🟢 Starting Calibration Pipeline

=== Processing MDC102_W039_2025-08-29 ===

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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 2 las0.zip files to process

Processing Rigs:   0%|          | 0/2 [00:00<?, ?it/s][INFO] Filtered 945 stationary frames, 208 remain


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→ 1000 Phase 2: corners:  89%|████████▉ | 186/208 [02:30<00:17,  1.23it/s]

→ 1000 Phase 2: corners:  90%|████████▉ | 187/208 [02:30<00:16,  1.25it/s]

→ 1000 Phase 2: corners:  90%|█████████ | 188/208 [02:31<00:16,  1.22it/s]

→ 1000 Phase 2: corners:  91%|█████████ | 189/208 [02:32<00:15,  1.25it/s]

→ 1000 Phase 2: corners:  91%|█████████▏| 190/208 [02:33<00:14,  1.24it/s]

→ 1000 Phase 2: corners:  92%|█████████▏| 191/208 [02:34<00:13,  1.26it/s]

→ 1000 Phase 2: corners:  92%|█████████▏| 192/208 [02:34<00:12,  1.27it/s]

→ 1000 Phase 2: corners:  93%|█████████▎| 193/208 [02:35<00:11,  1.27it/s]

→ 1000 Phase 2: corners:  93%|█████████▎| 194/208 [02:36<00:11,  1.26it/s]

→ 1000 Phase 2: corners:  94%|█████████▍| 195/208 [02:37<00:10,  1.26it/s]

→ 1000 Phase 2: corners:  94%|█████████▍| 196/208 [02:38<00:09,  1.26it/s]

→ 1000 Phase 2: corners:  95%|█████████▍| 197/208 [02:38<00:08,  1.25it/s]

→ 1000 Phase 2: corners:  95%|█████████▌| 198/208 [02:39<00:07,  1.26it/s]

→ 1000 Phase 2: corners:  96%|█████████▌| 199/208 [02:40<00:07,  1.27it/s]

→ 1000 Phase 2: corners:  96%|█████████▌| 200/208 [02:41<00:06,  1.26it/s]

→ 1000 Phase 2: corners:  97%|█████████▋| 201/208 [02:42<00:05,  1.26it/s]

→ 1000 Phase 2: corners:  97%|█████████▋| 202/208 [02:42<00:04,  1.26it/s]

→ 1000 Phase 2: corners:  98%|█████████▊| 203/208 [02:43<00:03,  1.28it/s]

→ 1000 Phase 2: corners:  98%|█████████▊| 204/208 [02:44<00:03,  1.28it/s]

→ 1000 Phase 2: corners:  99%|█████████▊| 205/208 [02:45<00:02,  1.27it/s]

→ 1000 Phase 2: corners:  99%|█████████▉| 206/208 [02:46<00:01,  1.28it/s]

→ 1000 Phase 2: corners: 100%|█████████▉| 207/208 [02:46<00:00,  1.27it/s]

→ 1000 Phase 2: corners: 100%|██████████| 208/208 [02:47<00:00,  1.28it/s]

                                                                          [PASS2] Frame 0000444: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000445: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000446: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000447: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001060: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001061: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0001062: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0001063: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000446: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001062: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Summary: 4 frames fixed, 5 untrusted, 208 total


→ 1000 Phase 3: finalize:   0%|          | 0/208 [00:00<?, ?it/s]

→ 1000 Phase 3: finalize:   1%|          | 2/208 [00:00<00:17, 12.01it/s]

→ 1000 Phase 3: finalize:   2%|▏         | 4/208 [00:00<00:16, 12.49it/s]

→ 1000 Phase 3: finalize:   3%|▎         | 6/208 [00:00<00:15, 12.67it/s]

→ 1000 Phase 3: finalize:   4%|▍         | 8/208 [00:00<00:15, 12.73it/s]

→ 1000 Phase 3: finalize:   5%|▍         | 10/208 [00:00<00:15, 12.81it/s]

→ 1000 Phase 3: finalize:   6%|▌         | 12/208 [00:00<00:15, 12.84it/s]

→ 1000 Phase 3: finalize:   7%|▋         | 14/208 [00:01<00:15, 12.88it/s]

→ 1000 Phase 3: finalize:   8%|▊         | 16/208 [00:01<00:14, 12.89it/s]

→ 1000 Phase 3: finalize:   9%|▊         | 18/208 [00:01<00:14, 13.09it/s]

→ 1000 Phase 3: finalize:  10%|▉         | 20/208 [00:01<00:14, 13.20it/s]

→ 1000 Phase 3: finalize:  11%|█         | 22/208 [00:01<00:14, 13.28it/s]

→ 1000 Phase 3: finalize:  12%|█▏        | 24/208 [00:01<00:13, 13.32it/s]

→ 1000 Phase 3: finalize:  12%|█▎        | 26/208 [00:01<00:13, 13.36it/s]

→ 1000 Phase 3: finalize:  13%|█▎        | 28/208 [00:02<00:12, 14.69it/s]

→ 1000 Phase 3: finalize:  14%|█▍        | 30/208 [00:02<00:12, 14.27it/s]

→ 1000 Phase 3: finalize:  15%|█▌        | 32/208 [00:02<00:12, 14.02it/s]

→ 1000 Phase 3: finalize:  16%|█▋        | 34/208 [00:02<00:12, 13.80it/s]

→ 1000 Phase 3: finalize:  17%|█▋        | 36/208 [00:02<00:12, 13.66it/s]

→ 1000 Phase 3: finalize:  18%|█▊        | 38/208 [00:02<00:12, 13.57it/s]

→ 1000 Phase 3: finalize:  19%|█▉        | 40/208 [00:02<00:12, 13.50it/s]

→ 1000 Phase 3: finalize:  20%|██        | 42/208 [00:03<00:12, 13.42it/s]

→ 1000 Phase 3: finalize:  21%|██        | 44/208 [00:03<00:12, 13.40it/s]

→ 1000 Phase 3: finalize:  22%|██▏       | 46/208 [00:03<00:12, 13.35it/s]

→ 1000 Phase 3: finalize:  23%|██▎       | 48/208 [00:03<00:12, 13.32it/s]

→ 1000 Phase 3: finalize:  24%|██▍       | 50/208 [00:03<00:11, 13.28it/s]

→ 1000 Phase 3: finalize:  25%|██▌       | 52/208 [00:03<00:11, 13.27it/s]

→ 1000 Phase 3: finalize:  26%|██▌       | 54/208 [00:04<00:11, 13.25it/s]

→ 1000 Phase 3: finalize:  27%|██▋       | 56/208 [00:04<00:11, 13.23it/s]

→ 1000 Phase 3: finalize:  28%|██▊       | 58/208 [00:04<00:11, 13.25it/s]

→ 1000 Phase 3: finalize:  29%|██▉       | 60/208 [00:04<00:11, 13.23it/s]

→ 1000 Phase 3: finalize:  30%|██▉       | 62/208 [00:04<00:11, 13.25it/s]

→ 1000 Phase 3: finalize:  31%|███       | 64/208 [00:04<00:10, 13.23it/s]

→ 1000 Phase 3: finalize:  32%|███▏      | 66/208 [00:04<00:10, 13.21it/s]

→ 1000 Phase 3: finalize:  33%|███▎      | 68/208 [00:05<00:10, 13.18it/s]

→ 1000 Phase 3: finalize:  34%|███▎      | 70/208 [00:05<00:10, 13.17it/s]

→ 1000 Phase 3: finalize:  35%|███▍      | 72/208 [00:05<00:10, 13.07it/s]

→ 1000 Phase 3: finalize:  36%|███▌      | 74/208 [00:05<00:10, 13.05it/s]

→ 1000 Phase 3: finalize:  37%|███▋      | 76/208 [00:05<00:10, 13.04it/s]

→ 1000 Phase 3: finalize:  38%|███▊      | 78/208 [00:05<00:10, 12.98it/s]

→ 1000 Phase 3: finalize:  38%|███▊      | 80/208 [00:06<00:09, 12.93it/s]

→ 1000 Phase 3: finalize:  39%|███▉      | 82/208 [00:06<00:09, 12.85it/s]

→ 1000 Phase 3: finalize:  40%|████      | 84/208 [00:06<00:09, 12.82it/s]

→ 1000 Phase 3: finalize:  41%|████▏     | 86/208 [00:06<00:09, 12.78it/s]

→ 1000 Phase 3: finalize:  42%|████▏     | 88/208 [00:06<00:09, 12.78it/s]

→ 1000 Phase 3: finalize:  43%|████▎     | 90/208 [00:06<00:09, 12.78it/s]

→ 1000 Phase 3: finalize:  44%|████▍     | 92/208 [00:06<00:09, 12.80it/s]

→ 1000 Phase 3: finalize:  45%|████▌     | 94/208 [00:07<00:08, 12.84it/s]

→ 1000 Phase 3: finalize:  46%|████▌     | 96/208 [00:07<00:08, 12.89it/s]

→ 1000 Phase 3: finalize:  47%|████▋     | 98/208 [00:07<00:08, 12.91it/s]

→ 1000 Phase 3: finalize:  48%|████▊     | 100/208 [00:07<00:08, 12.95it/s]

→ 1000 Phase 3: finalize:  49%|████▉     | 102/208 [00:07<00:08, 13.01it/s]

→ 1000 Phase 3: finalize:  50%|█████     | 104/208 [00:07<00:07, 13.02it/s]

→ 1000 Phase 3: finalize:  51%|█████     | 106/208 [00:08<00:07, 13.02it/s]

→ 1000 Phase 3: finalize:  52%|█████▏    | 108/208 [00:08<00:07, 13.08it/s]

→ 1000 Phase 3: finalize:  53%|█████▎    | 110/208 [00:08<00:07, 13.09it/s]

→ 1000 Phase 3: finalize:  54%|█████▍    | 112/208 [00:08<00:07, 13.12it/s]

→ 1000 Phase 3: finalize:  55%|█████▍    | 114/208 [00:08<00:07, 13.16it/s]

→ 1000 Phase 3: finalize:  56%|█████▌    | 116/208 [00:08<00:06, 13.15it/s]

→ 1000 Phase 3: finalize:  57%|█████▋    | 118/208 [00:08<00:06, 13.17it/s]

