 10.52iter/s]
Best score: 0.3069: : 460iter [00:44, 10.52iter/s]
Best score: 0.3069: : 461iter [00:44, 10.75iter/s]
Best score: 0.3069: : 461iter [00:44, 10.75iter/s]
Best score: 0.3069: : 462iter [00:44, 10.75iter/s]
Best score: 0.3069: : 463iter [00:44, 11.08iter/s]
Best score: 0.3069: : 463iter [00:44, 11.08iter/s]
Best score: 0.3069: : 464iter [00:44, 11.08iter/s]
Best score: 0.3069: : 465iter [00:44, 11.33iter/s]
Best score: 0.3069: : 465iter [00:44, 11.33iter/s]
Best score: 0.3069: : 466iter [00:44, 11.33iter/s]
Best score: 0.3069: : 467iter [00:44, 11.50iter/s]
Best score: 0.3069: : 467iter [00:44, 11.50iter/s]
Best score: 0.3069: : 468iter [00:44, 11.50iter/s]
Best score: 0.3069: : 469iter [00:44, 11.71iter/s]
Best score: 0.3069: : 469iter [00:44, 11.71iter/s]
Best score: 0.3069: : 470iter [00:44, 11.71iter/s]
Best score: 0.3069: : 471iter [00:44, 11.66iter/s]
Best score: 0.3069: : 471iter [00:45, 11.66iter/s]
Best score: 0.3069: : 472iter [00:45, 11.66iter/s]
Best score: 0.3069: : 473iter [00:45, 11.80iter/s]
Best score: 0.3069: : 473iter [00:45, 11.80iter/s]
Best score: 0.3069: : 474iter [00:45, 11.80iter/s]
Best score: 0.3069: : 475iter [00:45, 11.91iter/s]
Best score: 0.3069: : 475iter [00:45, 11.91iter/s]
Best score: 0.3069: : 476iter [00:45, 11.91iter/s]
Best score: 0.3069: : 477iter [00:45, 11.95iter/s]
Best score: 0.3069: : 477iter [00:45, 11.95iter/s]
Best score: 0.3069: : 478iter [00:45, 11.95iter/s]
Best score: 0.3069: : 479iter [00:45, 12.02iter/s]
Best score: 0.3069: : 479iter [00:45, 12.02iter/s]
Best score: 0.3069: : 480iter [00:45, 12.02iter/s]
Best score: 0.3069: : 481iter [00:45, 11.80iter/s]
Best score: 0.3069: : 481iter [00:45, 11.80iter/s]
Best score: 0.3069: : 482iter [00:45, 11.80iter/s]
Best score: 0.3069: : 483iter [00:45, 11.86iter/s]
Best score: 0.3069: : 483iter [00:46, 11.86iter/s]
Best score: 0.3069: : 484iter [00:46, 11.86iter/s]
Best score: 0.3069: : 485iter [00:46, 11.96iter/s]
Best score: 0.3069: : 485iter [00:46, 11.96iter/s]
Best score: 0.3069: : 486iter [00:46, 11.96iter/s]
Best score: 0.3069: : 487iter [00:46, 11.99iter/s]
Best score: 0.3069: : 487iter [00:46, 11.99iter/s]
Best score: 0.3069: : 488iter [00:46, 11.99iter/s]
Best score: 0.3069: : 489iter [00:46, 12.01iter/s]
Best score: 0.3069: : 489iter [00:46, 12.01iter/s]
Best score: 0.3069: : 490iter [00:46, 12.01iter/s]
Best score: 0.3069: : 491iter [00:46, 11.86iter/s]
Best score: 0.3069: : 491iter [00:46, 11.86iter/s]
Best score: 0.3069: : 492iter [00:46, 11.86iter/s]
Best score: 0.3069: : 493iter [00:46, 11.96iter/s]
Best score: 0.3069: : 493iter [00:46, 11.96iter/s]
Best score: 0.3069: : 494iter [00:46, 11.96iter/s]
Best score: 0.3069: : 495iter [00:46, 12.01iter/s]
Best score: 0.3069: : 495iter [00:47, 12.01iter/s]
Best score: 0.3069: : 496iter [00:47, 12.01iter/s]
Best score: 0.3069: : 497iter [00:47, 12.01iter/s]
Best score: 0.3069: : 497iter [00:47, 12.01iter/s]
Best score: 0.3069: : 498iter [00:47, 12.01iter/s]
Best score: 0.3069: : 499iter [00:47, 11.97iter/s]
[ITER 500] Best: 0.3069
[PARAMS] Current best parameters:
  fx: 469.9789
  fy: 469.2525
  px: 869.2960
  py: 1005.5954
  k1: 0.07797451
  k2: -0.02307566
  k3: 0.01659952
  k4: -0.00586079
  p1: -0.01579657
  p2: 0.00783578
  p3: 0.00314356
  p4: -0.00635441
  s1: -0.0020
  s2: 0.0053
  s3: 0.0187
  s4: 0.0077
  tilt_x: 0.0409
  tilt_y: -0.0535
  scale: 3.0566
  rotation: -0.4530

Best score: 0.3069: : 499iter [00:47, 11.97iter/s]
Best score: 0.3069: : 500iter [00:47, 11.97iter/s]
Best score: 0.3069: : 501iter [00:47,  7.73iter/s]
Best score: 0.3069: : 501iter [00:47,  7.73iter/s]
Best score: 0.3069: : 502iter [00:47,  7.73iter/s]
Best score: 0.3069: : 503iter [00:47,  8.64iter/s]
Best score: 0.3069: : 503iter [00:48,  8.64iter/s]
Best score: 0.3069: : 504iter [00:48,  8.64iter/s]
Best score: 0.3069: : 505iter [00:48,  9.44iter/s]
Best score: 0.3069: : 505iter [00:48,  9.44iter/s]
Best score: 0.3069: : 506iter [00:48,  9.44iter/s]
Best score: 0.3069: : 507iter [00:48, 10.13iter/s]
Best score: 0.3069: : 507iter [00:48, 10.13iter/s]
Best score: 0.3069: : 508iter [00:48, 10.13iter/s]
Best score: 0.3069: : 509iter [00:48, 10.66iter/s]
Best score: 0.3069: : 509iter [00:48, 10.66iter/s]
Best score: 0.3069: : 510iter [00:48, 10.66iter/s]
Best score: 0.3069: : 511iter [00:48, 10.91iter/s]
Best score: 0.3069: : 511iter [00:48, 10.91iter/s]
Best score: 0.3069: : 512iter [00:48, 10.91iter/s]
Best score: 0.3069: : 513iter [00:48, 11.25iter/s]
Best score: 0.3069: : 513iter [00:48, 11.25iter/s]
Best score: 0.3069: : 514iter [00:48, 11.25iter/s]
Best score: 0.3069: : 515iter [00:48, 11.47iter/s]
Best score: 0.3069: : 515iter [00:49, 11.47iter/s]
Best score: 0.3069: : 516iter [00:49, 11.47iter/s]
Best score: 0.3069: : 517iter [00:49, 11.67iter/s]
Best score: 0.3069: : 517iter [00:49, 11.67iter/s]
Best score: 0.3069: : 518iter [00:49, 11.67iter/s]
Best score: 0.3069: : 519iter [00:49, 11.83iter/s]
Best score: 0.3069: : 519iter [00:49, 11.83iter/s]
Best score: 0.3069: : 520iter [00:49, 11.83iter/s]
Best score: 0.3069: : 521iter [00:49, 11.71iter/s]
Best score: 0.3069: : 521iter [00:49, 11.71iter/s]
Best score: 0.3069: : 522iter [00:49, 11.71iter/s]
Best score: 0.3069: : 523iter [00:49, 11.85iter/s]
Best score: 0.3069: : 523iter [00:49, 11.85iter/s]
Best score: 0.3069: : 524iter [00:49, 11.85iter/s]
Best score: 0.3069: : 525iter [00:49, 11.96iter/s]
Best score: 0.3069: : 525iter [00:49, 11.96iter/s]
Best score: 0.3069: : 526iter [00:49, 11.96iter/s]
Best score: 0.3069: : 527iter [00:49, 11.99iter/s]
Best score: 0.3069: : 527iter [00:50, 11.99iter/s]
Best score: 0.3069: : 528iter [00:50, 11.99iter/s]
Best score: 0.3069: : 529iter [00:50, 12.02iter/s]
Best score: 0.3069: : 529iter [00:50, 12.02iter/s]
Best score: 0.3069: : 530iter [00:50, 12.02iter/s]
Best score: 0.3069: : 531iter [00:50, 11.87iter/s]
Best score: 0.3069: : 531iter [00:50, 11.87iter/s]
Best score: 0.3069: : 532iter [00:50, 11.87iter/s]
Best score: 0.3069: : 533iter [00:50, 11.97iter/s]
Best score: 0.3069: : 533iter [00:50, 11.97iter/s]
Best score: 0.3069: : 534iter [00:50, 11.97iter/s]
Best score: 0.3069: : 535iter [00:50, 11.97iter/s]
Best score: 0.3069: : 535iter [00:50, 11.97iter/s]
Best score: 0.3069: : 536iter [00:50, 11.97iter/s]
Best score: 0.3069: : 537iter [00:50, 12.04iter/s]
Best score: 0.3069: : 537iter [00:50, 12.04iter/s]
Best score: 0.3069: : 538iter [00:50, 12.04iter/s]
Best score: 0.3069: : 539iter [00:50, 12.06iter/s]
Best score: 0.3069: : 539iter [00:51, 12.06iter/s]
Best score: 0.3069: : 540iter [00:51, 12.06iter/s]
Best score: 0.3069: : 541iter [00:51, 11.82iter/s]
Best score: 0.3069: : 541iter [00:51, 11.82iter/s]
Best score: 0.3069: : 542iter [00:51, 11.82iter/s]
Best score: 0.3069: : 543iter [00:51, 11.93iter/s]
Best score: 0.3069: : 543iter [00:51, 11.93iter/s]
Best score: 0.3069: : 544iter [00:51, 11.93iter/s]
Best score: 0.3069: : 545iter [00:51, 12.02iter/s]
Best score: 0.3069: : 545iter [00:51, 12.02iter/s]
Best score: 0.3069: : 546iter [00:51, 12.02iter/s]
Best score: 0.3069: : 547iter [00:51, 12.07iter/s]
Best score: 0.3069: : 547iter [00:51, 12.07iter/s]
Best score: 0.3069: : 548iter [00:51, 12.07iter/s]
Best score: 0.3069: : 549iter [00:51, 12.11iter/s]
[ITER 550] Best: 0.2735
[PARAMS] Current best parameters:
  fx: 468.9302
  fy: 468.4998
  px: 869.6540
  py: 1004.2205
  k1: 0.08999917
  k2: -0.03539366
  k3: 0.02223581
  k4: -0.00703756
  p1: -0.01663331
  p2: 0.00990203
  p3: 0.00619647
  p4: -0.00924475
  s1: -0.0004
  s2: 0.0042
  s3: 0.0199
  s4: 0.0067
  tilt_x: 0.0364
  tilt_y: -0.0494
  scale: 3.0368
  rotation: -0.4774

Best score: 0.2735: : 549iter [00:51, 12.11iter/s]
[Periodic outlier @ iter 450] Removing 2000L frame 15 (score=2.32, threshold=2.23)
  Remaining frames: 76