→ 1000 Phase 3: finalize:  58%|█████▊    | 120/208 [00:09<00:06, 13.23it/s]

→ 1000 Phase 3: finalize:  59%|█████▊    | 122/208 [00:09<00:06, 13.28it/s]

→ 1000 Phase 3: finalize:  60%|█████▉    | 124/208 [00:09<00:06, 13.32it/s]

→ 1000 Phase 3: finalize:  61%|██████    | 126/208 [00:09<00:06, 13.36it/s]

→ 1000 Phase 3: finalize:  62%|██████▏   | 128/208 [00:09<00:05, 13.40it/s]

→ 1000 Phase 3: finalize:  62%|██████▎   | 130/208 [00:09<00:05, 13.40it/s]

→ 1000 Phase 3: finalize:  63%|██████▎   | 132/208 [00:10<00:05, 13.41it/s]

→ 1000 Phase 3: finalize:  64%|██████▍   | 134/208 [00:10<00:05, 13.43it/s]

→ 1000 Phase 3: finalize:  65%|██████▌   | 136/208 [00:10<00:05, 13.47it/s]

→ 1000 Phase 3: finalize:  66%|██████▋   | 138/208 [00:10<00:05, 13.47it/s]

→ 1000 Phase 3: finalize:  67%|██████▋   | 140/208 [00:10<00:05, 13.52it/s]

→ 1000 Phase 3: finalize:  68%|██████▊   | 142/208 [00:10<00:04, 13.59it/s]

→ 1000 Phase 3: finalize:  69%|██████▉   | 144/208 [00:10<00:04, 13.62it/s]

→ 1000 Phase 3: finalize:  70%|███████   | 146/208 [00:11<00:04, 13.68it/s]

→ 1000 Phase 3: finalize:  71%|███████   | 148/208 [00:11<00:04, 13.73it/s]

→ 1000 Phase 3: finalize:  72%|███████▏  | 150/208 [00:11<00:04, 13.76it/s]

→ 1000 Phase 3: finalize:  73%|███████▎  | 152/208 [00:11<00:04, 13.80it/s]

→ 1000 Phase 3: finalize:  74%|███████▍  | 154/208 [00:11<00:03, 13.81it/s]

→ 1000 Phase 3: finalize:  75%|███████▌  | 156/208 [00:11<00:03, 13.82it/s]

→ 1000 Phase 3: finalize:  76%|███████▌  | 158/208 [00:11<00:03, 13.83it/s]

→ 1000 Phase 3: finalize:  77%|███████▋  | 160/208 [00:12<00:03, 13.85it/s]

→ 1000 Phase 3: finalize:  78%|███████▊  | 162/208 [00:12<00:03, 13.80it/s]

→ 1000 Phase 3: finalize:  79%|███████▉  | 164/208 [00:12<00:03, 13.80it/s]

→ 1000 Phase 3: finalize:  80%|███████▉  | 166/208 [00:12<00:03, 13.79it/s]

→ 1000 Phase 3: finalize:  81%|████████  | 168/208 [00:12<00:02, 13.76it/s]

→ 1000 Phase 3: finalize:  82%|████████▏ | 170/208 [00:12<00:02, 13.74it/s]

→ 1000 Phase 3: finalize:  83%|████████▎ | 172/208 [00:12<00:02, 13.72it/s]

→ 1000 Phase 3: finalize:  84%|████████▎ | 174/208 [00:13<00:02, 13.66it/s]

→ 1000 Phase 3: finalize:  85%|████████▍ | 176/208 [00:13<00:02, 13.63it/s]

→ 1000 Phase 3: finalize:  86%|████████▌ | 178/208 [00:13<00:02, 13.61it/s]

→ 1000 Phase 3: finalize:  87%|████████▋ | 180/208 [00:13<00:02, 13.56it/s]

→ 1000 Phase 3: finalize:  88%|████████▊ | 182/208 [00:13<00:01, 13.54it/s]

→ 1000 Phase 3: finalize:  88%|████████▊ | 184/208 [00:13<00:01, 13.53it/s]

→ 1000 Phase 3: finalize:  89%|████████▉ | 186/208 [00:13<00:01, 13.53it/s]

→ 1000 Phase 3: finalize:  90%|█████████ | 188/208 [00:14<00:01, 13.52it/s]

→ 1000 Phase 3: finalize:  91%|█████████▏| 190/208 [00:14<00:01, 13.52it/s]

→ 1000 Phase 3: finalize:  92%|█████████▏| 192/208 [00:14<00:01, 13.51it/s]

→ 1000 Phase 3: finalize:  93%|█████████▎| 194/208 [00:14<00:01, 13.46it/s]

→ 1000 Phase 3: finalize:  94%|█████████▍| 196/208 [00:14<00:00, 13.44it/s]

→ 1000 Phase 3: finalize:  95%|█████████▌| 198/208 [00:14<00:00, 13.42it/s]

→ 1000 Phase 3: finalize:  96%|█████████▌| 200/208 [00:15<00:00, 13.42it/s]

→ 1000 Phase 3: finalize:  97%|█████████▋| 202/208 [00:15<00:00, 13.39it/s]

→ 1000 Phase 3: finalize:  98%|█████████▊| 204/208 [00:15<00:00, 13.39it/s]

→ 1000 Phase 3: finalize:  99%|█████████▉| 206/208 [00:15<00:00, 13.39it/s]

→ 1000 Phase 3: finalize: 100%|██████████| 208/208 [00:15<00:00, 13.41it/s]

                                                                           
Processing Rigs:  50%|█████     | 1/2 [03:26<03:26, 206.47s/it][INFO] Filtered 980 stationary frames, 204 remain


→ 500 (204 images) Phase 1:   0%|          | 0/204 [00:00<?, ?it/s]

→ 500 (204 images) Phase 1:   0%|          | 1/204 [00:03<10:37,  3.14s/it]

→ 500 (204 images) Phase 1:  16%|█▌        | 33/204 [00:05<00:25,  6.74it/s]

→ 500 (204 images) Phase 1:  27%|██▋       | 56/204 [00:05<00:11, 13.13it/s]

→ 500 (204 images) Phase 1:  33%|███▎      | 67/204 [00:08<00:15,  8.58it/s]

→ 500 (204 images) Phase 1:  43%|████▎     | 87/204 [00:08<00:08, 13.86it/s]

→ 500 (204 images) Phase 1:  49%|████▊     | 99/204 [00:11<00:11,  9.19it/s]

→ 500 (204 images) Phase 1:  59%|█████▉    | 121/204 [00:11<00:05, 14.87it/s]

→ 500 (204 images) Phase 1:  65%|██████▌   | 133/204 [00:13<00:07,  9.80it/s]

→ 500 (204 images) Phase 1:  76%|███████▌  | 155/204 [00:13<00:03, 15.40it/s]

→ 500 (204 images) Phase 1:  82%|████████▏ | 167/204 [00:16<00:03, 10.08it/s]

→ 500 (204 images) Phase 1:  92%|█████████▏| 188/204 [00:16<00:01, 15.45it/s]

→ 500 (204 images) Phase 1:  98%|█████████▊| 200/204 [00:18<00:00, 12.99it/s]

                                                                             

→ 500 Phase 2: corners:   0%|          | 0/204 [00:00<?, ?it/s]

→ 500 Phase 2: corners:   0%|          | 1/204 [00:00<03:01,  1.12it/s]

→ 500 Phase 2: corners:   1%|          | 2/204 [00:01<03:08,  1.07it/s]

→ 500 Phase 2: corners:   1%|▏         | 3/204 [00:02<03:06,  1.08it/s]

→ 500 Phase 2: corners:   2%|▏         | 4/204 [00:03<03:04,  1.08it/s]

→ 500 Phase 2: corners:   2%|▏         | 5/204 [00:04<03:03,  1.09it/s]

→ 500 Phase 2: corners:   3%|▎         | 6/204 [00:05<03:01,  1.09it/s]

→ 500 Phase 2: corners:   3%|▎         | 7/204 [00:06<02:59,  1.10it/s]

→ 500 Phase 2: corners:   4%|▍         | 8/204 [00:07<02:57,  1.10it/s]

→ 500 Phase 2: corners:   4%|▍         | 9/204 [00:08<02:53,  1.13it/s]

→ 500 Phase 2: corners:   5%|▍         | 10/204 [00:09<02:57,  1.09it/s]

→ 500 Phase 2: corners:   5%|▌         | 11/204 [00:10<02:54,  1.11it/s]

→ 500 Phase 2: corners:   6%|▌         | 12/204 [00:10<02:54,  1.10it/s]

→ 500 Phase 2: corners:   6%|▋         | 13/204 [00:11<02:51,  1.11it/s]

→ 500 Phase 2: corners:   7%|▋         | 14/204 [00:12<02:51,  1.11it/s]

→ 500 Phase 2: corners:   7%|▋         | 15/204 [00:13<02:47,  1.13it/s]

→ 500 Phase 2: corners:   8%|▊         | 16/204 [00:14<02:45,  1.14it/s]

→ 500 Phase 2: corners:   8%|▊         | 17/204 [00:15<02:44,  1.14it/s]

→ 500 Phase 2: corners:   9%|▉         | 18/204 [00:16<02:46,  1.11it/s]

→ 500 Phase 2: corners:   9%|▉         | 19/204 [00:17<02:43,  1.13it/s]

→ 500 Phase 2: corners:  10%|▉         | 20/204 [00:17<02:40,  1.15it/s]

→ 500 Phase 2: corners:  10%|█         | 21/204 [00:18<02:43,  1.12it/s]

→ 500 Phase 2: corners:  11%|█         | 22/204 [00:19<02:42,  1.12it/s]

→ 500 Phase 2: corners:  11%|█▏        | 23/204 [00:20<02:40,  1.13it/s]

→ 500 Phase 2: corners:  12%|█▏        | 24/204 [00:21<02:40,  1.12it/s]

→ 500 Phase 2: corners:  12%|█▏        | 25/204 [00:22<02:37,  1.14it/s]

→ 500 Phase 2: corners:  13%|█▎        | 26/204 [00:23<02:40,  1.11it/s]