Best score: 0.2735: : 550iter [00:52, 12.11iter/s]
Best score: 0.2735: : 551iter [00:52,  6.74iter/s]
Best score: 0.2735: : 551iter [00:52,  6.74iter/s]
Best score: 0.2735: : 552iter [00:52,  6.74iter/s]
Best score: 0.2735: : 553iter [00:52,  7.74iter/s]
Best score: 0.2735: : 553iter [00:52,  7.74iter/s]
Best score: 0.2735: : 554iter [00:52,  7.74iter/s]
Best score: 0.2735: : 555iter [00:52,  8.65iter/s]
Best score: 0.2735: : 555iter [00:52,  8.65iter/s]
Best score: 0.2735: : 556iter [00:52,  8.65iter/s]
Best score: 0.2735: : 557iter [00:52,  9.42iter/s]
Best score: 0.2735: : 557iter [00:52,  9.42iter/s]
Best score: 0.2735: : 558iter [00:53,  9.42iter/s]
Best score: 0.2735: : 559iter [00:53, 10.06iter/s]
Best score: 0.2475: : 559iter [00:53, 10.06iter/s]
Best score: 0.2475: : 560iter [00:53, 10.06iter/s]
Best score: 0.2475: : 561iter [00:53, 10.43iter/s]
Best score: 0.2475: : 561iter [00:53, 10.43iter/s]
Best score: 0.2475: : 562iter [00:53, 10.43iter/s]
Best score: 0.2475: : 563iter [00:53, 10.87iter/s]
Best score: 0.2475: : 563iter [00:53, 10.87iter/s]
Best score: 0.2475: : 564iter [00:53, 10.87iter/s]
Best score: 0.2475: : 565iter [00:53, 11.20iter/s]
Best score: 0.2475: : 565iter [00:53, 11.20iter/s]
Best score: 0.2475: : 566iter [00:53, 11.20iter/s]
Best score: 0.2475: : 567iter [00:53, 11.46iter/s]
Best score: 0.2475: : 567iter [00:53, 11.46iter/s]
Best score: 0.2475: : 568iter [00:53, 11.46iter/s]
Best score: 0.2475: : 569iter [00:53, 11.60iter/s]
Best score: 0.2475: : 569iter [00:53, 11.60iter/s]
Best score: 0.2475: : 570iter [00:54, 11.60iter/s]
Best score: 0.2475: : 571iter [00:54, 11.54iter/s]
Best score: 0.2475: : 571iter [00:54, 11.54iter/s]
Best score: 0.2475: : 572iter [00:54, 11.54iter/s]
Best score: 0.2475: : 573iter [00:54, 11.67iter/s]
Best score: 0.2475: : 573iter [00:54, 11.67iter/s]
Best score: 0.2475: : 574iter [00:54, 11.67iter/s]
Best score: 0.2475: : 575iter [00:54, 11.75iter/s]
Best score: 0.2475: : 575iter [00:54, 11.75iter/s]
Best score: 0.2475: : 576iter [00:54, 11.75iter/s]
Best score: 0.2475: : 577iter [00:54, 11.80iter/s]
Best score: 0.2475: : 577iter [00:54, 11.80iter/s]
Best score: 0.2475: : 578iter [00:54, 11.80iter/s]
Best score: 0.2475: : 579iter [00:54, 11.84iter/s]
Best score: 0.2475: : 579iter [00:54, 11.84iter/s]
Best score: 0.2475: : 580iter [00:54, 11.84iter/s]
Best score: 0.2475: : 581iter [00:54, 11.67iter/s]
Best score: 0.2475: : 581iter [00:55, 11.67iter/s]
Best score: 0.2475: : 582iter [00:55, 11.67iter/s]
Best score: 0.2475: : 583iter [00:55, 11.75iter/s]
Best score: 0.2475: : 583iter [00:55, 11.75iter/s]
Best score: 0.2475: : 584iter [00:55, 11.75iter/s]
Best score: 0.2475: : 585iter [00:55, 11.86iter/s]
Best score: 0.2475: : 585iter [00:55, 11.86iter/s]
Best score: 0.2475: : 586iter [00:55, 11.86iter/s]
Best score: 0.2475: : 587iter [00:55, 11.92iter/s]
Best score: 0.2475: : 587iter [00:55, 11.92iter/s]
Best score: 0.2475: : 588iter [00:55, 11.92iter/s]
Best score: 0.2475: : 589iter [00:55, 11.96iter/s]
Best score: 0.2475: : 589iter [00:55, 11.96iter/s]
Best score: 0.2475: : 590iter [00:55, 11.96iter/s]
Best score: 0.2475: : 591iter [00:55, 11.77iter/s]
Best score: 0.2475: : 591iter [00:55, 11.77iter/s]
Best score: 0.2475: : 592iter [00:55, 11.77iter/s]
Best score: 0.2475: : 593iter [00:55, 11.82iter/s]
Best score: 0.2475: : 593iter [00:56, 11.82iter/s]
Best score: 0.2475: : 594iter [00:56, 11.82iter/s]
Best score: 0.2475: : 595iter [00:56, 11.84iter/s]
Best score: 0.2475: : 595iter [00:56, 11.84iter/s]
Best score: 0.2475: : 596iter [00:56, 11.84iter/s]
Best score: 0.2475: : 597iter [00:56, 11.89iter/s]
Best score: 0.2475: : 597iter [00:56, 11.89iter/s]
Best score: 0.2475: : 598iter [00:56, 11.89iter/s]
Best score: 0.2475: : 599iter [00:56, 11.99iter/s]
[ITER 600] Best: 0.2475
[PARAMS] Current best parameters:
  fx: 468.9302
  fy: 468.4998
  px: 869.6540
  py: 1004.2205
  k1: 0.08999917
  k2: -0.03539366
  k3: 0.02223581
  k4: -0.00703756
  p1: -0.01663331
  p2: 0.00990203
  p3: 0.00619647
  p4: -0.00924475
  s1: -0.0004
  s2: 0.0042
  s3: 0.0199
  s4: 0.0067
  tilt_x: 0.0364
  tilt_y: -0.0494
  scale: 3.0368
  rotation: -0.4774

Best score: 0.2475: : 599iter [00:56, 11.99iter/s]
Best score: 0.2475: : 600iter [00:56, 11.99iter/s]
Best score: 0.2475: : 601iter [00:56,  7.73iter/s]
Best score: 0.2475: : 601iter [00:56,  7.73iter/s]
Best score: 0.2475: : 602iter [00:57,  7.73iter/s]
Best score: 0.2475: : 603iter [00:57,  8.64iter/s]
Best score: 0.2475: : 603iter [00:57,  8.64iter/s]
Best score: 0.2475: : 604iter [00:57,  8.64iter/s]
Best score: 0.2475: : 605iter [00:57,  9.44iter/s]
Best score: 0.2475: : 605iter [00:57,  9.44iter/s]
Best score: 0.2475: : 606iter [00:57,  9.44iter/s]
Best score: 0.2475: : 607iter [00:57, 10.12iter/s]
Best score: 0.2475: : 607iter [00:57, 10.12iter/s]
Best score: 0.2475: : 608iter [00:57, 10.12iter/s]
Best score: 0.2475: : 609iter [00:57, 10.64iter/s]
Best score: 0.2475: : 609iter [00:57, 10.64iter/s]
Best score: 0.2475: : 610iter [00:57, 10.64iter/s]
Best score: 0.2475: : 611iter [00:57, 10.86iter/s]
Best score: 0.2475: : 611iter [00:57, 10.86iter/s]
Best score: 0.2475: : 612iter [00:57, 10.86iter/s]
Best score: 0.2475: : 613iter [00:57, 11.23iter/s]
Best score: 0.2475: : 613iter [00:57, 11.23iter/s]
Best score: 0.2475: : 614iter [00:58, 11.23iter/s]
Best score: 0.2475: : 615iter [00:58, 11.44iter/s]
Best score: 0.2475: : 615iter [00:58, 11.44iter/s]
Best score: 0.2475: : 616iter [00:58, 11.44iter/s]
Best score: 0.2475: : 617iter [00:58, 11.68iter/s]
Best score: 0.2475: : 617iter [00:58, 11.68iter/s]
Best score: 0.2475: : 618iter [00:58, 11.68iter/s]
Best score: 0.2475: : 619iter [00:58, 11.84iter/s]
Best score: 0.2475: : 619iter [00:58, 11.84iter/s]
Best score: 0.2475: : 620iter [00:58, 11.84iter/s]
Best score: 0.2475: : 621iter [00:58, 11.79iter/s]
Best score: 0.2475: : 621iter [00:58, 11.79iter/s]
Best score: 0.2475: : 622iter [00:58, 11.79iter/s]
Best score: 0.2475: : 623iter [00:58, 11.95iter/s]
Best score: 0.2475: : 623iter [00:58, 11.95iter/s]
Best score: 0.2475: : 624iter [00:58, 11.95iter/s]
Best score: 0.2475: : 625iter [00:58, 12.02iter/s]
Best score: 0.2475: : 625iter [00:58, 12.02iter/s]
Best score: 0.2475: : 626iter [00:59, 12.02iter/s]
Best score: 0.2475: : 627iter [00:59, 12.12iter/s]
Best score: 0.2475: : 627iter [00:59, 12.12iter/s]
Best score: 0.2475: : 628iter [00:59, 12.12iter/s]
Best score: 0.2475: : 629iter [00:59, 12.19iter/s]
Best score: 0.2475: : 629iter [00:59, 12.19iter/s]
Best score: 0.2475: : 630iter [00:59, 12.19iter/s]
Best score: 0.2475: : 631iter [00:59, 12.02iter/s]
Best score: 0.2475: : 631iter [00:59, 12.02iter/s]
Best score: 0.2475: : 632iter [00:59, 12.02iter/s]
Best score: 0.2475: : 633iter [00:59, 12.03iter/s]
Best score: 0.2475: : 633iter [00:59, 12.03iter/s]
Best score: 0.2475: : 634iter [00:59, 12.03iter/s]
Best score: 0.2475: : 635iter [00:59, 12.08iter/s]
Best score: 0.2475: : 635iter [00:59, 12.08iter/s]
Best score: 0.2475: : 636iter [00:59, 12.08iter/s]
Best score: 0.2475: : 637iter [00:59, 12.12iter/s]
Best score: 0.2475: : 637iter [00:59, 12.12iter/s]
Best score: 0.2475: : 638iter [01:00, 12.12iter/s]
Best score: 0.2475: : 639iter [01:00, 12.19iter/s]
Best score: 0.2475: : 639iter [01:00, 12.19iter/s]
Best score: 0.2475: : 640iter [01:00, 12.19iter/s]
Best score: 0.2475: : 641iter [01:00, 12.03iter/s]
Best score: 0.2475: : 641iter [01:00, 12.03iter/s]
Best score: 0.2475: : 642iter [01:00, 12.03iter/s]
Best score: 0.2475: : 643iter [01:00,  9.66iter/s]
Best score: 0.2475: : 643iter [01:00,  9.66iter/s]
Best score: 0.2475: : 644iter [01:00,  9.66iter/s]
Best score: 0.2475: : 645iter [01:00, 10.29iter/s]
Best score: 0.2475: : 645iter [01:00, 10.29iter/s]
Best score: 0.2475: : 646iter [01:00, 10.29iter/s]
Best score: 0.2475: : 647iter [01:00, 10.80iter/s]
Best score: 0.2475: : 647iter [01:00, 10.80iter/s]
Best score: 0.2475: : 648iter [01:01, 10.80iter/s]
Best score: 0.2475: : 649iter [01:01, 11.20iter/s]
[ITER 650] Best: 0.2475
[PARAMS] Current best parameters:
  fx: 468.9302
  fy: 468.4998
  px: 869.6540
  py: 1004.2205
  k1: 0.08999917
  k2: -0.03539366
  k3: 0.02223581
  k4: -0.00703756
  p1: -0.01663331
  p2: 0.00990203
  p3: 0.00619647
  p4: -0.00924475
  s1: -0.0004
  s2: 0.0042
  s3: 0.0199
  s4: 0.0067
  tilt_x: 0.0364
  tilt_y: -0.0494
  scale: 3.0368
  rotation: -0.4774