→ 500 Phase 2: corners:  13%|█▎        | 27/204 [00:24<02:40,  1.10it/s]

→ 500 Phase 2: corners:  14%|█▎        | 28/204 [00:25<02:36,  1.12it/s]

→ 500 Phase 2: corners:  14%|█▍        | 29/204 [00:26<02:35,  1.13it/s]

→ 500 Phase 2: corners:  15%|█▍        | 30/204 [00:26<02:37,  1.11it/s]

→ 500 Phase 2: corners:  15%|█▌        | 31/204 [00:27<02:34,  1.12it/s]

→ 500 Phase 2: corners:  16%|█▌        | 32/204 [00:28<02:35,  1.11it/s]

→ 500 Phase 2: corners:  16%|█▌        | 33/204 [00:29<02:34,  1.11it/s]

→ 500 Phase 2: corners:  17%|█▋        | 34/204 [00:30<02:32,  1.11it/s]

→ 500 Phase 2: corners:  17%|█▋        | 35/204 [00:31<02:33,  1.10it/s]

→ 500 Phase 2: corners:  18%|█▊        | 36/204 [00:32<02:32,  1.10it/s]

→ 500 Phase 2: corners:  18%|█▊        | 37/204 [00:33<02:31,  1.10it/s]

→ 500 Phase 2: corners:  19%|█▊        | 38/204 [00:34<02:31,  1.10it/s]

→ 500 Phase 2: corners:  19%|█▉        | 39/204 [00:35<02:29,  1.10it/s]

→ 500 Phase 2: corners:  20%|█▉        | 40/204 [00:36<02:29,  1.10it/s]

→ 500 Phase 2: corners:  20%|██        | 41/204 [00:36<02:28,  1.10it/s]

→ 500 Phase 2: corners:  21%|██        | 42/204 [00:37<02:27,  1.10it/s]

→ 500 Phase 2: corners:  21%|██        | 43/204 [00:38<02:23,  1.12it/s]

→ 500 Phase 2: corners:  22%|██▏       | 44/204 [00:39<02:24,  1.11it/s]

→ 500 Phase 2: corners:  22%|██▏       | 45/204 [00:40<02:19,  1.14it/s]

→ 500 Phase 2: corners:  23%|██▎       | 46/204 [00:41<02:19,  1.13it/s]

→ 500 Phase 2: corners:  23%|██▎       | 47/204 [00:42<02:16,  1.15it/s]

→ 500 Phase 2: corners:  24%|██▎       | 48/204 [00:43<02:15,  1.15it/s]

→ 500 Phase 2: corners:  24%|██▍       | 49/204 [00:43<02:15,  1.14it/s]

→ 500 Phase 2: corners:  25%|██▍       | 50/204 [00:44<02:17,  1.12it/s]

→ 500 Phase 2: corners:  25%|██▌       | 51/204 [00:45<02:16,  1.12it/s]

→ 500 Phase 2: corners:  25%|██▌       | 52/204 [00:46<02:14,  1.13it/s]

→ 500 Phase 2: corners:  26%|██▌       | 53/204 [00:47<02:11,  1.15it/s]

→ 500 Phase 2: corners:  26%|██▋       | 54/204 [00:48<02:11,  1.14it/s]

→ 500 Phase 2: corners:  27%|██▋       | 55/204 [00:49<02:09,  1.15it/s]

→ 500 Phase 2: corners:  27%|██▋       | 56/204 [00:50<02:08,  1.15it/s]

→ 500 Phase 2: corners:  28%|██▊       | 57/204 [00:50<02:05,  1.17it/s]

→ 500 Phase 2: corners:  28%|██▊       | 58/204 [00:51<02:03,  1.18it/s]

→ 500 Phase 2: corners:  29%|██▉       | 59/204 [00:52<02:01,  1.19it/s]

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→ 500 Phase 2: corners:  30%|██▉       | 61/204 [00:54<01:58,  1.21it/s]

→ 500 Phase 2: corners:  30%|███       | 62/204 [00:55<01:59,  1.19it/s]

→ 500 Phase 2: corners:  31%|███       | 63/204 [00:55<01:57,  1.20it/s]

→ 500 Phase 2: corners:  31%|███▏      | 64/204 [00:56<01:58,  1.18it/s]

→ 500 Phase 2: corners:  32%|███▏      | 65/204 [00:57<01:57,  1.19it/s]

→ 500 Phase 2: corners:  32%|███▏      | 66/204 [00:58<01:57,  1.18it/s]

→ 500 Phase 2: corners:  33%|███▎      | 67/204 [00:59<01:57,  1.17it/s]

→ 500 Phase 2: corners:  33%|███▎      | 68/204 [01:00<01:57,  1.16it/s]

→ 500 Phase 2: corners:  34%|███▍      | 69/204 [01:01<01:56,  1.16it/s]

→ 500 Phase 2: corners:  34%|███▍      | 70/204 [01:01<01:57,  1.14it/s]

→ 500 Phase 2: corners:  35%|███▍      | 71/204 [01:02<01:57,  1.13it/s]

→ 500 Phase 2: corners:  35%|███▌      | 72/204 [01:03<01:57,  1.13it/s]

→ 500 Phase 2: corners:  36%|███▌      | 73/204 [01:04<01:56,  1.12it/s]

→ 500 Phase 2: corners:  36%|███▋      | 74/204 [01:05<01:57,  1.11it/s]

→ 500 Phase 2: corners:  37%|███▋      | 75/204 [01:06<01:54,  1.12it/s]

→ 500 Phase 2: corners:  37%|███▋      | 76/204 [01:07<01:54,  1.11it/s]

→ 500 Phase 2: corners:  38%|███▊      | 77/204 [01:08<01:52,  1.13it/s]

→ 500 Phase 2: corners:  38%|███▊      | 78/204 [01:09<01:53,  1.11it/s]

→ 500 Phase 2: corners:  39%|███▊      | 79/204 [01:10<01:52,  1.11it/s]

→ 500 Phase 2: corners:  39%|███▉      | 80/204 [01:10<01:51,  1.11it/s]

→ 500 Phase 2: corners:  40%|███▉      | 81/204 [01:11<01:51,  1.11it/s]

→ 500 Phase 2: corners:  40%|████      | 82/204 [01:12<01:50,  1.10it/s]

→ 500 Phase 2: corners:  41%|████      | 83/204 [01:13<01:50,  1.09it/s]

→ 500 Phase 2: corners:  41%|████      | 84/204 [01:14<01:49,  1.09it/s]

→ 500 Phase 2: corners:  42%|████▏     | 85/204 [01:15<01:48,  1.10it/s]

→ 500 Phase 2: corners:  42%|████▏     | 86/204 [01:16<01:48,  1.09it/s]

→ 500 Phase 2: corners:  43%|████▎     | 87/204 [01:17<01:48,  1.08it/s]

→ 500 Phase 2: corners:  43%|████▎     | 88/204 [01:18<01:47,  1.08it/s]

→ 500 Phase 2: corners:  44%|████▎     | 89/204 [01:19<01:47,  1.07it/s]

→ 500 Phase 2: corners:  44%|████▍     | 90/204 [01:20<01:46,  1.07it/s]

→ 500 Phase 2: corners:  45%|████▍     | 91/204 [01:21<01:43,  1.09it/s]

→ 500 Phase 2: corners:  45%|████▌     | 92/204 [01:22<01:43,  1.08it/s]

→ 500 Phase 2: corners:  46%|████▌     | 93/204 [01:22<01:41,  1.10it/s]

→ 500 Phase 2: corners:  46%|████▌     | 94/204 [01:23<01:39,  1.11it/s]

→ 500 Phase 2: corners:  47%|████▋     | 95/204 [01:24<01:38,  1.11it/s]

→ 500 Phase 2: corners:  47%|████▋     | 96/204 [01:25<01:37,  1.10it/s]

→ 500 Phase 2: corners:  48%|████▊     | 97/204 [01:26<01:36,  1.11it/s]

→ 500 Phase 2: corners:  48%|████▊     | 98/204 [01:27<01:34,  1.12it/s]

→ 500 Phase 2: corners:  49%|████▊     | 99/204 [01:28<01:33,  1.12it/s]

→ 500 Phase 2: corners:  49%|████▉     | 100/204 [01:29<01:31,  1.13it/s]

→ 500 Phase 2: corners:  50%|████▉     | 101/204 [01:30<01:31,  1.12it/s]

→ 500 Phase 2: corners:  50%|█████     | 102/204 [01:30<01:29,  1.13it/s]

→ 500 Phase 2: corners:  50%|█████     | 103/204 [01:31<01:29,  1.13it/s]

→ 500 Phase 2: corners:  51%|█████     | 104/204 [01:32<01:28,  1.13it/s]

→ 500 Phase 2: corners:  51%|█████▏    | 105/204 [01:33<01:28,  1.12it/s]

→ 500 Phase 2: corners:  52%|█████▏    | 106/204 [01:34<01:26,  1.13it/s]

→ 500 Phase 2: corners:  52%|█████▏    | 107/204 [01:35<01:27,  1.10it/s]

→ 500 Phase 2: corners:  53%|█████▎    | 108/204 [01:36<01:26,  1.12it/s]

→ 500 Phase 2: corners:  53%|█████▎    | 109/204 [01:37<01:27,  1.09it/s]

→ 500 Phase 2: corners:  54%|█████▍    | 110/204 [01:38<01:26,  1.08it/s]

→ 500 Phase 2: corners:  54%|█████▍    | 111/204 [01:39<01:25,  1.09it/s]

→ 500 Phase 2: corners:  55%|█████▍    | 112/204 [01:39<01:23,  1.10it/s]

→ 500 Phase 2: corners:  55%|█████▌    | 113/204 [01:40<01:23,  1.09it/s]

→ 500 Phase 2: corners:  56%|█████▌    | 114/204 [01:41<01:23,  1.08it/s]

→ 500 Phase 2: corners:  56%|█████▋    | 115/204 [01:42<01:23,  1.07it/s]

→ 500 Phase 2: corners:  57%|█████▋    | 116/204 [01:43<01:21,  1.08it/s]

→ 500 Phase 2: corners:  57%|█████▋    | 117/204 [01:44<01:19,  1.09it/s]