Best score: 0.2475: : 649iter [01:01, 11.20iter/s]
Best score: 0.2475: : 650iter [01:01, 11.20iter/s]
Best score: 0.2475: : 651iter [01:01,  7.51iter/s]
Best score: 0.2475: : 651iter [01:01,  7.51iter/s]
Best score: 0.2475: : 652iter [01:01,  7.51iter/s]
Best score: 0.2475: : 653iter [01:01,  8.51iter/s]
Best score: 0.2475: : 653iter [01:01,  8.51iter/s]
Best score: 0.2475: : 654iter [01:01,  8.51iter/s]
Best score: 0.2475: : 655iter [01:01,  9.37iter/s]
Best score: 0.2475: : 655iter [01:01,  9.37iter/s]
Best score: 0.2475: : 656iter [01:01,  9.37iter/s]
Best score: 0.2475: : 657iter [01:01, 10.09iter/s]
Best score: 0.2475: : 657iter [01:02, 10.09iter/s]
Best score: 0.2475: : 658iter [01:02, 10.09iter/s]
Best score: 0.2475: : 659iter [01:02, 10.62iter/s]
Best score: 0.2475: : 659iter [01:02, 10.62iter/s]
Best score: 0.2475: : 660iter [01:02, 10.62iter/s]
Best score: 0.2475: : 661iter [01:02, 10.93iter/s]
Best score: 0.2475: : 661iter [01:02, 10.93iter/s]
Best score: 0.2475: : 662iter [01:02, 10.93iter/s]
Best score: 0.2475: : 663iter [01:02, 11.30iter/s]
Best score: 0.2475: : 663iter [01:02, 11.30iter/s]
Best score: 0.2475: : 664iter [01:02, 11.30iter/s]
Best score: 0.2475: : 665iter [01:02, 11.59iter/s]
Best score: 0.2475: : 665iter [01:02, 11.59iter/s]
Best score: 0.2475: : 666iter [01:02, 11.59iter/s]
Best score: 0.2475: : 667iter [01:02, 11.81iter/s]
Best score: 0.2475: : 667iter [01:02, 11.81iter/s]
Best score: 0.2475: : 668iter [01:02, 11.81iter/s]
Best score: 0.2475: : 669iter [01:02, 11.97iter/s]
Best score: 0.2475: : 669iter [01:03, 11.97iter/s]
Best score: 0.2475: : 670iter [01:03, 11.97iter/s]
Best score: 0.2475: : 671iter [01:03, 11.79iter/s]
Best score: 0.2475: : 671iter [01:03, 11.79iter/s]
Best score: 0.2475: : 672iter [01:03, 11.79iter/s]
Best score: 0.2475: : 673iter [01:03, 11.91iter/s]
Best score: 0.2475: : 673iter [01:03, 11.91iter/s]
Best score: 0.2475: : 674iter [01:03, 11.91iter/s]
Best score: 0.2475: : 675iter [01:03, 12.05iter/s]
Best score: 0.2475: : 675iter [01:03, 12.05iter/s]
Best score: 0.2475: : 676iter [01:03, 12.05iter/s]
Best score: 0.2475: : 677iter [01:03, 12.15iter/s]
Best score: 0.2475: : 677iter [01:03, 12.15iter/s]
Best score: 0.2475: : 678iter [01:03, 12.15iter/s]
Best score: 0.2475: : 679iter [01:03, 12.18iter/s]
Best score: 0.2475: : 679iter [01:03, 12.18iter/s]
Best score: 0.2475: : 680iter [01:03, 12.18iter/s]
Best score: 0.2475: : 681iter [01:03, 11.96iter/s]
Best score: 0.2475: : 681iter [01:04, 11.96iter/s]
Best score: 0.2475: : 682iter [01:04, 11.96iter/s]
Best score: 0.2475: : 683iter [01:04, 12.04iter/s]
Best score: 0.2475: : 683iter [01:04, 12.04iter/s]
Best score: 0.2475: : 684iter [01:04, 12.04iter/s]
Best score: 0.2475: : 685iter [01:04, 12.11iter/s]
Best score: 0.2475: : 685iter [01:04, 12.11iter/s]
Best score: 0.2475: : 686iter [01:04, 12.11iter/s]
Best score: 0.2475: : 687iter [01:04, 12.18iter/s]
Best score: 0.2475: : 687iter [01:04, 12.18iter/s]
Best score: 0.2475: : 688iter [01:04, 12.18iter/s]
Best score: 0.2475: : 689iter [01:04, 12.24iter/s]
Best score: 0.2475: : 689iter [01:04, 12.24iter/s]
Best score: 0.2475: : 690iter [01:04, 12.24iter/s]
Best score: 0.2475: : 691iter [01:04, 12.04iter/s]
Best score: 0.2475: : 691iter [01:04, 12.04iter/s]
Best score: 0.2475: : 692iter [01:04, 12.04iter/s]
Best score: 0.2475: : 693iter [01:04, 12.14iter/s]
Best score: 0.2475: : 693iter [01:05, 12.14iter/s]
Best score: 0.2475: : 694iter [01:05, 12.14iter/s]
Best score: 0.2475: : 695iter [01:05, 12.20iter/s]
Best score: 0.2475: : 695iter [01:05, 12.20iter/s]
Best score: 0.2475: : 696iter [01:05, 12.20iter/s]
Best score: 0.2475: : 697iter [01:05, 12.25iter/s]
Best score: 0.2475: : 697iter [01:05, 12.25iter/s]
Best score: 0.2475: : 698iter [01:05, 12.25iter/s]
Best score: 0.2475: : 699iter [01:05, 12.28iter/s]
[ITER 700] Best: 0.2475
[PARAMS] Current best parameters:
  fx: 468.9302
  fy: 468.4998
  px: 869.6540
  py: 1004.2205
  k1: 0.08999917
  k2: -0.03539366
  k3: 0.02223581
  k4: -0.00703756
  p1: -0.01663331
  p2: 0.00990203
  p3: 0.00619647
  p4: -0.00924475
  s1: -0.0004
  s2: 0.0042
  s3: 0.0199
  s4: 0.0067
  tilt_x: 0.0364
  tilt_y: -0.0494
  scale: 3.0368
  rotation: -0.4774

Best score: 0.2475: : 699iter [01:05, 12.28iter/s]
Best score: 0.2475: : 700iter [01:05, 12.28iter/s]
Best score: 0.2475: : 701iter [01:05,  7.87iter/s]
Best score: 0.2475: : 701iter [01:05,  7.87iter/s]
Best score: 0.2475: : 702iter [01:06,  7.87iter/s]
Best score: 0.2475: : 703iter [01:06,  8.78iter/s]
Best score: 0.2475: : 703iter [01:06,  8.78iter/s]
Best score: 0.2475: : 704iter [01:06,  8.78iter/s]
Best score: 0.2475: : 705iter [01:06,  9.61iter/s]
Best score: 0.2475: : 705iter [01:06,  9.61iter/s]
Best score: 0.2475: : 706iter [01:06,  9.61iter/s]
Best score: 0.2475: : 707iter [01:06, 10.30iter/s]
Best score: 0.2475: : 707iter [01:06, 10.30iter/s]
Best score: 0.2475: : 708iter [01:06, 10.30iter/s]
Best score: 0.2475: : 709iter [01:06, 10.80iter/s]
Best score: 0.2475: : 709iter [01:06, 10.80iter/s]
Best score: 0.2475: : 710iter [01:06, 10.80iter/s]
Best score: 0.2475: : 711iter [01:06, 11.04iter/s]
Best score: 0.2475: : 711iter [01:06, 11.04iter/s]
Best score: 0.2475: : 712iter [01:06, 11.04iter/s]
Best score: 0.2475: : 713iter [01:06, 11.41iter/s]
Best score: 0.2475: : 713iter [01:06, 11.41iter/s]
Best score: 0.2475: : 714iter [01:07, 11.41iter/s]
Best score: 0.2475: : 715iter [01:07, 11.66iter/s]
Best score: 0.2475: : 715iter [01:07, 11.66iter/s]
Best score: 0.2475: : 716iter [01:07, 11.66iter/s]
Best score: 0.2475: : 717iter [01:07, 11.86iter/s]
Best score: 0.2475: : 717iter [01:07, 11.86iter/s]
Best score: 0.2475: : 718iter [01:07, 11.86iter/s]
Best score: 0.2475: : 719iter [01:07, 12.01iter/s]
Best score: 0.2475: : 719iter [01:07, 12.01iter/s]
Best score: 0.2475: : 720iter [01:07, 12.01iter/s]
Best score: 0.2475: : 721iter [01:07, 11.88iter/s]
Best score: 0.2475: : 721iter [01:07, 11.88iter/s]
Best score: 0.2475: : 722iter [01:07, 11.88iter/s]
Best score: 0.2475: : 723iter [01:07, 12.01iter/s]
Best score: 0.2475: : 723iter [01:07, 12.01iter/s]
Best score: 0.2475: : 724iter [01:07, 12.01iter/s]
Best score: 0.2475: : 725iter [01:07, 12.01iter/s]
Best score: 0.2475: : 725iter [01:07, 12.01iter/s]
Best score: 0.2475: : 726iter [01:08, 12.01iter/s]
Best score: 0.2475: : 727iter [01:08, 12.01iter/s]
Best score: 0.2475: : 727iter [01:08, 12.01iter/s]
Best score: 0.2475: : 728iter [01:08, 12.01iter/s]
Best score: 0.2475: : 729iter [01:08, 12.03iter/s]
Best score: 0.2475: : 729iter [01:08, 12.03iter/s]
Best score: 0.2475: : 730iter [01:08, 12.03iter/s]
Best score: 0.2475: : 731iter [01:08, 11.91iter/s]
Best score: 0.2475: : 731iter [01:08, 11.91iter/s]
Best score: 0.2475: : 732iter [01:08, 11.91iter/s]
Best score: 0.2475: : 733iter [01:08, 11.99iter/s]
Best score: 0.2475: : 733iter [01:08, 11.99iter/s]
Best score: 0.2475: : 734iter [01:08, 11.99iter/s]
Best score: 0.2475: : 735iter [01:08, 12.04iter/s]
Best score: 0.2475: : 735iter [01:08, 12.04iter/s]
Best score: 0.2475: : 736iter [01:08, 12.04iter/s]
Best score: 0.2475: : 737iter [01:08, 12.11iter/s]
Best score: 0.2475: : 737iter [01:08, 12.11iter/s]
Best score: 0.2475: : 738iter [01:09, 12.11iter/s]
Best score: 0.2475: : 739iter [01:09, 12.16iter/s]
Best score: 0.2475: : 739iter [01:09, 12.16iter/s]
Best score: 0.2475: : 740iter [01:09, 12.16iter/s]
Best score: 0.2475: : 741iter [01:09, 11.95iter/s]
Best score: 0.2475: : 741iter [01:09, 11.95iter/s]
Best score: 0.2475: : 742iter [01:09, 11.95iter/s]
Best score: 0.2475: : 743iter [01:09, 12.02iter/s]
Best score: 0.2475: : 743iter [01:09, 12.02iter/s]
Best score: 0.2475: : 744iter [01:09, 12.02iter/s]
Best score: 0.2475: : 745iter [01:09, 12.09iter/s]
Best score: 0.2475: : 745iter [01:09, 12.09iter/s]
Best score: 0.2475: : 746iter [01:09, 12.09iter/s]
Best score: 0.2475: : 747iter [01:09, 12.16iter/s]
Best score: 0.2475: : 747iter [01:09, 12.16iter/s]
Best score: 0.2475: : 748iter [01:09, 12.16iter/s]
Best score: 0.2475: : 749iter [01:09, 12.18iter/s]
[ITER 750] Best: 0.2475
[PARAMS] Current best parameters:
  fx: 468.9302
  fy: 468.4998
  px: 869.6540
  py: 1004.2205
  k1: 0.08999917
  k2: -0.03539366
  k3: 0.02223581
  k4: -0.00703756
  p1: -0.01663331
  p2: 0.00990203
  p3: 0.00619647
  p4: -0.00924475
  s1: -0.0004
  s2: 0.0042
  s3: 0.0199
  s4: 0.0067
  tilt_x: 0.0364
  tilt_y: -0.0494
  scale: 3.0368
  rotation: -0.4774

Best score: 0.2475: : 749iter [01:09, 12.18iter/s]
Best score: 0.2475: : 750iter [01:10, 12.18iter/s]
Best score: 0.2475: : 751iter [01:10,  7.84iter/s]
Best score: 0.2475: : 751iter [01:10,  7.84iter/s]
Best score: 0.2475: : 752iter [01:10,  7.84iter/s]
Best score: 0.2475: : 753iter [01:10,  8.80iter/s]
Best score: 0.2475: : 753iter [01:10,  8.80iter/s]
Best score: 0.2475: : 754iter [01:10,  8.80iter/s]
Best score: 0.2475: : 755iter [01:10,  9.63iter/s]
Best score: 0.2475: : 755iter [01:10,  9.63iter/s]
Best score: 0.2475: : 756iter [01:10,  9.63iter/s]
Best score: 0.2475: : 757iter [01:10, 10.26iter/s]
Best score: 0.2475: : 757iter [01:10, 10.26iter/s]
Best score: 0.2475: : 758iter [01:10, 10.26iter/s]
Best score: 0.2475: : 759iter [01:10, 10.72iter/s]
Best score: 0.2203: : 759iter [01:11, 10.72iter/s]
Best score: 0.2203: : 760iter [01:11, 10.72iter/s]
Best score: 0.2203: : 761iter [01:11, 10.98iter/s]
Best score: 0.2203: : 761iter [01:11, 10.98iter/s]
Best score: 0.2203: : 762iter [01:11, 10.98iter/s]
Best score: 0.2203: : 763iter [01:11, 11.34iter/s]
Best score: 0.2203: : 763iter [01:11, 11.34iter/s]
Best score: 0.2203: : 764iter [01:11, 11.34iter/s]
Best score: 0.2203: : 765iter [01:11, 11.62iter/s]
Best score: 0.2203: : 765iter [01:11, 11.62iter/s]
Best score: 0.2203: : 766iter [01:11, 11.62iter/s]
Best score: 0.2203: : 767iter [01:11, 11.83iter/s]
Best score: 0.2203: : 767iter [01:11, 11.83iter/s]
Best score: 0.2203: : 768iter [01:11, 11.83iter/s]
Best score: 0.2203: : 769iter [01:11, 11.97iter/s]
Best score: 0.2203: : 769iter [01:11, 11.97iter/s]
Best score: 0.2203: : 770iter [01:11, 11.97iter/s]
Best score: 0.2203: : 771iter [01:11, 11.76iter/s]
Best score: 0.2203: : 771iter [01:12, 11.76iter/s]
Best score: 0.2203: : 772iter [01:12, 11.76iter/s]
Best score: 0.2203: : 773iter [01:12, 11.83iter/s]
Best score: 0.2203: : 773iter [01:12, 11.83iter/s]
Best score: 0.2203: : 774iter [01:12, 11.83iter/s]
Best score: 0.2203: : 775iter [01:12, 11.98iter/s]
Best score: 0.2203: : 775iter [01:12, 11.98iter/s]
Best score: 0.2203: : 776iter [01:12, 11.98iter/s]
Best score: 0.2203: : 777iter [01:12, 12.06iter/s]
Best score: 0.2203: : 777iter [01:12, 12.06iter/s]
Best score: 0.2203: : 778iter [01:12, 12.06iter/s]
Best score: 0.2203: : 779iter [01:12, 12.13iter/s]
Best score: 0.2203: : 779iter [01:12, 12.13iter/s]
Best score: 0.2203: : 780iter [01:12, 12.13iter/s]
Best score: 0.2203: : 781iter [01:12, 11.97iter/s]
Best score: 0.2203: : 781iter [01:12, 11.97iter/s]
Best score: 0.2203: : 782iter [01:12, 11.97iter/s]
Best score: 0.2203: : 783iter [01:12, 12.08iter/s]
Best score: 0.2203: : 783iter [01:13, 12.08iter/s]
Best score: 0.2203: : 784iter [01:13, 12.08iter/s]
Best score: 0.2203: : 785iter [01:13, 12.06iter/s]
Best score: 0.2203: : 785iter [01:13, 12.06iter/s]
Best score: 0.2203: : 786iter [01:13, 12.06iter/s]
Best score: 0.2203: : 787iter [01:13, 12.14iter/s]
Best score: 0.2203: : 787iter [01:13, 12.14iter/s]
Best score: 0.2203: : 788iter [01:13, 12.14iter/s]
Best score: 0.2203: : 789iter [01:13, 12.20iter/s]
Best score: 0.2117: : 789iter [01:13, 12.20iter/s]
Best score: 0.2117: : 790iter [01:13, 12.20iter/s]
Best score: 0.2117: : 791iter [01:13, 12.02iter/s]
Best score: 0.2117: : 791iter [01:13, 12.02iter/s]
Best score: 0.2117: : 792iter [01:13, 12.02iter/s]
Best score: 0.2117: : 793iter [01:13, 12.03iter/s]
Best score: 0.2117: : 793iter [01:13, 12.03iter/s]
Best score: 0.2117: : 794iter [01:13, 12.03iter/s]
Best score: 0.2117: : 795iter [01:13, 12.10iter/s]
Best score: 0.2117: : 795iter [01:14, 12.10iter/s]
Best score: 0.2117: : 796iter [01:14, 12.10iter/s]
Best score: 0.2117: : 797iter [01:14, 12.13iter/s]
Best score: 0.2117: : 797iter [01:14, 12.13iter/s]
Best score: 0.2117: : 798iter [01:14, 12.13iter/s]
Best score: 0.2117: : 799iter [01:14, 12.17iter/s]
[ITER 800] Best: 0.1957
[PARAMS] Current best parameters:
  fx: 469.4143
  fy: 468.8867
  px: 867.9494
  py: 1002.7532
  k1: 0.08667583
  k2: -0.03120455
  k3: 0.01885635
  k4: -0.00591446
  p1: -0.01532438
  p2: 0.00640786
  p3: 0.00525917
  p4: -0.00399405
  s1: 0.0024
  s2: -0.0006
  s3: 0.0141
  s4: 0.0048
  tilt_x: 0.0272
  tilt_y: -0.0496
  scale: 3.0415
  rotation: -0.4466

Best score: 0.1957: : 799iter [01:14, 12.17iter/s]
Best score: 0.1957: : 800iter [01:14, 12.17iter/s]
Best score: 0.1957: : 801iter [01:14,  7.84iter/s]
Best score: 0.1957: : 801iter [01:14,  7.84iter/s]
Best score: 0.1957: : 802iter [01:14,  7.84iter/s]
Best score: 0.1957: : 803iter [01:14,  8.81iter/s]
Best score: 0.1957: : 803iter [01:14,  8.81iter/s]
Best score: 0.1957: : 804iter [01:15,  8.81iter/s]
Best score: 0.1957: : 805iter [01:15,  9.61iter/s]
Best score: 0.1957: : 805iter [01:15,  9.61iter/s]
Best score: 0.1957: : 806iter [01:15,  9.61iter/s]
Best score: 0.1957: : 807iter [01:15, 10.30iter/s]
Best score: 0.1957: : 807iter [01:15, 10.30iter/s]
Best score: 0.1957: : 808iter [01:15, 10.30iter/s]
Best score: 0.1957: : 809iter [01:15, 10.83iter/s]
Best score: 0.1882: : 809iter [01:15, 10.83iter/s]
Best score: 0.1882: : 810iter [01:15, 10.83iter/s]
Best score: 0.1882: : 811iter [01:15, 11.07iter/s]
Best score: 0.1882: : 811iter [01:15, 11.07iter/s]
Best score: 0.1882: : 812iter [01:15, 11.07iter/s]
Best score: 0.1882: : 813iter [01:15, 11.39iter/s]
Best score: 0.1882: : 813iter [01:15, 11.39iter/s]
Best score: 0.1882: : 814iter [01:15, 11.39iter/s]
Best score: 0.1882: : 815iter [01:15, 11.62iter/s]
Best score: 0.1882: : 815iter [01:15, 11.62iter/s]
Best score: 0.1882: : 816iter [01:16, 11.62iter/s]
Best score: 0.1882: : 817iter [01:16, 11.82iter/s]
Best score: 0.1882: : 817iter [01:16, 11.82iter/s]
Best score: 0.1882: : 818iter [01:16, 11.82iter/s]
Best score: 0.1882: : 819iter [01:16, 11.94iter/s]
Best score: 0.1875: : 819iter [01:16, 11.94iter/s]
Best score: 0.1875: : 820iter [01:16, 11.94iter/s]
Best score: 0.1875: : 821iter [01:16, 11.87iter/s]
Best score: 0.1875: : 821iter [01:16, 11.87iter/s]
Best score: 0.1875: : 822iter [01:16, 11.87iter/s]
Best score: 0.1875: : 823iter [01:16, 12.01iter/s]
Best score: 0.1875: : 823iter [01:16, 12.01iter/s]
Best score: 0.1875: : 824iter [01:16, 12.01iter/s]
Best score: 0.1875: : 825iter [01:16, 12.08iter/s]
Best score: 0.1875: : 825iter [01:16, 12.08iter/s]
Best score: 0.1875: : 826iter [01:16, 12.08iter/s]
Best score: 0.1875: : 827iter [01:16, 12.07iter/s]
Best score: 0.1875: : 827iter [01:16, 12.07iter/s]
Best score: 0.1875: : 828iter [01:17, 12.07iter/s]
Best score: 0.1875: : 829iter [01:17, 12.15iter/s]
Best score: 0.1862: : 829iter [01:17, 12.15iter/s]
Best score: 0.1862: : 830iter [01:17, 12.15iter/s]
Best score: 0.1862: : 831iter [01:17, 11.99iter/s]
Best score: 0.1862: : 831iter [01:17, 11.99iter/s]
Best score: 0.1862: : 832iter [01:17, 11.99iter/s]
Best score: 0.1862: : 833iter [01:17, 12.02iter/s]
Best score: 0.1862: : 833iter [01:17, 12.02iter/s]
Best score: 0.1862: : 834iter [01:17, 12.02iter/s]
Best score: 0.1862: : 835iter [01:17, 12.06iter/s]
Best score: 0.1862: : 835iter [01:17, 12.06iter/s]
Best score: 0.1862: : 836iter [01:17, 12.06iter/s]
Best score: 0.1862: : 837iter [01:17, 12.14iter/s]
Best score: 0.1862: : 837iter [01:17, 12.14iter/s]
Best score: 0.1862: : 838iter [01:17, 12.14iter/s]
Best score: 0.1862: : 839iter [01:17, 12.20iter/s]
Best score: 0.1862: : 839iter [01:17, 12.20iter/s]
Best score: 0.1862: : 840iter [01:18, 12.20iter/s]
Best score: 0.1862: : 841iter [01:18, 11.96iter/s]
Best score: 0.1862: : 841iter [01:18, 11.96iter/s]
Best score: 0.1862: : 842iter [01:18, 11.96iter/s]
Best score: 0.1862: : 843iter [01:18, 12.07iter/s]
Best score: 0.1862: : 843iter [01:18, 12.07iter/s]
Best score: 0.1862: : 844iter [01:18, 12.07iter/s]
Best score: 0.1862: : 845iter [01:18, 12.13iter/s]
Best score: 0.1862: : 845iter [01:18, 12.13iter/s]
Best score: 0.1862: : 846iter [01:18, 12.13iter/s]
Best score: 0.1862: : 847iter [01:18, 12.16iter/s]
Best score: 0.1862: : 847iter [01:18, 12.16iter/s]
Best score: 0.1862: : 848iter [01:18, 12.16iter/s]
Best score: 0.1862: : 849iter [01:18, 12.18iter/s]
[ITER 850] Best: 0.1841
[PARAMS] Current best parameters:
  fx: 466.6698
  fy: 466.2318
  px: 868.1238
  py: 1001.8160
  k1: 0.08873875
  k2: -0.02905413
  k3: 0.01686112
  k4: -0.00528102
  p1: -0.01646017
  p2: 0.00962203
  p3: 0.00583152
  p4: -0.00255681
  s1: -0.0038
  s2: 0.0005
  s3: 0.0156
  s4: 0.0021
  tilt_x: 0.0250
  tilt_y: -0.0433
  scale: 3.0395
  rotation: -0.4664