→ 500 Phase 2: corners:  58%|█████▊    | 118/204 [01:45<01:17,  1.11it/s]

→ 500 Phase 2: corners:  58%|█████▊    | 119/204 [01:46<01:17,  1.10it/s]

→ 500 Phase 2: corners:  59%|█████▉    | 120/204 [01:47<01:14,  1.12it/s]

→ 500 Phase 2: corners:  59%|█████▉    | 121/204 [01:48<01:13,  1.13it/s]

→ 500 Phase 2: corners:  60%|█████▉    | 122/204 [01:48<01:11,  1.15it/s]

→ 500 Phase 2: corners:  60%|██████    | 123/204 [01:49<01:10,  1.16it/s]

→ 500 Phase 2: corners:  61%|██████    | 124/204 [01:50<01:08,  1.17it/s]

→ 500 Phase 2: corners:  61%|██████▏   | 125/204 [01:51<01:07,  1.17it/s]

→ 500 Phase 2: corners:  62%|██████▏   | 126/204 [01:52<01:06,  1.17it/s]

→ 500 Phase 2: corners:  62%|██████▏   | 127/204 [01:53<01:06,  1.16it/s]

→ 500 Phase 2: corners:  63%|██████▎   | 128/204 [01:54<01:06,  1.15it/s]

→ 500 Phase 2: corners:  63%|██████▎   | 129/204 [01:55<01:05,  1.14it/s]

→ 500 Phase 2: corners:  64%|██████▎   | 130/204 [01:55<01:04,  1.15it/s]

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→ 500 Phase 2: corners:  65%|██████▌   | 133/204 [01:58<01:03,  1.12it/s]

→ 500 Phase 2: corners:  66%|██████▌   | 134/204 [01:59<01:02,  1.12it/s]

→ 500 Phase 2: corners:  66%|██████▌   | 135/204 [02:00<01:01,  1.11it/s]

→ 500 Phase 2: corners:  67%|██████▋   | 136/204 [02:01<01:00,  1.12it/s]

→ 500 Phase 2: corners:  67%|██████▋   | 137/204 [02:02<01:00,  1.10it/s]

→ 500 Phase 2: corners:  68%|██████▊   | 138/204 [02:03<01:00,  1.09it/s]

→ 500 Phase 2: corners:  68%|██████▊   | 139/204 [02:04<01:00,  1.07it/s]

→ 500 Phase 2: corners:  69%|██████▊   | 140/204 [02:05<00:59,  1.07it/s]

→ 500 Phase 2: corners:  69%|██████▉   | 141/204 [02:06<00:59,  1.06it/s]

→ 500 Phase 2: corners:  70%|██████▉   | 142/204 [02:06<00:58,  1.06it/s]

→ 500 Phase 2: corners:  70%|███████   | 143/204 [02:07<00:58,  1.04it/s]

→ 500 Phase 2: corners:  71%|███████   | 144/204 [02:08<00:57,  1.05it/s]

→ 500 Phase 2: corners:  71%|███████   | 145/204 [02:09<00:55,  1.06it/s]

→ 500 Phase 2: corners:  72%|███████▏  | 146/204 [02:10<00:54,  1.06it/s]

→ 500 Phase 2: corners:  72%|███████▏  | 147/204 [02:11<00:54,  1.05it/s]

→ 500 Phase 2: corners:  73%|███████▎  | 148/204 [02:12<00:52,  1.06it/s]

→ 500 Phase 2: corners:  73%|███████▎  | 149/204 [02:13<00:51,  1.06it/s]

→ 500 Phase 2: corners:  74%|███████▎  | 150/204 [02:14<00:50,  1.07it/s]

→ 500 Phase 2: corners:  74%|███████▍  | 151/204 [02:15<00:49,  1.08it/s]

→ 500 Phase 2: corners:  75%|███████▍  | 152/204 [02:16<00:48,  1.08it/s]

→ 500 Phase 2: corners:  75%|███████▌  | 153/204 [02:17<00:47,  1.07it/s]

→ 500 Phase 2: corners:  75%|███████▌  | 154/204 [02:18<00:46,  1.08it/s]

→ 500 Phase 2: corners:  76%|███████▌  | 155/204 [02:19<00:44,  1.09it/s]

→ 500 Phase 2: corners:  76%|███████▋  | 156/204 [02:20<00:43,  1.10it/s]

→ 500 Phase 2: corners:  77%|███████▋  | 157/204 [02:20<00:42,  1.11it/s]

→ 500 Phase 2: corners:  77%|███████▋  | 158/204 [02:21<00:41,  1.11it/s]

→ 500 Phase 2: corners:  78%|███████▊  | 159/204 [02:22<00:40,  1.11it/s]

→ 500 Phase 2: corners:  78%|███████▊  | 160/204 [02:23<00:39,  1.11it/s]

→ 500 Phase 2: corners:  79%|███████▉  | 161/204 [02:24<00:38,  1.10it/s]

→ 500 Phase 2: corners:  79%|███████▉  | 162/204 [02:25<00:38,  1.09it/s]

→ 500 Phase 2: corners:  80%|███████▉  | 163/204 [02:26<00:37,  1.09it/s]

→ 500 Phase 2: corners:  80%|████████  | 164/204 [02:27<00:36,  1.09it/s]

→ 500 Phase 2: corners:  81%|████████  | 165/204 [02:28<00:35,  1.09it/s]

→ 500 Phase 2: corners:  81%|████████▏ | 166/204 [02:29<00:34,  1.11it/s]

→ 500 Phase 2: corners:  82%|████████▏ | 167/204 [02:29<00:33,  1.11it/s]

→ 500 Phase 2: corners:  82%|████████▏ | 168/204 [02:30<00:33,  1.09it/s]

→ 500 Phase 2: corners:  83%|████████▎ | 169/204 [02:31<00:32,  1.08it/s]

→ 500 Phase 2: corners:  83%|████████▎ | 170/204 [02:32<00:31,  1.08it/s]

→ 500 Phase 2: corners:  84%|████████▍ | 171/204 [02:33<00:30,  1.08it/s]

→ 500 Phase 2: corners:  84%|████████▍ | 172/204 [02:34<00:29,  1.08it/s]

→ 500 Phase 2: corners:  85%|████████▍ | 173/204 [02:35<00:28,  1.08it/s]

→ 500 Phase 2: corners:  85%|████████▌ | 174/204 [02:36<00:27,  1.09it/s]

→ 500 Phase 2: corners:  86%|████████▌ | 175/204 [02:37<00:26,  1.08it/s]

→ 500 Phase 2: corners:  86%|████████▋ | 176/204 [02:38<00:26,  1.07it/s]

→ 500 Phase 2: corners:  87%|████████▋ | 177/204 [02:39<00:25,  1.07it/s]

→ 500 Phase 2: corners:  87%|████████▋ | 178/204 [02:40<00:24,  1.06it/s]

→ 500 Phase 2: corners:  88%|████████▊ | 179/204 [02:41<00:23,  1.07it/s]

→ 500 Phase 2: corners:  88%|████████▊ | 180/204 [02:42<00:22,  1.07it/s]

→ 500 Phase 2: corners:  89%|████████▊ | 181/204 [02:43<00:21,  1.09it/s]

→ 500 Phase 2: corners:  89%|████████▉ | 182/204 [02:43<00:20,  1.09it/s]

→ 500 Phase 2: corners:  90%|████████▉ | 183/204 [02:44<00:19,  1.09it/s]

→ 500 Phase 2: corners:  90%|█████████ | 184/204 [02:45<00:18,  1.11it/s]

→ 500 Phase 2: corners:  91%|█████████ | 185/204 [02:46<00:16,  1.12it/s]

→ 500 Phase 2: corners:  91%|█████████ | 186/204 [02:47<00:15,  1.14it/s]

→ 500 Phase 2: corners:  92%|█████████▏| 187/204 [02:48<00:14,  1.15it/s]

→ 500 Phase 2: corners:  92%|█████████▏| 188/204 [02:49<00:14,  1.13it/s]

→ 500 Phase 2: corners:  93%|█████████▎| 189/204 [02:50<00:13,  1.13it/s]

→ 500 Phase 2: corners:  93%|█████████▎| 190/204 [02:50<00:12,  1.13it/s]

→ 500 Phase 2: corners:  94%|█████████▎| 191/204 [02:51<00:11,  1.12it/s]

→ 500 Phase 2: corners:  94%|█████████▍| 192/204 [02:52<00:10,  1.13it/s]

→ 500 Phase 2: corners:  95%|█████████▍| 193/204 [02:53<00:09,  1.14it/s]

→ 500 Phase 2: corners:  95%|█████████▌| 194/204 [02:54<00:08,  1.13it/s]

→ 500 Phase 2: corners:  96%|█████████▌| 195/204 [02:55<00:08,  1.11it/s]

→ 500 Phase 2: corners:  96%|█████████▌| 196/204 [02:56<00:06,  1.14it/s]

→ 500 Phase 2: corners:  97%|█████████▋| 197/204 [02:57<00:06,  1.12it/s]

→ 500 Phase 2: corners:  97%|█████████▋| 198/204 [02:58<00:05,  1.13it/s]

→ 500 Phase 2: corners:  98%|█████████▊| 199/204 [02:58<00:04,  1.13it/s]

→ 500 Phase 2: corners:  98%|█████████▊| 200/204 [02:59<00:03,  1.12it/s]

→ 500 Phase 2: corners:  99%|█████████▊| 201/204 [03:00<00:02,  1.14it/s]

→ 500 Phase 2: corners:  99%|█████████▉| 202/204 [03:01<00:01,  1.14it/s]

→ 500 Phase 2: corners: 100%|█████████▉| 203/204 [03:02<00:00,  1.13it/s]

→ 500 Phase 2: corners: 100%|██████████| 204/204 [03:03<00:00,  1.10it/s]

                                                                         [PASS2] Frame 0000174: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000324: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000610: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000611: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000612: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000618: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000889: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001045: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000174: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000611: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000612: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Summary: 7 frames fixed, 1 untrusted, 204 total


→ 500 Phase 3: finalize:   0%|          | 0/204 [00:00<?, ?it/s]

→ 500 Phase 3: finalize:   1%|          | 2/204 [00:00<00:15, 12.84it/s]