Best score: 0.1841: : 849iter [01:18, 12.18iter/s]
Best score: 0.1841: : 850iter [01:19, 12.18iter/s]
Best score: 0.1841: : 851iter [01:19,  7.80iter/s]
Best score: 0.1841: : 851iter [01:19,  7.80iter/s]
Best score: 0.1841: : 852iter [01:19,  7.80iter/s]
Best score: 0.1841: : 853iter [01:19,  8.76iter/s]
Best score: 0.1841: : 853iter [01:19,  8.76iter/s]
Best score: 0.1841: : 854iter [01:19,  8.76iter/s]
Best score: 0.1841: : 855iter [01:19,  9.59iter/s]
Best score: 0.1841: : 855iter [01:19,  9.59iter/s]
Best score: 0.1841: : 856iter [01:19,  9.59iter/s]
Best score: 0.1841: : 857iter [01:19, 10.25iter/s]
Best score: 0.1841: : 857iter [01:19, 10.25iter/s]
Best score: 0.1841: : 858iter [01:19, 10.25iter/s]
Best score: 0.1841: : 859iter [01:19, 10.79iter/s]
Best score: 0.1841: : 859iter [01:19, 10.79iter/s]
Best score: 0.1841: : 860iter [01:19, 10.79iter/s]
Best score: 0.1841: : 861iter [01:19, 10.95iter/s]
Best score: 0.1841: : 861iter [01:20, 10.95iter/s]
Best score: 0.1841: : 862iter [01:20, 10.95iter/s]
Best score: 0.1841: : 863iter [01:20, 11.33iter/s]
Best score: 0.1841: : 863iter [01:20, 11.33iter/s]
Best score: 0.1841: : 864iter [01:20, 11.33iter/s]
Best score: 0.1841: : 865iter [01:20, 11.62iter/s]
Best score: 0.1841: : 865iter [01:20, 11.62iter/s]
Best score: 0.1841: : 866iter [01:20, 11.62iter/s]
Best score: 0.1841: : 867iter [01:20, 11.84iter/s]
Best score: 0.1841: : 867iter [01:20, 11.84iter/s]
Best score: 0.1841: : 868iter [01:20, 11.84iter/s]
Best score: 0.1841: : 869iter [01:20, 11.99iter/s]
Best score: 0.1841: : 869iter [01:20, 11.99iter/s]
Best score: 0.1841: : 870iter [01:20, 11.99iter/s]
Best score: 0.1841: : 871iter [01:20, 11.88iter/s]
Best score: 0.1841: : 871iter [01:20, 11.88iter/s]
Best score: 0.1841: : 872iter [01:20, 11.88iter/s]
Best score: 0.1841: : 873iter [01:20, 12.01iter/s]
Best score: 0.1841: : 873iter [01:21, 12.01iter/s]
Best score: 0.1841: : 874iter [01:21, 12.01iter/s]
Best score: 0.1841: : 875iter [01:21, 12.09iter/s]
Best score: 0.1841: : 875iter [01:21, 12.09iter/s]
Best score: 0.1841: : 876iter [01:21, 12.09iter/s]
Best score: 0.1841: : 877iter [01:21, 12.16iter/s]
Best score: 0.1841: : 877iter [01:21, 12.16iter/s]
Best score: 0.1841: : 878iter [01:21, 12.16iter/s]
Best score: 0.1841: : 879iter [01:21, 12.22iter/s]
Best score: 0.1841: : 879iter [01:21, 12.22iter/s]
Best score: 0.1841: : 880iter [01:21, 12.22iter/s]
Best score: 0.1841: : 881iter [01:21, 12.04iter/s]
Best score: 0.1841: : 881iter [01:21, 12.04iter/s]
Best score: 0.1841: : 882iter [01:21, 12.04iter/s]
Best score: 0.1841: : 883iter [01:21, 12.13iter/s]
Best score: 0.1841: : 883iter [01:21, 12.13iter/s]
Best score: 0.1841: : 884iter [01:21, 12.13iter/s]
Best score: 0.1841: : 885iter [01:21, 12.13iter/s]
Best score: 0.1841: : 885iter [01:22, 12.13iter/s]
Best score: 0.1841: : 886iter [01:22, 12.13iter/s]
Best score: 0.1841: : 887iter [01:22, 12.20iter/s]
Best score: 0.1841: : 887iter [01:22, 12.20iter/s]
Best score: 0.1841: : 888iter [01:22, 12.20iter/s]
Best score: 0.1841: : 889iter [01:22, 12.25iter/s]
Best score: 0.1836: : 889iter [01:22, 12.25iter/s]
Best score: 0.1836: : 890iter [01:22, 12.25iter/s]
Best score: 0.1836: : 891iter [01:22, 12.06iter/s]
Best score: 0.1836: : 891iter [01:22, 12.06iter/s]
Best score: 0.1836: : 892iter [01:22, 12.06iter/s]
Best score: 0.1836: : 893iter [01:22, 12.09iter/s]
Best score: 0.1836: : 893iter [01:22, 12.09iter/s]
Best score: 0.1836: : 894iter [01:22, 12.09iter/s]
Best score: 0.1836: : 895iter [01:22, 12.17iter/s]
Best score: 0.1836: : 895iter [01:22, 12.17iter/s]
Best score: 0.1836: : 896iter [01:22, 12.17iter/s]
Best score: 0.1836: : 897iter [01:22, 12.20iter/s]
Best score: 0.1836: : 897iter [01:23, 12.20iter/s]
Best score: 0.1836: : 898iter [01:23, 12.20iter/s]
Best score: 0.1836: : 899iter [01:23, 12.24iter/s]
[ITER 900] Best: 0.1782
[PARAMS] Current best parameters:
  fx: 468.9869
  fy: 468.4458
  px: 865.4227
  py: 1000.4984
  k1: 0.09008012
  k2: -0.03280039
  k3: 0.01794772
  k4: -0.00532647
  p1: -0.01450602
  p2: 0.00832106
  p3: 0.00525743
  p4: -0.00343350
  s1: -0.0039
  s2: 0.0008
  s3: 0.0121
  s4: 0.0039
  tilt_x: 0.0155
  tilt_y: -0.0351
  scale: 3.0312
  rotation: -0.4112

Best score: 0.1782: : 899iter [01:23, 12.24iter/s]
Best score: 0.1782: : 900iter [01:23, 12.24iter/s]
Best score: 0.1782: : 901iter [01:23,  7.81iter/s]
Best score: 0.1782: : 901iter [01:23,  7.81iter/s]
Best score: 0.1782: : 902iter [01:23,  7.81iter/s]
Best score: 0.1782: : 903iter [01:23,  8.76iter/s]
Best score: 0.1782: : 903iter [01:23,  8.76iter/s]
Best score: 0.1782: : 904iter [01:23,  8.76iter/s]
Best score: 0.1782: : 905iter [01:23,  9.57iter/s]
Best score: 0.1782: : 905iter [01:23,  9.57iter/s]
Best score: 0.1782: : 906iter [01:24,  9.57iter/s]
Best score: 0.1782: : 907iter [01:24, 10.19iter/s]
Best score: 0.1782: : 907iter [01:24, 10.19iter/s]
Best score: 0.1782: : 908iter [01:24, 10.19iter/s]
Best score: 0.1782: : 909iter [01:24, 10.75iter/s]
Best score: 0.1704: : 909iter [01:24, 10.75iter/s]
Best score: 0.1704: : 910iter [01:24, 10.75iter/s]
Best score: 0.1704: : 911iter [01:24, 10.99iter/s]
Best score: 0.1704: : 911iter [01:24, 10.99iter/s]
Best score: 0.1704: : 912iter [01:24, 10.99iter/s]
Best score: 0.1704: : 913iter [01:24, 11.34iter/s]
Best score: 0.1704: : 913iter [01:24, 11.34iter/s]
Best score: 0.1704: : 914iter [01:24, 11.34iter/s]
Best score: 0.1704: : 915iter [01:24, 11.59iter/s]
Best score: 0.1704: : 915iter [01:24, 11.59iter/s]
Best score: 0.1704: : 916iter [01:24, 11.59iter/s]
Best score: 0.1704: : 917iter [01:24, 11.76iter/s]
Best score: 0.1704: : 917iter [01:24, 11.76iter/s]
Best score: 0.1704: : 918iter [01:25, 11.76iter/s]
Best score: 0.1704: : 919iter [01:25, 11.88iter/s]
Best score: 0.1704: : 919iter [01:25, 11.88iter/s]
Best score: 0.1704: : 920iter [01:25, 11.88iter/s]
Best score: 0.1704: : 921iter [01:25, 11.80iter/s]
Best score: 0.1704: : 921iter [01:25, 11.80iter/s]
Best score: 0.1704: : 922iter [01:25, 11.80iter/s]
Best score: 0.1704: : 923iter [01:25, 11.96iter/s]
Best score: 0.1704: : 923iter [01:25, 11.96iter/s]
Best score: 0.1704: : 924iter [01:25, 11.96iter/s]
Best score: 0.1704: : 925iter [01:25, 12.08iter/s]
Best score: 0.1704: : 925iter [01:25, 12.08iter/s]
Best score: 0.1704: : 926iter [01:25, 12.08iter/s]
Best score: 0.1704: : 927iter [01:25, 12.15iter/s]
Best score: 0.1704: : 927iter [01:25, 12.15iter/s]
Best score: 0.1704: : 928iter [01:25, 12.15iter/s]
Best score: 0.1704: : 929iter [01:25, 12.21iter/s]
Best score: 0.1683: : 929iter [01:25, 12.21iter/s]
Best score: 0.1683: : 930iter [01:26, 12.21iter/s]
Best score: 0.1683: : 931iter [01:26, 12.03iter/s]
Best score: 0.1683: : 931iter [01:26, 12.03iter/s]
Best score: 0.1683: : 932iter [01:26, 12.03iter/s]
Best score: 0.1683: : 933iter [01:26, 12.12iter/s]
Best score: 0.1683: : 933iter [01:26, 12.12iter/s]
Best score: 0.1683: : 934iter [01:26, 12.12iter/s]
Best score: 0.1683: : 935iter [01:26, 12.19iter/s]
Best score: 0.1683: : 935iter [01:26, 12.19iter/s]
Best score: 0.1683: : 936iter [01:26, 12.19iter/s]
Best score: 0.1683: : 937iter [01:26, 12.18iter/s]
Best score: 0.1683: : 937iter [01:26, 12.18iter/s]
Best score: 0.1683: : 938iter [01:26, 12.18iter/s]
Best score: 0.1683: : 939iter [01:26, 12.22iter/s]
Best score: 0.1683: : 939iter [01:26, 12.22iter/s]
Best score: 0.1683: : 940iter [01:26, 12.22iter/s]
Best score: 0.1683: : 941iter [01:26, 12.04iter/s]
Best score: 0.1683: : 941iter [01:26, 12.04iter/s]
Best score: 0.1683: : 942iter [01:27, 12.04iter/s]
Best score: 0.1683: : 943iter [01:27, 12.13iter/s]
Best score: 0.1683: : 943iter [01:27, 12.13iter/s]
Best score: 0.1683: : 944iter [01:27, 12.13iter/s]
Best score: 0.1683: : 945iter [01:27, 12.20iter/s]
Best score: 0.1683: : 945iter [01:27, 12.20iter/s]
Best score: 0.1683: : 946iter [01:27, 12.20iter/s]
Best score: 0.1683: : 947iter [01:27, 12.23iter/s]
Best score: 0.1683: : 947iter [01:27, 12.23iter/s]
Best score: 0.1683: : 948iter [01:27, 12.23iter/s]
Best score: 0.1683: : 949iter [01:27, 12.28iter/s]
[ITER 950] Best: 0.1674
[PARAMS] Current best parameters:
  fx: 471.4676
  fy: 471.1879
  px: 863.1744
  py: 1000.5887
  k1: 0.08882905
  k2: -0.03448643
  k3: 0.01811944
  k4: -0.00515818
  p1: -0.01435889
  p2: 0.00843750
  p3: 0.00846854
  p4: -0.00511499
  s1: -0.0087
  s2: 0.0024
  s3: 0.0090
  s4: 0.0055
  tilt_x: 0.0154
  tilt_y: -0.0247
  scale: 3.0286
  rotation: -0.4129

Best score: 0.1674: : 949iter [01:27, 12.28iter/s]
Best score: 0.1674: : 950iter [01:27, 12.28iter/s]
Best score: 0.1674: : 951iter [01:27,  7.85iter/s]
Best score: 0.1674: : 951iter [01:28,  7.85iter/s]
Best score: 0.1674: : 952iter [01:28,  7.85iter/s]
Best score: 0.1674: : 953iter [01:28,  8.78iter/s]
Best score: 0.1674: : 953iter [01:28,  8.78iter/s]
Best score: 0.1674: : 954iter [01:28,  8.78iter/s]
Best score: 0.1674: : 955iter [01:28,  9.61iter/s]
Best score: 0.1674: : 955iter [01:28,  9.61iter/s]
Best score: 0.1674: : 956iter [01:28,  9.61iter/s]
Best score: 0.1674: : 957iter [01:28, 10.28iter/s]
Best score: 0.1674: : 957iter [01:28, 10.28iter/s]
Best score: 0.1674: : 958iter [01:28, 10.28iter/s]
Best score: 0.1674: : 959iter [01:28, 10.83iter/s]
Best score: 0.1671: : 959iter [01:28, 10.83iter/s]
Best score: 0.1671: : 960iter [01:28, 10.83iter/s]
Best score: 0.1671: : 961iter [01:28, 11.00iter/s]
Best score: 0.1671: : 961iter [01:28, 11.00iter/s]
Best score: 0.1671: : 962iter [01:28, 11.00iter/s]
Best score: 0.1671: : 963iter [01:28, 11.32iter/s]
Best score: 0.1671: : 963iter [01:29, 11.32iter/s]
Best score: 0.1671: : 964iter [01:29, 11.32iter/s]
Best score: 0.1671: : 965iter [01:29, 11.60iter/s]
Best score: 0.1671: : 965iter [01:29, 11.60iter/s]
Best score: 0.1671: : 966iter [01:29, 11.60iter/s]
Best score: 0.1671: : 967iter [01:29, 11.77iter/s]
Best score: 0.1671: : 967iter [01:29, 11.77iter/s]
Best score: 0.1671: : 968iter [01:29, 11.77iter/s]
Best score: 0.1671: : 969iter [01:29, 11.93iter/s]
Best score: 0.1667: : 969iter [01:29, 11.93iter/s]
Best score: 0.1667: : 970iter [01:29, 11.93iter/s]
Best score: 0.1667: : 971iter [01:29, 11.84iter/s]
Best score: 0.1667: : 971iter [01:29, 11.84iter/s]
Best score: 0.1667: : 972iter [01:29, 11.84iter/s]
Best score: 0.1667: : 973iter [01:29, 11.97iter/s]
Best score: 0.1667: : 973iter [01:29, 11.97iter/s]
Best score: 0.1667: : 974iter [01:29, 11.97iter/s]
Best score: 0.1667: : 975iter [01:29, 12.06iter/s]
Best score: 0.1667: : 975iter [01:30, 12.06iter/s]
Best score: 0.1667: : 976iter [01:30, 12.06iter/s]
Best score: 0.1667: : 977iter [01:30, 12.13iter/s]
Best score: 0.1667: : 977iter [01:30, 12.13iter/s]
Best score: 0.1667: : 978iter [01:30, 12.13iter/s]
Best score: 0.1667: : 979iter [01:30, 12.18iter/s]
Best score: 0.1666: : 979iter [01:30, 12.18iter/s]
Best score: 0.1666: : 980iter [01:30, 12.18iter/s]
Best score: 0.1666: : 981iter [01:30, 11.99iter/s]
Best score: 0.1666: : 981iter [01:30, 11.99iter/s]
Best score: 0.1666: : 982iter [01:30, 11.99iter/s]
Best score: 0.1666: : 983iter [01:30, 12.01iter/s]
Best score: 0.1666: : 983iter [01:30, 12.01iter/s]
Best score: 0.1666: : 984iter [01:30, 12.01iter/s]
Best score: 0.1666: : 985iter [01:30, 12.09iter/s]
Best score: 0.1666: : 985iter [01:30, 12.09iter/s]
Best score: 0.1666: : 986iter [01:30, 12.09iter/s]
Best score: 0.1666: : 987iter [01:30, 12.11iter/s]
Best score: 0.1666: : 987iter [01:31, 12.11iter/s]
Best score: 0.1666: : 988iter [01:31, 12.11iter/s]
Best score: 0.1666: : 989iter [01:31, 12.17iter/s]
Best score: 0.1658: : 989iter [01:31, 12.17iter/s]
Best score: 0.1658: : 990iter [01:31, 12.17iter/s]
Best score: 0.1658: : 991iter [01:31, 12.02iter/s]
Best score: 0.1658: : 991iter [01:31, 12.02iter/s]
Best score: 0.1658: : 992iter [01:31, 12.02iter/s]
Best score: 0.1658: : 993iter [01:31, 12.00iter/s]
Best score: 0.1658: : 993iter [01:31, 12.00iter/s]
Best score: 0.1658: : 994iter [01:31, 12.00iter/s]
Best score: 0.1658: : 995iter [01:31, 12.10iter/s]
Best score: 0.1658: : 995iter [01:31, 12.10iter/s]
Best score: 0.1658: : 996iter [01:31, 12.10iter/s]
Best score: 0.1658: : 997iter [01:31, 12.09iter/s]
Best score: 0.1658: : 997iter [01:31, 12.09iter/s]
Best score: 0.1658: : 998iter [01:31, 12.09iter/s]
Best score: 0.1658: : 999iter [01:31, 12.08iter/s]
[ITER 1000] Best: 0.1651
[PARAMS] Current best parameters:
  fx: 473.9349
  fy: 473.6529
  px: 860.7708
  py: 999.4365
  k1: 0.08856101
  k2: -0.03787099
  k3: 0.01930378
  k4: -0.00513264
  p1: -0.01494936
  p2: 0.00654541
  p3: 0.01300591
  p4: -0.00708034
  s1: -0.0146
  s2: 0.0051
  s3: 0.0035
  s4: 0.0077
  tilt_x: 0.0118
  tilt_y: -0.0189
  scale: 3.0261
  rotation: -0.4056

Best score: 0.1651: : 999iter [01:32, 12.08iter/s]
Best score: 0.1651: : 1000iter [01:32, 12.08iter/s]
Best score: 0.1651: : 1001iter [01:32,  7.81iter/s]
Best score: 0.1651: : 1001iter [01:32,  7.81iter/s]
Best score: 0.1651: : 1002iter [01:32,  7.81iter/s]
Best score: 0.1651: : 1003iter [01:32,  8.77iter/s]
Best score: 0.1651: : 1003iter [01:32,  8.77iter/s]
Best score: 0.1651: : 1004iter [01:32,  8.77iter/s]
Best score: 0.1651: : 1005iter [01:32,  9.60iter/s]
Best score: 0.1651: : 1005iter [01:32,  9.60iter/s]
Best score: 0.1651: : 1006iter [01:32,  9.60iter/s]
Best score: 0.1651: : 1007iter [01:32, 10.27iter/s]
Best score: 0.1651: : 1007iter [01:33, 10.27iter/s]
Best score: 0.1651: : 1008iter [01:33, 10.27iter/s]
Best score: 0.1651: : 1009iter [01:33, 10.74iter/s]
Best score: 0.1648: : 1009iter [01:33, 10.74iter/s]
Best score: 0.1648: : 1010iter [01:33, 10.74iter/s]
Best score: 0.1648: : 1011iter [01:33, 10.91iter/s]
Best score: 0.1648: : 1011iter [01:33, 10.91iter/s]
Best score: 0.1648: : 1012iter [01:33, 10.91iter/s]
Best score: 0.1648: : 1013iter [01:33, 11.28iter/s]
Best score: 0.1648: : 1013iter [01:33, 11.28iter/s]
Best score: 0.1648: : 1014iter [01:33, 11.28iter/s]
Best score: 0.1648: : 1015iter [01:33, 11.57iter/s]
Best score: 0.1648: : 1015iter [01:33, 11.57iter/s]
Best score: 0.1648: : 1016iter [01:33, 11.57iter/s]
Best score: 0.1648: : 1017iter [01:33, 11.79iter/s]
Best score: 0.1648: : 1017iter [01:33, 11.79iter/s]
Best score: 0.1648: : 1018iter [01:33, 11.79iter/s]
Best score: 0.1648: : 1019iter [01:33, 11.90iter/s]
Best score: 0.1643: : 1019iter [01:34, 11.90iter/s]
Best score: 0.1643: : 1020iter [01:34, 11.90iter/s]
Best score: 0.1643: : 1021iter [01:34, 11.76iter/s]
Best score: 0.1643: : 1021iter [01:34, 11.76iter/s]
Best score: 0.1643: : 1022iter [01:34, 11.76iter/s]
Best score: 0.1643: : 1023iter [01:34, 11.91iter/s]
Best score: 0.1643: : 1023iter [01:34, 11.91iter/s]
Best score: 0.1643: : 1024iter [01:34, 11.91iter/s]
Best score: 0.1643: : 1025iter [01:34, 12.00iter/s]
Best score: 0.1643: : 1025iter [01:34, 12.00iter/s]
Best score: 0.1643: : 1026iter [01:34, 12.00iter/s]
Best score: 0.1643: : 1027iter [01:34, 12.10iter/s]
Best score: 0.1643: : 1027iter [01:34, 12.10iter/s]
Best score: 0.1643: : 1028iter [01:34, 12.10iter/s]
Best score: 0.1643: : 1029iter [01:34, 12.18iter/s]
Best score: 0.1643: : 1029iter [01:34, 12.18iter/s]
Best score: 0.1643: : 1030iter [01:34, 12.18iter/s]
Best score: 0.1643: : 1031iter [01:34, 12.02iter/s]
Best score: 0.1643: : 1031iter [01:34, 12.02iter/s]
Best score: 0.1643: : 1032iter [01:35, 12.02iter/s]
Best score: 0.1643: : 1033iter [01:35, 12.06iter/s]
Best score: 0.1643: : 1033iter [01:35, 12.06iter/s]
Best score: 0.1643: : 1034iter [01:35, 12.06iter/s]
Best score: 0.1643: : 1035iter [01:35, 12.14iter/s]
Best score: 0.1643: : 1035iter [01:35, 12.14iter/s]
Best score: 0.1643: : 1036iter [01:35, 12.14iter/s]
Best score: 0.1643: : 1037iter [01:35, 12.18iter/s]
Best score: 0.1643: : 1037iter [01:35, 12.18iter/s]
Best score: 0.1643: : 1038iter [01:35, 12.18iter/s]
Best score: 0.1643: : 1039iter [01:35, 12.22iter/s]
Best score: 0.1643: : 1039iter [01:35, 12.22iter/s]
Best score: 0.1643: : 1040iter [01:35, 12.22iter/s]
Best score: 0.1643: : 1041iter [01:35, 11.94iter/s]
Best score: 0.1643: : 1041iter [01:35, 11.94iter/s]
Best score: 0.1643: : 1042iter [01:35, 11.94iter/s]
Best score: 0.1643: : 1043iter [01:35, 12.03iter/s]
Best score: 0.1643: : 1043iter [01:35, 12.03iter/s]
Best score: 0.1643: : 1044iter [01:36, 12.03iter/s]
Best score: 0.1643: : 1045iter [01:36, 12.10iter/s]
Best score: 0.1643: : 1045iter [01:36, 12.10iter/s]
Best score: 0.1643: : 1046iter [01:36, 12.10iter/s]
Best score: 0.1643: : 1047iter [01:36, 12.18iter/s]
Best score: 0.1643: : 1047iter [01:36, 12.18iter/s]
Best score: 0.1643: : 1048iter [01:36, 12.18iter/s]
Best score: 0.1643: : 1049iter [01:36, 12.21iter/s]
[ITER 1050] Best: 0.1639
[PARAMS] Current best parameters:
  fx: 473.7068
  fy: 473.4513
  px: 861.1704
  py: 999.7221
  k1: 0.08743387
  k2: -0.03690071
  k3: 0.01956071
  k4: -0.00536337
  p1: -0.01436750
  p2: 0.00781522
  p3: 0.00932373
  p4: -0.00547804
  s1: -0.0113
  s2: 0.0032
  s3: 0.0072
  s4: 0.0056
  tilt_x: 0.0121
  tilt_y: -0.0178
  scale: 3.0277
  rotation: -0.4194