→ 500 Phase 3: finalize:   2%|▏         | 4/204 [00:00<00:15, 13.10it/s]

→ 500 Phase 3: finalize:   3%|▎         | 6/204 [00:00<00:15, 13.19it/s]

→ 500 Phase 3: finalize:   4%|▍         | 8/204 [00:00<00:14, 13.22it/s]

→ 500 Phase 3: finalize:   5%|▍         | 10/204 [00:00<00:14, 13.23it/s]

→ 500 Phase 3: finalize:   6%|▌         | 12/204 [00:00<00:14, 13.21it/s]

→ 500 Phase 3: finalize:   7%|▋         | 14/204 [00:01<00:14, 13.23it/s]

→ 500 Phase 3: finalize:   8%|▊         | 16/204 [00:01<00:14, 13.15it/s]

→ 500 Phase 3: finalize:   9%|▉         | 18/204 [00:01<00:14, 13.23it/s]

→ 500 Phase 3: finalize:  10%|▉         | 20/204 [00:01<00:13, 13.24it/s]

→ 500 Phase 3: finalize:  11%|█         | 22/204 [00:01<00:13, 13.21it/s]

→ 500 Phase 3: finalize:  12%|█▏        | 24/204 [00:01<00:13, 13.24it/s]

→ 500 Phase 3: finalize:  13%|█▎        | 26/204 [00:01<00:13, 13.24it/s]

→ 500 Phase 3: finalize:  14%|█▎        | 28/204 [00:02<00:13, 13.28it/s]

→ 500 Phase 3: finalize:  15%|█▍        | 30/204 [00:02<00:13, 13.26it/s]

→ 500 Phase 3: finalize:  16%|█▌        | 32/204 [00:02<00:12, 13.29it/s]

→ 500 Phase 3: finalize:  17%|█▋        | 34/204 [00:02<00:12, 13.14it/s]

→ 500 Phase 3: finalize:  18%|█▊        | 36/204 [00:02<00:12, 13.06it/s]

→ 500 Phase 3: finalize:  19%|█▊        | 38/204 [00:02<00:12, 12.96it/s]

→ 500 Phase 3: finalize:  20%|█▉        | 40/204 [00:03<00:12, 12.88it/s]

→ 500 Phase 3: finalize:  21%|██        | 42/204 [00:03<00:12, 12.84it/s]

→ 500 Phase 3: finalize:  22%|██▏       | 44/204 [00:03<00:12, 12.84it/s]

→ 500 Phase 3: finalize:  23%|██▎       | 46/204 [00:03<00:12, 12.82it/s]

→ 500 Phase 3: finalize:  24%|██▎       | 48/204 [00:03<00:12, 12.79it/s]

→ 500 Phase 3: finalize:  25%|██▍       | 50/204 [00:03<00:12, 12.77it/s]

→ 500 Phase 3: finalize:  25%|██▌       | 52/204 [00:03<00:11, 12.77it/s]

→ 500 Phase 3: finalize:  26%|██▋       | 54/204 [00:04<00:11, 12.74it/s]

→ 500 Phase 3: finalize:  27%|██▋       | 56/204 [00:04<00:11, 12.73it/s]

→ 500 Phase 3: finalize:  28%|██▊       | 58/204 [00:04<00:11, 12.72it/s]

→ 500 Phase 3: finalize:  29%|██▉       | 60/204 [00:04<00:11, 12.72it/s]

→ 500 Phase 3: finalize:  30%|███       | 62/204 [00:04<00:11, 12.69it/s]

→ 500 Phase 3: finalize:  31%|███▏      | 64/204 [00:04<00:11, 12.67it/s]

→ 500 Phase 3: finalize:  32%|███▏      | 66/204 [00:05<00:10, 12.65it/s]

→ 500 Phase 3: finalize:  33%|███▎      | 68/204 [00:05<00:10, 12.64it/s]

→ 500 Phase 3: finalize:  34%|███▍      | 70/204 [00:05<00:10, 12.69it/s]

→ 500 Phase 3: finalize:  35%|███▌      | 72/204 [00:05<00:10, 12.68it/s]

→ 500 Phase 3: finalize:  36%|███▋      | 74/204 [00:05<00:10, 12.74it/s]

→ 500 Phase 3: finalize:  37%|███▋      | 76/204 [00:05<00:10, 12.78it/s]

→ 500 Phase 3: finalize:  38%|███▊      | 78/204 [00:06<00:09, 12.76it/s]

→ 500 Phase 3: finalize:  39%|███▉      | 80/204 [00:06<00:09, 12.75it/s]

→ 500 Phase 3: finalize:  40%|████      | 82/204 [00:06<00:09, 12.82it/s]

→ 500 Phase 3: finalize:  41%|████      | 84/204 [00:06<00:09, 12.92it/s]

→ 500 Phase 3: finalize:  42%|████▏     | 86/204 [00:06<00:09, 12.96it/s]

→ 500 Phase 3: finalize:  43%|████▎     | 88/204 [00:06<00:08, 13.09it/s]

→ 500 Phase 3: finalize:  44%|████▍     | 90/204 [00:06<00:08, 13.13it/s]

→ 500 Phase 3: finalize:  45%|████▌     | 92/204 [00:07<00:08, 13.28it/s]

→ 500 Phase 3: finalize:  46%|████▌     | 94/204 [00:07<00:08, 13.38it/s]

→ 500 Phase 3: finalize:  47%|████▋     | 96/204 [00:07<00:08, 13.50it/s]

→ 500 Phase 3: finalize:  48%|████▊     | 98/204 [00:07<00:07, 13.67it/s]

→ 500 Phase 3: finalize:  49%|████▉     | 100/204 [00:07<00:07, 13.78it/s]

→ 500 Phase 3: finalize:  50%|█████     | 102/204 [00:07<00:07, 13.82it/s]

→ 500 Phase 3: finalize:  51%|█████     | 104/204 [00:07<00:07, 13.92it/s]

→ 500 Phase 3: finalize:  52%|█████▏    | 106/204 [00:08<00:07, 13.99it/s]

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→ 500 Phase 3: finalize:  89%|████████▉ | 182/204 [00:13<00:01, 13.27it/s]

→ 500 Phase 3: finalize:  90%|█████████ | 184/204 [00:13<00:01, 13.33it/s]

→ 500 Phase 3: finalize:  91%|█████████ | 186/204 [00:13<00:01, 13.32it/s]

→ 500 Phase 3: finalize:  92%|█████████▏| 188/204 [00:14<00:01, 13.32it/s]

→ 500 Phase 3: finalize:  93%|█████████▎| 190/204 [00:14<00:01, 13.35it/s]

→ 500 Phase 3: finalize:  94%|█████████▍| 192/204 [00:14<00:00, 13.31it/s]

→ 500 Phase 3: finalize:  95%|█████████▌| 194/204 [00:14<00:00, 13.29it/s]

→ 500 Phase 3: finalize:  96%|█████████▌| 196/204 [00:14<00:00, 13.28it/s]

→ 500 Phase 3: finalize:  97%|█████████▋| 198/204 [00:14<00:00, 13.26it/s]

→ 500 Phase 3: finalize:  98%|█████████▊| 200/204 [00:14<00:00, 13.28it/s]

→ 500 Phase 3: finalize:  99%|█████████▉| 202/204 [00:15<00:00, 13.25it/s]

→ 500 Phase 3: finalize: 100%|██████████| 204/204 [00:15<00:00, 13.25it/s]

                                                                          
Processing Rigs: 100%|██████████| 2/2 [07:07<00:00, 214.82s/it]
Processing Rigs: 100%|██████████| 2/2 [07:07<00:00, 213.57s/it]
[💾] Saved RigFrameDataset to /working/MDC102_W039_2025-08-29/calibration/debug/1_digitized_full/rig_frames_full.json
[✅] Saved full dataset: 412 frames from 2 rigs to /working/MDC102_W039_2025-08-29/calibration/debug/1_digitized_full/rig_frames_full.json
[💾] Saved RigFrameDataset to /working/MDC102_W039_2025-08-29/calibration/debug/1_digitized_full/rig_frames_full.json
[📋] Creating calibration subset (100 frames/rig) with visualizations...
[📋] 1000: 100 frames selected from 208
[📋] 500: 100 frames selected from 204
[💾] Saved RigFrameDataset to /working/MDC102_W039_2025-08-29/calibration/debug/1_digitized/rig_frames.json
[INFO] Reloading dataset from disk to ensure clean state for multiprocessing...
[📂] Loaded RigFrameDataset from /working/MDC102_W039_2025-08-29/calibration/debug/1_digitized/rig_frames.json

-------------------------------------------------------------------
                        Step 2: Calibration                        
-------------------------------------------------------------------