Best score: 0.1639: : 1049iter [01:36, 12.21iter/s]
Best score: 0.1639: : 1050iter [01:36, 12.21iter/s]
Best score: 0.1639: : 1051iter [01:36,  7.84iter/s]
Best score: 0.1639: : 1051iter [01:36,  7.84iter/s]
Best score: 0.1639: : 1052iter [01:37,  7.84iter/s]
Best score: 0.1639: : 1053iter [01:37,  8.77iter/s]
Best score: 0.1639: : 1053iter [01:37,  8.77iter/s]
Best score: 0.1639: : 1054iter [01:37,  8.77iter/s]
Best score: 0.1639: : 1055iter [01:37,  9.60iter/s]
Best score: 0.1639: : 1055iter [01:37,  9.60iter/s]
Best score: 0.1639: : 1056iter [01:37,  9.60iter/s]
Best score: 0.1639: : 1057iter [01:37, 10.28iter/s]
Best score: 0.1639: : 1057iter [01:37, 10.28iter/s]
Best score: 0.1639: : 1058iter [01:37, 10.28iter/s]
Best score: 0.1639: : 1059iter [01:37, 10.78iter/s]
Best score: 0.1639: : 1059iter [01:37, 10.78iter/s]
Best score: 0.1639: : 1060iter [01:37, 10.78iter/s]
Best score: 0.1639: : 1061iter [01:37, 10.99iter/s]
Best score: 0.1639: : 1061iter [01:37, 10.99iter/s]
Best score: 0.1639: : 1062iter [01:37, 10.99iter/s]
Best score: 0.1639: : 1063iter [01:37, 11.28iter/s]
Best score: 0.1639: : 1063iter [01:37, 11.28iter/s]
Best score: 0.1639: : 1064iter [01:38, 11.28iter/s]
Best score: 0.1639: : 1065iter [01:38, 11.47iter/s]
Best score: 0.1639: : 1065iter [01:38, 11.47iter/s]
Best score: 0.1639: : 1066iter [01:38, 11.47iter/s]
Best score: 0.1639: : 1067iter [01:38, 11.70iter/s]
Best score: 0.1639: : 1067iter [01:38, 11.70iter/s]
Best score: 0.1639: : 1068iter [01:38, 11.70iter/s]
Best score: 0.1639: : 1069iter [01:38, 11.88iter/s]
Best score: 0.1639: : 1069iter [01:38, 11.88iter/s]
Best score: 0.1639: : 1070iter [01:38, 11.88iter/s]
Best score: 0.1639: : 1071iter [01:38, 11.81iter/s]
Best score: 0.1639: : 1071iter [01:38, 11.81iter/s]
Best score: 0.1639: : 1072iter [01:38, 11.81iter/s]
Best score: 0.1639: : 1073iter [01:38, 11.96iter/s]
Best score: 0.1639: : 1073iter [01:38, 11.96iter/s]
Best score: 0.1639: : 1074iter [01:38, 11.96iter/s]
Best score: 0.1639: : 1075iter [01:38, 12.07iter/s]
Best score: 0.1639: : 1075iter [01:38, 12.07iter/s]
Best score: 0.1639: : 1076iter [01:39, 12.07iter/s]
Best score: 0.1639: : 1077iter [01:39, 12.13iter/s]
Best score: 0.1639: : 1077iter [01:39, 12.13iter/s]
Best score: 0.1639: : 1078iter [01:39, 12.13iter/s]
Best score: 0.1639: : 1079iter [01:39, 12.14iter/s]
Best score: 0.1639: : 1079iter [01:39, 12.14iter/s]
Best score: 0.1639: : 1080iter [01:39, 12.14iter/s]
Best score: 0.1639: : 1081iter [01:39, 11.89iter/s]
Best score: 0.1639: : 1081iter [01:39, 11.89iter/s]
Best score: 0.1639: : 1082iter [01:39, 11.89iter/s]
Best score: 0.1639: : 1083iter [01:39, 11.93iter/s]
Best score: 0.1639: : 1083iter [01:39, 11.93iter/s]
Best score: 0.1639: : 1084iter [01:39, 11.93iter/s]
Best score: 0.1639: : 1085iter [01:39, 11.99iter/s]
Best score: 0.1639: : 1085iter [01:39, 11.99iter/s]
Best score: 0.1639: : 1086iter [01:39, 11.99iter/s]
Best score: 0.1639: : 1087iter [01:39, 12.08iter/s]
Best score: 0.1639: : 1087iter [01:39, 12.08iter/s]
Best score: 0.1639: : 1088iter [01:39, 12.08iter/s]
Best score: 0.1639: : 1089iter [01:39, 12.15iter/s]
Best score: 0.1637: : 1089iter [01:40, 12.15iter/s]
Best score: 0.1637: : 1090iter [01:40, 12.15iter/s]
Best score: 0.1637: : 1091iter [01:40, 11.97iter/s]
Best score: 0.1637: : 1091iter [01:40, 11.97iter/s]
Best score: 0.1637: : 1092iter [01:40, 11.97iter/s]
Best score: 0.1637: : 1093iter [01:40, 11.98iter/s]
Best score: 0.1637: : 1093iter [01:40, 11.98iter/s]
Best score: 0.1637: : 1094iter [01:40, 11.98iter/s]
Best score: 0.1637: : 1095iter [01:40, 12.02iter/s]
Best score: 0.1637: : 1095iter [01:40, 12.02iter/s]
Best score: 0.1637: : 1096iter [01:40, 12.02iter/s]
Best score: 0.1637: : 1097iter [01:40, 12.12iter/s]
Best score: 0.1637: : 1097iter [01:40, 12.12iter/s]
Best score: 0.1637: : 1098iter [01:40, 12.12iter/s]
Best score: 0.1637: : 1099iter [01:40, 12.17iter/s]
[ITER 1100] Best: 0.1636
[PARAMS] Current best parameters:
  fx: 473.4336
  fy: 473.1591
  px: 862.0012
  py: 999.8270
  k1: 0.08770996
  k2: -0.03744798
  k3: 0.02028708
  k4: -0.00560685
  p1: -0.01422765
  p2: 0.00921189
  p3: 0.00606904
  p4: -0.00461942
  s1: -0.0089
  s2: 0.0024
  s3: 0.0103
  s4: 0.0047
  tilt_x: 0.0123
  tilt_y: -0.0185
  scale: 3.0279
  rotation: -0.4144

Best score: 0.1636: : 1099iter [01:40, 12.17iter/s]
Best score: 0.1636: : 1100iter [01:41, 10.87iter/s]

[📈] Running L-BFGS-B polish after 1100 DE iterations...
  Polish did not improve score: 0.163625

[⭕] Ring refinement pass (3500mm diameter)...
  Points: 97,792 → 90,011 within 3500mm ring
  Ring polish did not improve score: 0.163625
  Success: False
  Tangential distortion: p1=-0.014228, p2=0.009212, p3=0.006069, p4=-0.004619
  ✓ Tangential correction is significant for corner improvement
[✅] Square reference optimization complete. Score: 0.1636
[✅] Parameters copied to: /working/MDCP3D-SL-013_W046(6)/calibration/params.json
[📌] Selecting best parameters...
[✅] Saved final refined parameters.


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


[DEBUG] Parameters being applied to PTD conversion:
    fx: 473.43355951379294
    fy: 473.15914667419923
    px: 862.001164360541
    py: 999.8270033206016
    k1: 0.0877099626678541
    k2: -0.03744797502437501
    k3: 0.020287079539891183
    k4: -0.005606853886651459
    p1: -0.014227650547717331
    p2: 0.009211890804604295
    p3: 0.006069039927711562
    p4: -0.004619423955694202
    scale: 3.0279057263563214
    rotation: -0.4143897043272726
    mmpp: 3.4792092606184974

[🔄] Converting 1397 frames to PTD, creating debug images for 400 calibration frames...

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[✅] Saved PTDs: /working/MDCP3D-SL-013_W046(6)/calibration/debug/4_undistorted/output/ptd

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[✅] Saved PTDs: /working/MDCP3D-SL-013_W046(6)/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.

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📤 Writing LUT:  65%|██████▍   | 2102373/3240000 [00:02<00:01, 880226.04px/s]
📤 Writing LUT:  68%|██████▊   | 2190593/3240000 [00:02<00:01, 880810.84px/s]
📤 Writing LUT:  70%|███████   | 2281237/3240000 [00:02<00:01, 888451.74px/s]
📤 Writing LUT:  73%|███████▎  | 2370096/3240000 [00:02<00:00, 886919.82px/s]
📤 Writing LUT:  76%|███████▌  | 2458798/3240000 [00:02<00:00, 883772.55px/s]
📤 Writing LUT:  79%|███████▊  | 2547184/3240000 [00:02<00:00, 878686.64px/s]
📤 Writing LUT:  81%|████████▏ | 2635063/3240000 [00:03<00:00, 876318.55px/s]
📤 Writing LUT:  84%|████████▍ | 2723169/3240000 [00:03<00:00, 877730.03px/s]
📤 Writing LUT:  87%|████████▋ | 2810948/3240000 [00:03<00:00, 877494.06px/s]
📤 Writing LUT:  89%|████████▉ | 2898702/3240000 [00:03<00:00, 873874.37px/s]
📤 Writing LUT:  92%|█████████▏| 2986095/3240000 [00:03<00:00, 870415.69px/s]
📤 Writing LUT:  95%|█████████▍| 3073142/3240000 [00:03<00:00, 868470.03px/s]
📤 Writing LUT:  98%|█████████▊| 3160204/3240000 [00:03<00:00, 869109.36px/s]
📤 Writing LUT: 100%|██████████| 3240000/3240000 [00:03<00:00, 872785.77px/s]
[✅] LUT written to: /working/MDCP3D-SL-013_W046(6)/calibration/debug/4_undistorted/output/LUT.lut
[WARN] Folder name 'MDCP3D-SL-013_W046(6)' does not match expected pattern MDC042_W007_5_28_2025. Using simple naming convention.
[✅] LUT copied to: /working/MDCP3D-SL-013_W046(6)/calibration/MDCP3D-SL-013_W046(6)_unknown.lut

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

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

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

   🔥 2000L:   0%|          | 0/327 [00:00<?, ?frame/s]

   🔥 2000L:   2%|▏         | 8/327 [00:00<00:04, 74.78frame/s]

   🔥 2000L:   5%|▌         | 17/327 [00:00<00:03, 80.80frame/s]

   🔥 2000L:   8%|▊         | 27/327 [00:00<00:03, 86.52frame/s]

   🔥 2000L:  11%|█▏        | 37/327 [00:00<00:03, 90.04frame/s]

   🔥 2000L:  15%|█▍        | 48/327 [00:00<00:02, 94.66frame/s]

   🔥 2000L:  18%|█▊        | 59/327 [00:00<00:02, 98.54frame/s]

   🔥 2000L:  21%|██▏       | 70/327 [00:00<00:02, 101.16frame/s]

   🔥 2000L:  25%|██▍       | 81/327 [00:00<00:02, 102.48frame/s]

   🔥 2000L:  28%|██▊       | 92/327 [00:00<00:02, 102.51frame/s]

   🔥 2000L:  31%|███▏      | 103/327 [00:01<00:02, 102.62frame/s]

   🔥 2000L:  35%|███▍      | 114/327 [00:01<00:02, 102.20frame/s]

   🔥 2000L:  38%|███▊      | 125/327 [00:01<00:02, 100.01frame/s]

   🔥 2000L:  42%|████▏     | 136/327 [00:01<00:01, 98.54frame/s] 

   🔥 2000L:  45%|████▍     | 146/327 [00:01<00:01, 98.62frame/s]

   🔥 2000L:  48%|████▊     | 157/327 [00:01<00:01, 99.21frame/s]

   🔥 2000L:  52%|█████▏    | 169/327 [00:01<00:01, 103.00frame/s]

   🔥 2000L:  55%|█████▌    | 181/327 [00:01<00:01, 105.63frame/s]

   🔥 2000L:  59%|█████▊    | 192/327 [00:01<00:01, 106.15frame/s]

   🔥 2000L:  62%|██████▏   | 203/327 [00:02<00:01, 105.60frame/s]

   🔥 2000L:  65%|██████▌   | 214/327 [00:02<00:01, 102.47frame/s]

   🔥 2000L:  69%|██████▉   | 225/327 [00:02<00:01, 97.19frame/s] 

   🔥 2000L:  72%|███████▏  | 235/327 [00:02<00:00, 93.57frame/s]

   🔥 2000L:  75%|███████▍  | 245/327 [00:02<00:00, 90.75frame/s]

   🔥 2000L:  78%|███████▊  | 255/327 [00:02<00:00, 88.05frame/s]

   🔥 2000L:  81%|████████  | 264/327 [00:02<00:00, 85.84frame/s]

   🔥 2000L:  83%|████████▎ | 273/327 [00:02<00:00, 84.19frame/s]

   🔥 2000L:  86%|████████▌ | 282/327 [00:02<00:00, 83.33frame/s]

   🔥 2000L:  89%|████████▉ | 291/327 [00:03<00:00, 80.57frame/s]

   🔥 2000L:  92%|█████████▏| 300/327 [00:03<00:00, 78.63frame/s]

   🔥 2000L:  94%|█████████▍| 308/327 [00:03<00:00, 78.38frame/s]

   🔥 2000L:  97%|█████████▋| 316/327 [00:03<00:00, 77.83frame/s]

   🔥 2000L:  99%|█████████▉| 324/327 [00:03<00:00, 77.39frame/s]

                                                                 [✅] 2000L: /working/MDCP3D-SL-013_W046(6)/calibration/debug/5_heatmap/2000L_heatmap.png
[✅] 2000L (fitted): /working/MDCP3D-SL-013_W046(6)/calibration/debug/5_heatmap/2000L_heatmap_fitted.png

📁 Rigs (heatmap):  25%|██▌       | 1/4 [00:05<00:15,  5.27s/rig]

   🔥 2000R:   0%|          | 0/295 [00:00<?, ?frame/s]

   🔥 2000R:   3%|▎         | 8/295 [00:00<00:03, 76.67frame/s]

   🔥 2000R:   6%|▌         | 17/295 [00:00<00:03, 80.10frame/s]

   🔥 2000R:   9%|▉         | 26/295 [00:00<00:03, 84.05frame/s]

   🔥 2000R:  12%|█▏        | 36/295 [00:00<00:02, 87.60frame/s]

   🔥 2000R:  16%|█▌        | 47/295 [00:00<00:02, 92.71frame/s]

   🔥 2000R:  20%|█▉        | 58/295 [00:00<00:02, 97.31frame/s]

   🔥 2000R:  23%|██▎       | 69/295 [00:00<00:02, 98.84frame/s]

   🔥 2000R:  27%|██▋       | 79/295 [00:00<00:02, 98.85frame/s]

   🔥 2000R:  30%|███       | 89/295 [00:00<00:02, 99.16frame/s]

   🔥 2000R:  34%|███▍      | 100/295 [00:01<00:01, 99.98frame/s]

   🔥 2000R:  38%|███▊      | 111/295 [00:01<00:01, 100.05frame/s]

   🔥 2000R:  41%|████▏     | 122/295 [00:01<00:01, 99.75frame/s] 

   🔥 2000R:  45%|████▌     | 133/295 [00:01<00:01, 100.87frame/s]

   🔥 2000R:  49%|████▉     | 144/295 [00:01<00:01, 102.55frame/s]

   🔥 2000R:  53%|█████▎    | 156/295 [00:01<00:01, 105.50frame/s]

   🔥 2000R:  57%|█████▋    | 168/295 [00:01<00:01, 107.73frame/s]

   🔥 2000R:  61%|██████    | 180/295 [00:01<00:01, 109.88frame/s]

   🔥 2000R:  65%|██████▌   | 192/295 [00:01<00:00, 110.65frame/s]

   🔥 2000R:  69%|██████▉   | 204/295 [00:02<00:00, 106.65frame/s]

   🔥 2000R:  73%|███████▎  | 215/295 [00:02<00:00, 102.42frame/s]

   🔥 2000R:  77%|███████▋  | 226/295 [00:02<00:00, 99.70frame/s] 

   🔥 2000R:  80%|████████  | 237/295 [00:02<00:00, 96.45frame/s]

   🔥 2000R:  84%|████████▎ | 247/295 [00:02<00:00, 92.74frame/s]

   🔥 2000R:  87%|████████▋ | 257/295 [00:02<00:00, 90.51frame/s]

   🔥 2000R:  91%|█████████ | 267/295 [00:02<00:00, 88.28frame/s]

   🔥 2000R:  94%|█████████▎| 276/295 [00:02<00:00, 86.86frame/s]

   🔥 2000R:  97%|█████████▋| 285/295 [00:02<00:00, 85.54frame/s]

   🔥 2000R: 100%|█████████▉| 294/295 [00:03<00:00, 84.31frame/s]

                                                                 [✅] 2000R: /working/MDCP3D-SL-013_W046(6)/calibration/debug/5_heatmap/2000R_heatmap.png
[✅] 2000R (fitted): /working/MDCP3D-SL-013_W046(6)/calibration/debug/5_heatmap/2000R_heatmap_fitted.png

📁 Rigs (heatmap):  50%|█████     | 2/4 [00:10<00:09,  4.97s/rig]

   🔥 1000:   0%|          | 0/302 [00:00<?, ?frame/s]

   🔥 1000:   3%|▎         | 8/302 [00:00<00:03, 78.69frame/s]

   🔥 1000:   6%|▌         | 17/302 [00:00<00:03, 80.90frame/s]

   🔥 1000:   9%|▊         | 26/302 [00:00<00:03, 81.58frame/s]

   🔥 1000:  12%|█▏        | 35/302 [00:00<00:03, 81.76frame/s]

   🔥 1000:  15%|█▍        | 44/302 [00:00<00:03, 80.28frame/s]

   🔥 1000:  18%|█▊        | 53/302 [00:00<00:03, 80.74frame/s]

   🔥 1000:  21%|██        | 62/302 [00:00<00:02, 80.42frame/s]

   🔥 1000:  24%|██▎       | 71/302 [00:00<00:02, 79.80frame/s]

   🔥 1000:  26%|██▋       | 80/302 [00:00<00:02, 79.74frame/s]

   🔥 1000:  29%|██▉       | 89/302 [00:01<00:02, 79.97frame/s]

   🔥 1000:  32%|███▏      | 98/302 [00:01<00:02, 80.45frame/s]

   🔥 1000:  35%|███▌      | 107/302 [00:01<00:02, 79.88frame/s]

   🔥 1000:  38%|███▊      | 115/302 [00:01<00:02, 79.38frame/s]

   🔥 1000:  41%|████      | 123/302 [00:01<00:02, 78.48frame/s]

   🔥 1000:  43%|████▎     | 131/302 [00:01<00:02, 78.14frame/s]

   🔥 1000:  46%|████▌     | 139/302 [00:01<00:02, 77.84frame/s]

   🔥 1000:  49%|████▉     | 148/302 [00:01<00:01, 79.08frame/s]

   🔥 1000:  52%|█████▏    | 157/302 [00:01<00:01, 79.49frame/s]

   🔥 1000:  55%|█████▍    | 166/302 [00:02<00:01, 81.39frame/s]

   🔥 1000:  58%|█████▊    | 176/302 [00:02<00:01, 84.22frame/s]

   🔥 1000:  62%|██████▏   | 186/302 [00:02<00:01, 85.84frame/s]

   🔥 1000:  65%|██████▍   | 195/302 [00:02<00:01, 85.77frame/s]

   🔥 1000:  68%|██████▊   | 204/302 [00:02<00:01, 85.82frame/s]

   🔥 1000:  71%|███████   | 213/302 [00:02<00:01, 85.55frame/s]

   🔥 1000:  74%|███████▎  | 222/302 [00:02<00:00, 86.12frame/s]

   🔥 1000:  76%|███████▋  | 231/302 [00:02<00:00, 85.67frame/s]

   🔥 1000:  79%|███████▉  | 240/302 [00:02<00:00, 84.90frame/s]

   🔥 1000:  82%|████████▏ | 249/302 [00:03<00:00, 85.19frame/s]

   🔥 1000:  85%|████████▌ | 258/302 [00:03<00:00, 84.60frame/s]

   🔥 1000:  88%|████████▊ | 267/302 [00:03<00:00, 83.29frame/s]

   🔥 1000:  91%|█████████▏| 276/302 [00:03<00:00, 82.33frame/s]

   🔥 1000:  94%|█████████▍| 285/302 [00:03<00:00, 82.08frame/s]

   🔥 1000:  97%|█████████▋| 294/302 [00:03<00:00, 82.13frame/s]

                                                                [✅] 1000: /working/MDCP3D-SL-013_W046(6)/calibration/debug/5_heatmap/1000_heatmap.png
[✅] 1000 (fitted): /working/MDCP3D-SL-013_W046(6)/calibration/debug/5_heatmap/1000_heatmap_fitted.png

📁 Rigs (heatmap):  75%|███████▌  | 3/4 [00:14<00:04,  4.71s/rig]

   🔥 1500:   0%|          | 0/473 [00:00<?, ?frame/s]

   🔥 1500:   2%|▏         | 9/473 [00:00<00:05, 89.25frame/s]

   🔥 1500:   4%|▍         | 18/473 [00:00<00:05, 81.40frame/s]

   🔥 1500:   6%|▌         | 27/473 [00:00<00:05, 78.49frame/s]

   🔥 1500:   7%|▋         | 35/473 [00:00<00:05, 77.69frame/s]

   🔥 1500:   9%|▉         | 43/473 [00:00<00:05, 78.39frame/s]

   🔥 1500:  11%|█         | 52/473 [00:00<00:05, 79.10frame/s]

   🔥 1500:  13%|█▎        | 60/473 [00:00<00:05, 79.37frame/s]

   🔥 1500:  14%|█▍        | 68/473 [00:00<00:05, 79.47frame/s]

   🔥 1500:  16%|█▌        | 76/473 [00:00<00:04, 79.52frame/s]

   🔥 1500:  18%|█▊        | 84/473 [00:01<00:04, 79.60frame/s]

   🔥 1500:  19%|█▉        | 92/473 [00:01<00:04, 79.27frame/s]

   🔥 1500:  21%|██        | 100/473 [00:01<00:04, 78.91frame/s]

   🔥 1500:  23%|██▎       | 108/473 [00:01<00:04, 78.78frame/s]

   🔥 1500:  25%|██▍       | 116/473 [00:01<00:04, 78.59frame/s]

   🔥 1500:  26%|██▌       | 124/473 [00:01<00:04, 78.87frame/s]

   🔥 1500:  28%|██▊       | 132/473 [00:01<00:04, 78.74frame/s]

   🔥 1500:  30%|██▉       | 140/473 [00:01<00:04, 78.15frame/s]

   🔥 1500:  31%|███▏      | 148/473 [00:01<00:04, 77.40frame/s]

   🔥 1500:  33%|███▎      | 156/473 [00:01<00:04, 76.89frame/s]

   🔥 1500:  35%|███▍      | 164/473 [00:02<00:04, 76.85frame/s]

   🔥 1500:  36%|███▋      | 172/473 [00:02<00:03, 76.78frame/s]

   🔥 1500:  38%|███▊      | 180/473 [00:02<00:03, 76.48frame/s]

   🔥 1500:  40%|███▉      | 188/473 [00:02<00:03, 76.05frame/s]

   🔥 1500:  41%|████▏     | 196/473 [00:02<00:03, 76.12frame/s]

   🔥 1500:  43%|████▎     | 204/473 [00:02<00:03, 76.22frame/s]

   🔥 1500:  45%|████▍     | 212/473 [00:02<00:03, 76.64frame/s]

   🔥 1500:  47%|████▋     | 220/473 [00:02<00:03, 77.56frame/s]

   🔥 1500:  48%|████▊     | 228/473 [00:02<00:03, 78.17frame/s]

   🔥 1500:  50%|████▉     | 236/473 [00:03<00:03, 78.49frame/s]

   🔥 1500:  52%|█████▏    | 244/473 [00:03<00:02, 78.81frame/s]

   🔥 1500:  53%|█████▎    | 253/473 [00:03<00:02, 80.10frame/s]

   🔥 1500:  55%|█████▌    | 262/473 [00:03<00:02, 82.04frame/s]

   🔥 1500:  57%|█████▋    | 271/473 [00:03<00:02, 82.40frame/s]

   🔥 1500:  59%|█████▉    | 280/473 [00:03<00:02, 81.93frame/s]

   🔥 1500:  61%|██████    | 289/473 [00:03<00:02, 80.77frame/s]

   🔥 1500:  63%|██████▎   | 298/473 [00:03<00:02, 81.19frame/s]

   🔥 1500:  65%|██████▍   | 307/473 [00:03<00:01, 83.24frame/s]

   🔥 1500:  67%|██████▋   | 316/473 [00:03<00:01, 85.03frame/s]

   🔥 1500:  69%|██████▉   | 326/473 [00:04<00:01, 87.03frame/s]

   🔥 1500:  71%|███████   | 336/473 [00:04<00:01, 87.98frame/s]

   🔥 1500:  73%|███████▎  | 345/473 [00:04<00:01, 88.16frame/s]

   🔥 1500:  75%|███████▍  | 354/473 [00:04<00:01, 87.81frame/s]

   🔥 1500:  77%|███████▋  | 363/473 [00:04<00:01, 88.14frame/s]

   🔥 1500:  79%|███████▊  | 372/473 [00:04<00:01, 88.17frame/s]

   🔥 1500:  81%|████████  | 381/473 [00:04<00:01, 86.12frame/s]

   🔥 1500:  82%|████████▏ | 390/473 [00:04<00:00, 83.97frame/s]

   🔥 1500:  84%|████████▍ | 399/473 [00:04<00:00, 84.66frame/s]

   🔥 1500:  86%|████████▋ | 408/473 [00:05<00:00, 85.84frame/s]

   🔥 1500:  88%|████████▊ | 417/473 [00:05<00:00, 85.08frame/s]

   🔥 1500:  90%|█████████ | 426/473 [00:05<00:00, 84.06frame/s]

   🔥 1500:  92%|█████████▏| 435/473 [00:05<00:00, 82.89frame/s]

   🔥 1500:  94%|█████████▍| 444/473 [00:05<00:00, 82.64frame/s]

   🔥 1500:  96%|█████████▌| 453/473 [00:05<00:00, 81.43frame/s]

   🔥 1500:  98%|█████████▊| 462/473 [00:05<00:00, 79.49frame/s]

   🔥 1500:  99%|█████████▉| 470/473 [00:05<00:00, 78.49frame/s]

                                                                [✅] 1500: /working/MDCP3D-SL-013_W046(6)/calibration/debug/5_heatmap/1500_heatmap.png
[✅] 1500 (fitted): /working/MDCP3D-SL-013_W046(6)/calibration/debug/5_heatmap/1500_heatmap_fitted.png

📁 Rigs (heatmap): 100%|██████████| 4/4 [00:21<00:00,  5.72s/rig]
📁 Rigs (heatmap): 100%|██████████| 4/4 [00:21<00:00,  5.43s/rig]
[✅] all_rigs_average.png
[✅] all_rigs_best.png
[✅] all_rigs_average_fitted.png
[✅] all_rigs_best_fitted.png
[✅] Heatmaps saved to: /working/MDCP3D-SL-013_W046(6)/calibration/debug/5_heatmap
[🏁] Finished processing MDCP3D-SL-013_W046(6)


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