-> Calculating the casing center ...
[INFO] Using 40 total sampled bright frames

Computing max image from bright frames:   0%|          | 0/40 [00:00<?, ?it/s]
Computing max image from bright frames:   2%|▎         | 1/40 [00:03<02:04,  3.20s/it]
Computing max image from bright frames:   5%|▌         | 2/40 [00:06<02:00,  3.17s/it]
Computing max image from bright frames:   8%|▊         | 3/40 [00:09<01:55,  3.12s/it]
Computing max image from bright frames:  10%|█         | 4/40 [00:12<01:52,  3.12s/it]
Computing max image from bright frames:  12%|█▎        | 5/40 [00:15<01:48,  3.10s/it]
Computing max image from bright frames:  15%|█▌        | 6/40 [00:18<01:45,  3.09s/it]
Computing max image from bright frames:  18%|█▊        | 7/40 [00:21<01:42,  3.10s/it]
Computing max image from bright frames:  20%|██        | 8/40 [00:24<01:39,  3.10s/it]
Computing max image from bright frames:  22%|██▎       | 9/40 [00:27<01:35,  3.10s/it]
Computing max image from bright frames:  25%|██▌       | 10/40 [00:31<01:33,  3.10s/it]
Computing max image from bright frames:  28%|██▊       | 11/40 [00:34<01:31,  3.16s/it]
Computing max image from bright frames:  30%|███       | 12/40 [00:37<01:28,  3.17s/it]
Computing max image from bright frames:  32%|███▎      | 13/40 [00:40<01:26,  3.20s/it]
Computing max image from bright frames:  35%|███▌      | 14/40 [00:44<01:24,  3.24s/it]
Computing max image from bright frames:  38%|███▊      | 15/40 [00:47<01:21,  3.26s/it]
Computing max image from bright frames:  40%|████      | 16/40 [00:50<01:17,  3.23s/it]
Computing max image from bright frames:  42%|████▎     | 17/40 [00:53<01:13,  3.20s/it]
Computing max image from bright frames:  45%|████▌     | 18/40 [00:56<01:09,  3.17s/it]
Computing max image from bright frames:  48%|████▊     | 19/40 [00:59<01:06,  3.15s/it]
Computing max image from bright frames:  50%|█████     | 20/40 [01:03<01:02,  3.13s/it]
Computing max image from bright frames:  52%|█████▎    | 21/40 [01:06<00:59,  3.14s/it]
Computing max image from bright frames:  55%|█████▌    | 22/40 [01:09<00:56,  3.16s/it]
Computing max image from bright frames:  57%|█████▊    | 23/40 [01:12<00:53,  3.16s/it]
Computing max image from bright frames:  60%|██████    | 24/40 [01:15<00:50,  3.16s/it]
Computing max image from bright frames:  62%|██████▎   | 25/40 [01:18<00:47,  3.17s/it]
Computing max image from bright frames:  65%|██████▌   | 26/40 [01:22<00:44,  3.17s/it]
Computing max image from bright frames:  68%|██████▊   | 27/40 [01:25<00:41,  3.18s/it]
Computing max image from bright frames:  70%|███████   | 28/40 [01:28<00:38,  3.18s/it]
Computing max image from bright frames:  72%|███████▎  | 29/40 [01:31<00:34,  3.17s/it]
Computing max image from bright frames:  75%|███████▌  | 30/40 [01:34<00:31,  3.19s/it]
Computing max image from bright frames:  78%|███████▊  | 31/40 [01:38<00:28,  3.22s/it]
Computing max image from bright frames:  80%|████████  | 32/40 [01:41<00:25,  3.22s/it]
Computing max image from bright frames:  82%|████████▎ | 33/40 [01:44<00:22,  3.21s/it]
Computing max image from bright frames:  85%|████████▌ | 34/40 [01:47<00:19,  3.22s/it]
Computing max image from bright frames:  88%|████████▊ | 35/40 [01:50<00:15,  3.19s/it]
Computing max image from bright frames:  90%|█████████ | 36/40 [01:54<00:12,  3.18s/it]
Computing max image from bright frames:  92%|█████████▎| 37/40 [01:57<00:09,  3.17s/it]
Computing max image from bright frames:  95%|█████████▌| 38/40 [02:00<00:06,  3.16s/it]
Computing max image from bright frames:  98%|█████████▊| 39/40 [02:03<00:03,  3.16s/it]
Computing max image from bright frames: 100%|██████████| 40/40 [02:06<00:00,  3.15s/it]
                                                                                       

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Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):   0%|          | 0/100 [00:00<?, ?it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):   1%|          | 1/100 [00:00<00:11,  8.46it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):   2%|▏         | 2/100 [00:00<00:05, 16.92it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):   2%|▏         | 2/100 [00:00<00:05, 16.92it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):   3%|▎         | 3/100 [00:00<00:05, 16.92it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):   4%|▍         | 4/100 [00:00<00:05, 16.92it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):   5%|▌         | 5/100 [00:00<00:05, 16.92it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):   6%|▌         | 6/100 [00:00<00:05, 16.92it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):   7%|▋         | 7/100 [00:00<00:05, 16.92it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):   8%|▊         | 8/100 [00:00<00:05, 16.92it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):   9%|▉         | 9/100 [00:00<00:05, 16.92it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):  10%|█         | 10/100 [00:00<00:05, 16.92it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):  11%|█         | 11/100 [00:00<00:05, 16.92it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):  12%|█▏        | 12/100 [00:00<00:05, 16.92it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):  13%|█▎        | 13/100 [00:00<00:01, 64.63it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):  13%|█▎        | 13/100 [00:00<00:01, 64.63it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):  14%|█▍        | 14/100 [00:00<00:01, 64.63it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):  15%|█▌        | 15/100 [00:00<00:01, 64.63it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):  16%|█▌        | 16/100 [00:00<00:01, 64.63it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):  17%|█▋        | 17/100 [00:00<00:01, 64.63it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):  18%|█▊        | 18/100 [00:00<00:01, 64.63it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):  19%|█▉        | 19/100 [00:00<00:01, 64.63it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):  20%|██        | 20/100 [00:00<00:01, 64.63it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):  21%|██        | 21/100 [00:00<00:01, 64.63it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):  22%|██▏       | 22/100 [00:00<00:01, 64.63it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):  23%|██▎       | 23/100 [00:00<00:01, 64.63it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):  24%|██▍       | 24/100 [00:00<00:01, 64.63it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 307.071} (0.000):  25%|██▌       | 25/100 [00:00<00:00, 84.61it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 483.838} (0.000):  25%|██▌       | 25/100 [00:00<00:00, 84.61it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.000 | Best: {'fx': 483.838} (0.000):  26%|██▌       | 26/100 [00:00<00:00, 84.61it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.002 | Best: {'fx': 490.909} (0.002):  27%|██▋       | 27/100 [00:00<00:00, 84.61it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.002 | Best: {'fx': 497.98} (0.002):  28%|██▊       | 28/100 [00:00<00:00, 84.61it/s] 
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.025 | Best: {'fx': 554.545} (0.025):  29%|██▉       | 29/100 [00:00<00:00, 84.61it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.032 | Best: {'fx': 519.192} (0.032):  30%|███       | 30/100 [00:00<00:00, 84.61it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.031 | Best: {'fx': 519.192} (0.032):  31%|███       | 31/100 [00:00<00:00, 84.61it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.050 | Best: {'fx': 526.263} (0.050):  32%|███▏      | 32/100 [00:00<00:00, 84.61it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.008 | Best: {'fx': 526.263} (0.050):  33%|███▎      | 33/100 [00:00<00:00, 84.61it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.021 | Best: {'fx': 526.263} (0.050):  34%|███▍      | 34/100 [00:00<00:00, 84.61it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.071 | Best: {'fx': 533.333} (0.071):  35%|███▌      | 35/100 [00:00<00:00, 84.61it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.021 | Best: {'fx': 533.333} (0.071):  36%|███▌      | 36/100 [00:00<00:00, 84.61it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.043 | Best: {'fx': 533.333} (0.071):  37%|███▋      | 37/100 [00:00<00:00, 84.61it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.043 | Best: {'fx': 533.333} (0.071):  38%|███▊      | 38/100 [00:00<00:00, 97.07it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.019 | Best: {'fx': 533.333} (0.071):  38%|███▊      | 38/100 [00:00<00:00, 97.07it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.014 | Best: {'fx': 533.333} (0.071):  39%|███▉      | 39/100 [00:00<00:00, 97.07it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.017 | Best: {'fx': 533.333} (0.071):  40%|████      | 40/100 [00:00<00:00, 97.07it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.016 | Best: {'fx': 533.333} (0.071):  41%|████      | 41/100 [00:00<00:00, 97.07it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.015 | Best: {'fx': 533.333} (0.071):  42%|████▏     | 42/100 [00:00<00:00, 97.07it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.013 | Best: {'fx': 533.333} (0.071):  43%|████▎     | 43/100 [00:00<00:00, 97.07it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.012 | Best: {'fx': 533.333} (0.071):  44%|████▍     | 44/100 [00:00<00:00, 97.07it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.012 | Best: {'fx': 533.333} (0.071):  45%|████▌     | 45/100 [00:00<00:00, 97.07it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.013 | Best: {'fx': 533.333} (0.071):  46%|████▌     | 46/100 [00:00<00:00, 97.07it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.011 | Best: {'fx': 533.333} (0.071):  47%|████▋     | 47/100 [00:00<00:00, 97.07it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.012 | Best: {'fx': 533.333} (0.071):  48%|████▊     | 48/100 [00:00<00:00, 97.07it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.071):  49%|████▉     | 49/100 [00:00<00:00, 97.07it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.071):  50%|█████     | 50/100 [00:00<00:00, 98.28it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.011 | Best: {'fx': 533.333} (0.071):  50%|█████     | 50/100 [00:00<00:00, 98.28it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.011 | Best: {'fx': 533.333} (0.071):  51%|█████     | 51/100 [00:00<00:00, 98.28it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.071):  52%|█████▏    | 52/100 [00:00<00:00, 98.28it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.011 | Best: {'fx': 533.333} (0.071):  53%|█████▎    | 53/100 [00:00<00:00, 98.28it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.011 | Best: {'fx': 533.333} (0.071):  54%|█████▍    | 54/100 [00:00<00:00, 98.28it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.071):  55%|█████▌    | 55/100 [00:00<00:00, 98.28it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.071):  56%|█████▌    | 56/100 [00:00<00:00, 98.28it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.071):  57%|█████▋    | 57/100 [00:00<00:00, 98.28it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.071):  58%|█████▊    | 58/100 [00:00<00:00, 98.28it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.071):  59%|█████▉    | 59/100 [00:00<00:00, 98.28it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.071):  60%|██████    | 60/100 [00:00<00:00, 98.28it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.071):  61%|██████    | 61/100 [00:00<00:00, 98.28it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  62%|██████▏   | 62/100 [00:00<00:00, 98.28it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  63%|██████▎   | 63/100 [00:00<00:00, 98.28it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.010 | Best: {'fx': 533.333} (0.071):  64%|██████▍   | 64/100 [00:00<00:00, 98.28it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  65%|██████▌   | 65/100 [00:00<00:00, 98.28it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  66%|██████▌   | 66/100 [00:00<00:00, 114.67it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  66%|██████▌   | 66/100 [00:00<00:00, 114.67it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  67%|██████▋   | 67/100 [00:00<00:00, 114.67it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  68%|██████▊   | 68/100 [00:00<00:00, 114.67it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  69%|██████▉   | 69/100 [00:00<00:00, 114.67it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  70%|███████   | 70/100 [00:00<00:00, 114.67it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  71%|███████   | 71/100 [00:00<00:00, 114.67it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  72%|███████▏  | 72/100 [00:00<00:00, 114.67it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  73%|███████▎  | 73/100 [00:00<00:00, 114.67it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  74%|███████▍  | 74/100 [00:00<00:00, 114.67it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  75%|███████▌  | 75/100 [00:00<00:00, 114.67it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  76%|███████▌  | 76/100 [00:00<00:00, 114.67it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  77%|███████▋  | 77/100 [00:00<00:00, 114.67it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  78%|███████▊  | 78/100 [00:00<00:00, 114.67it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  79%|███████▉  | 79/100 [00:00<00:00, 114.67it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  80%|████████  | 80/100 [00:00<00:00, 114.67it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  81%|████████  | 81/100 [00:00<00:00, 123.94it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  81%|████████  | 81/100 [00:00<00:00, 123.94it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  82%|████████▏ | 82/100 [00:00<00:00, 123.94it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  83%|████████▎ | 83/100 [00:00<00:00, 123.94it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  84%|████████▍ | 84/100 [00:00<00:00, 123.94it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  85%|████████▌ | 85/100 [00:00<00:00, 123.94it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  86%|████████▌ | 86/100 [00:00<00:00, 123.94it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  87%|████████▋ | 87/100 [00:00<00:00, 123.94it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  88%|████████▊ | 88/100 [00:00<00:00, 123.94it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  89%|████████▉ | 89/100 [00:00<00:00, 123.94it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  90%|█████████ | 90/100 [00:00<00:00, 123.94it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  91%|█████████ | 91/100 [00:00<00:00, 123.94it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  92%|█████████▏| 92/100 [00:00<00:00, 123.94it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  93%|█████████▎| 93/100 [00:00<00:00, 123.94it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  94%|█████████▍| 94/100 [00:00<00:00, 123.94it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  95%|█████████▌| 95/100 [00:00<00:00, 123.94it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  96%|█████████▌| 96/100 [00:00<00:00, 123.94it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  97%|█████████▋| 97/100 [00:00<00:00, 123.94it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  98%|█████████▊| 98/100 [00:00<00:00, 136.45it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  98%|█████████▊| 98/100 [00:00<00:00, 136.45it/s]
Brute | Start: {'fx': 500.0} (0.003) | Current: 0.009 | Best: {'fx': 533.333} (0.071):  99%|█████████▉| 99/100 [00:00<00:00, 136.45it/s]
                                                                                                                                        

  0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.012 | Best: {'fx': 508.333} (0.012):   0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.012 | Best: {'fx': 508.333} (0.012):   2%|▏         | 1/50 [00:00<00:05,  9.06it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.013 | Best: {'fx': 509.354} (0.013):   2%|▏         | 1/50 [00:00<00:05,  9.06it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.026 | Best: {'fx': 515.476} (0.026):   4%|▍         | 2/50 [00:00<00:05,  9.06it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.018 | Best: {'fx': 515.476} (0.026):   6%|▌         | 3/50 [00:00<00:05,  9.06it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.023 | Best: {'fx': 515.476} (0.026):   8%|▊         | 4/50 [00:00<00:05,  9.06it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.019 | Best: {'fx': 515.476} (0.026):  10%|█         | 5/50 [00:00<00:04,  9.06it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.022 | Best: {'fx': 515.476} (0.026):  12%|█▏        | 6/50 [00:00<00:04,  9.06it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.024 | Best: {'fx': 515.476} (0.026):  14%|█▍        | 7/50 [00:00<00:04,  9.06it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.028 | Best: {'fx': 516.497} (0.028):  16%|█▌        | 8/50 [00:00<00:04,  9.06it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.030 | Best: {'fx': 517.517} (0.030):  18%|█▊        | 9/50 [00:00<00:04,  9.06it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.041 | Best: {'fx': 523.639} (0.041):  20%|██        | 10/50 [00:00<00:04,  9.06it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.041 | Best: {'fx': 523.639} (0.041):  22%|██▏       | 11/50 [00:00<00:00, 58.05it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.031 | Best: {'fx': 523.639} (0.041):  22%|██▏       | 11/50 [00:00<00:00, 58.05it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.033 | Best: {'fx': 523.639} (0.041):  24%|██▍       | 12/50 [00:00<00:00, 58.05it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.035 | Best: {'fx': 523.639} (0.041):  26%|██▌       | 13/50 [00:00<00:00, 58.05it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.038 | Best: {'fx': 523.639} (0.041):  28%|██▊       | 14/50 [00:00<00:00, 58.05it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.038 | Best: {'fx': 523.639} (0.041):  30%|███       | 15/50 [00:00<00:00, 58.05it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.052 | Best: {'fx': 526.701} (0.052):  32%|███▏      | 16/50 [00:00<00:00, 58.05it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.049 | Best: {'fx': 526.701} (0.052):  34%|███▍      | 17/50 [00:00<00:00, 58.05it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.045 | Best: {'fx': 526.701} (0.052):  36%|███▌      | 18/50 [00:00<00:00, 58.05it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.066 | Best: {'fx': 528.741} (0.066):  38%|███▊      | 19/50 [00:00<00:00, 58.05it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.062 | Best: {'fx': 528.741} (0.066):  40%|████      | 20/50 [00:00<00:00, 58.05it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.076 | Best: {'fx': 530.782} (0.076):  42%|████▏     | 21/50 [00:00<00:00, 58.05it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.066 | Best: {'fx': 530.782} (0.076):  44%|████▍     | 22/50 [00:00<00:00, 58.05it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.074 | Best: {'fx': 530.782} (0.076):  46%|████▌     | 23/50 [00:00<00:00, 58.05it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.074 | Best: {'fx': 530.782} (0.076):  48%|████▊     | 24/50 [00:00<00:00, 84.22it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.055 | Best: {'fx': 530.782} (0.076):  48%|████▊     | 24/50 [00:00<00:00, 84.22it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.072 | Best: {'fx': 530.782} (0.076):  50%|█████     | 25/50 [00:00<00:00, 84.22it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.065 | Best: {'fx': 530.782} (0.076):  52%|█████▏    | 26/50 [00:00<00:00, 84.22it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.053 | Best: {'fx': 530.782} (0.076):  54%|█████▍    | 27/50 [00:00<00:00, 84.22it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.064 | Best: {'fx': 530.782} (0.076):  56%|█████▌    | 28/50 [00:00<00:00, 84.22it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.046 | Best: {'fx': 530.782} (0.076):  58%|█████▊    | 29/50 [00:00<00:00, 84.22it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.040 | Best: {'fx': 530.782} (0.076):  60%|██████    | 30/50 [00:00<00:00, 84.22it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.051 | Best: {'fx': 530.782} (0.076):  62%|██████▏   | 31/50 [00:00<00:00, 84.22it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.035 | Best: {'fx': 530.782} (0.076):  64%|██████▍   | 32/50 [00:00<00:00, 84.22it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.044 | Best: {'fx': 530.782} (0.076):  66%|██████▌   | 33/50 [00:00<00:00, 84.22it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.041 | Best: {'fx': 530.782} (0.076):  68%|██████▊   | 34/50 [00:00<00:00, 84.22it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.038 | Best: {'fx': 530.782} (0.076):  70%|███████   | 35/50 [00:00<00:00, 84.22it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.034 | Best: {'fx': 530.782} (0.076):  72%|███████▏  | 36/50 [00:00<00:00, 84.22it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.034 | Best: {'fx': 530.782} (0.076):  74%|███████▍  | 37/50 [00:00<00:00, 99.97it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.033 | Best: {'fx': 530.782} (0.076):  74%|███████▍  | 37/50 [00:00<00:00, 99.97it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.030 | Best: {'fx': 530.782} (0.076):  76%|███████▌  | 38/50 [00:00<00:00, 99.97it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.032 | Best: {'fx': 530.782} (0.076):  78%|███████▊  | 39/50 [00:00<00:00, 99.97it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.029 | Best: {'fx': 530.782} (0.076):  80%|████████  | 40/50 [00:00<00:00, 99.97it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.029 | Best: {'fx': 530.782} (0.076):  82%|████████▏ | 41/50 [00:00<00:00, 99.97it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.028 | Best: {'fx': 530.782} (0.076):  84%|████████▍ | 42/50 [00:00<00:00, 99.97it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.027 | Best: {'fx': 530.782} (0.076):  86%|████████▌ | 43/50 [00:00<00:00, 99.97it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.025 | Best: {'fx': 530.782} (0.076):  88%|████████▊ | 44/50 [00:00<00:00, 99.97it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.026 | Best: {'fx': 530.782} (0.076):  90%|█████████ | 45/50 [00:00<00:00, 99.97it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.023 | Best: {'fx': 530.782} (0.076):  92%|█████████▏| 46/50 [00:00<00:00, 99.97it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.024 | Best: {'fx': 530.782} (0.076):  94%|█████████▍| 47/50 [00:00<00:00, 99.97it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.025 | Best: {'fx': 530.782} (0.076):  96%|█████████▌| 48/50 [00:00<00:00, 99.97it/s]
Brute | Start: {'fx': 533.333} (0.071) | Current: 0.023 | Best: {'fx': 530.782} (0.076):  98%|█████████▊| 49/50 [00:00<00:00, 99.97it/s]
                                                                                                                                        
[DEBUG] Parameters after Step 5 (before square optimization):
    fx: 530.7823129251701
    px: 993.0
    py: 760.0
    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

  [Ring preference] diameter=3500 mm  →  radius=1379.7 px

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

Initial score: 39.6660: 0iter [00:00, ?iter/s]  [Ring mask] 25,852/25,852 points within ring radius 1379.7 px
[DEBUG] objective(x0) = 39.6660, picklable_objective(x0) = 39.6647

Best score: 39.6647: : 0iter [00:01, ?iter/s] 
Best score: 39.6647: : 1iter [00:01,  1.93s/iter]
Best score: 39.6647: : 1iter [00:01,  1.93s/iter]
Best score: 39.6647: : 2iter [00:02,  1.93s/iter]
Best score: 39.6647: : 3iter [00:02,  1.93s/iter]
Best score: 39.6647: : 4iter [00:02,  2.49iter/s]
Best score: 39.6647: : 4iter [00:02,  2.49iter/s]
Best score: 39.6647: : 5iter [00:02,  2.49iter/s]
Best score: 39.6647: : 6iter [00:02,  2.49iter/s]
Best score: 39.6647: : 7iter [00:02,  4.75iter/s]
Best score: 39.6647: : 7iter [00:02,  4.75iter/s]
Best score: 39.6647: : 8iter [00:02,  4.75iter/s]
Best score: 39.6647: : 9iter [00:02,  4.75iter/s]
Best score: 39.6647: : 10iter [00:02,  7.18iter/s]
Best score: 39.6647: : 10iter [00:02,  7.18iter/s]
Best score: 39.6647: : 11iter [00:02,  7.18iter/s]
Best score: 39.6647: : 12iter [00:02,  7.18iter/s]
Best score: 39.6647: : 13iter [00:02,  9.68iter/s]
Best score: 39.6647: : 13iter [00:02,  9.68iter/s]
Best score: 39.6647: : 14iter [00:02,  9.68iter/s]
Best score: 39.6647: : 15iter [00:02,  9.68iter/s]
Best score: 39.6647: : 16iter [00:02, 12.08iter/s]
Best score: 39.6647: : 16iter [00:02, 12.08iter/s]
Best score: 39.6647: : 17iter [00:02, 12.08iter/s]
Best score: 39.6647: : 18iter [00:02, 12.08iter/s]
Best score: 39.6647: : 19iter [00:02, 14.26iter/s]
Best score: 39.6647: : 19iter [00:02, 14.26iter/s]
Best score: 39.6647: : 20iter [00:02, 14.26iter/s]
Best score: 39.6647: : 21iter [00:02, 14.26iter/s]
Best score: 39.6647: : 22iter [00:02, 16.04iter/s]
Best score: 39.6647: : 22iter [00:02, 16.04iter/s]
Best score: 39.6647: : 23iter [00:02, 16.04iter/s]
Best score: 39.6647: : 24iter [00:03, 16.04iter/s]
Best score: 39.6647: : 25iter [00:03, 17.61iter/s]
Best score: 39.6647: : 25iter [00:03, 17.61iter/s]
Best score: 39.6647: : 26iter [00:03, 17.61iter/s]
Best score: 39.6647: : 27iter [00:03, 17.61iter/s]
Best score: 39.6647: : 28iter [00:03, 18.86iter/s]
Best score: 39.6647: : 28iter [00:03, 18.86iter/s]
Best score: 39.6647: : 29iter [00:03, 18.86iter/s]
Best score: 39.6647: : 30iter [00:03, 18.86iter/s]
Best score: 39.6647: : 31iter [00:03, 19.66iter/s]
Best score: 39.6647: : 31iter [00:03, 19.66iter/s]
Best score: 39.6647: : 32iter [00:03, 19.66iter/s]
Best score: 39.6647: : 33iter [00:03, 19.66iter/s]
Best score: 39.6647: : 34iter [00:03, 20.42iter/s]
Best score: 39.6647: : 34iter [00:03, 20.42iter/s]
Best score: 39.6647: : 35iter [00:03, 20.42iter/s]
Best score: 39.6647: : 36iter [00:03, 20.42iter/s]
Best score: 39.6647: : 37iter [00:03, 20.93iter/s]
Best score: 39.6647: : 37iter [00:03, 20.93iter/s]
Best score: 39.6647: : 38iter [00:03, 20.93iter/s]
Best score: 39.6647: : 39iter [00:03, 20.93iter/s]
Best score: 39.6647: : 40iter [00:03, 21.20iter/s]
Best score: 39.6647: : 40iter [00:03, 21.20iter/s]
Best score: 39.6647: : 41iter [00:03, 21.20iter/s]
Best score: 39.6647: : 42iter [00:03, 21.20iter/s]
Best score: 39.6647: : 43iter [00:03, 21.53iter/s]
Best score: 39.6647: : 43iter [00:03, 21.53iter/s]
Best score: 39.6647: : 44iter [00:03, 21.53iter/s]
Best score: 39.6647: : 45iter [00:03, 21.53iter/s]
Best score: 39.6647: : 46iter [00:03, 21.77iter/s]
Best score: 39.6647: : 46iter [00:04, 21.77iter/s]
Best score: 39.6647: : 47iter [00:04, 21.77iter/s]
Best score: 39.6647: : 48iter [00:04, 21.77iter/s]
Best score: 39.6647: : 49iter [00:04, 21.92iter/s]
[ITER 50] Best: 28.4803
[PARAMS] Current best parameters:
  fx: 526.6512
  fy: 530.6611
  px: 998.0613
  py: 767.6052
  k1: 0.03640419
  k2: -0.01825723
  k3: 0.00105519
  k4: -0.00115290
  p1: 0.00491073
  p2: -0.00180072
  p3: 0.00280606
  p4: 0.00438026
  scale: 2.9120
  rotation: 0.1011

Best score: 28.4803: : 49iter [00:04, 21.92iter/s]
Best score: 28.4803: : 50iter [00:04, 21.92iter/s]
Best score: 28.4803: : 51iter [00:04, 21.92iter/s]
Best score: 28.4803: : 52iter [00:04, 21.78iter/s]
Best score: 28.4803: : 52iter [00:04, 21.78iter/s]
Best score: 28.4803: : 53iter [00:04, 21.78iter/s]
Best score: 28.4803: : 54iter [00:04, 21.78iter/s]
Best score: 28.4803: : 55iter [00:04, 21.94iter/s]
Best score: 28.4803: : 55iter [00:04, 21.94iter/s]
Best score: 28.4803: : 56iter [00:04, 21.94iter/s]
Best score: 28.4803: : 57iter [00:04, 21.94iter/s]
Best score: 28.4803: : 58iter [00:04, 22.06iter/s]
Best score: 28.4803: : 58iter [00:04, 22.06iter/s]
Best score: 16.7104: : 59iter [00:04, 22.06iter/s]
Best score: 16.7104: : 60iter [00:04, 22.06iter/s]
Best score: 16.7104: : 61iter [00:04, 21.93iter/s]
Best score: 16.7104: : 61iter [00:04, 21.93iter/s]
Best score: 16.7104: : 62iter [00:04, 21.93iter/s]
Best score: 16.7104: : 63iter [00:04, 21.93iter/s]
Best score: 16.7104: : 64iter [00:04, 22.07iter/s]
Best score: 16.7104: : 64iter [00:04, 22.07iter/s]
Best score: 16.7104: : 65iter [00:04, 22.07iter/s]
Best score: 16.7104: : 66iter [00:04, 22.07iter/s]
Best score: 16.7104: : 67iter [00:04, 22.14iter/s]
Best score: 16.7104: : 67iter [00:04, 22.14iter/s]
Best score: 16.7104: : 68iter [00:05, 22.14iter/s]
Best score: 16.7104: : 69iter [00:05, 22.14iter/s]
Best score: 16.7104: : 70iter [00:05, 22.05iter/s]
Best score: 16.7104: : 70iter [00:05, 22.05iter/s]
Best score: 16.7104: : 71iter [00:05, 22.05iter/s]
Best score: 16.7104: : 72iter [00:05, 22.05iter/s]
Best score: 16.7104: : 73iter [00:05, 22.18iter/s]
Best score: 16.7104: : 73iter [00:05, 22.18iter/s]
Best score: 16.7104: : 74iter [00:05, 22.18iter/s]
Best score: 16.7104: : 75iter [00:05, 22.18iter/s]
Best score: 16.7104: : 76iter [00:05, 22.28iter/s]
Best score: 16.7104: : 76iter [00:05, 22.28iter/s]
Best score: 16.7104: : 77iter [00:05, 22.28iter/s]
Best score: 16.7104: : 78iter [00:05, 22.28iter/s]
Best score: 16.7104: : 79iter [00:05, 22.28iter/s]
Best score: 6.8637: : 79iter [00:05, 22.28iter/s] 
Best score: 6.8637: : 80iter [00:05, 22.28iter/s]
Best score: 6.8637: : 81iter [00:05, 22.28iter/s]
Best score: 6.8637: : 82iter [00:05, 22.12iter/s]
Best score: 6.8637: : 82iter [00:05, 22.12iter/s]
Best score: 6.8637: : 83iter [00:05, 22.12iter/s]
Best score: 6.8637: : 84iter [00:05, 22.12iter/s]
Best score: 6.8637: : 85iter [00:05, 22.22iter/s]
Best score: 6.8637: : 85iter [00:05, 22.22iter/s]
Best score: 6.8637: : 86iter [00:05, 22.22iter/s]
Best score: 6.8637: : 87iter [00:05, 22.22iter/s]
Best score: 6.8637: : 88iter [00:05, 22.38iter/s]
Best score: 6.8637: : 88iter [00:05, 22.38iter/s]
Best score: 4.5105: : 89iter [00:05, 22.38iter/s]
Best score: 4.5105: : 90iter [00:05, 22.38iter/s]
Best score: 4.5105: : 91iter [00:05, 22.19iter/s]
Best score: 4.5105: : 91iter [00:06, 22.19iter/s]
Best score: 4.5105: : 92iter [00:06, 22.19iter/s]
Best score: 4.5105: : 93iter [00:06, 22.19iter/s]
Best score: 4.5105: : 94iter [00:06, 22.28iter/s]
Best score: 4.5105: : 94iter [00:06, 22.28iter/s]
Best score: 4.5105: : 95iter [00:06, 22.28iter/s]
Best score: 4.5105: : 96iter [00:06, 22.28iter/s]
Best score: 4.5105: : 97iter [00:06, 22.26iter/s]
Best score: 4.5105: : 97iter [00:06, 22.26iter/s]
Best score: 4.5105: : 98iter [00:06, 22.26iter/s]
[ITER 100] Best: 4.5105
[PARAMS] Current best parameters:
  fx: 529.3289
  fy: 528.1862
  px: 1000.0631
  py: 765.4055
  k1: 0.02039478
  k2: -0.01015927
  k3: 0.00036085
  k4: -0.00054305
  p1: 0.00458818
  p2: 0.00530636
  p3: 0.00319814
  p4: -0.00017649
  scale: 2.9582
  rotation: 0.2643

Best score: 4.5105: : 99iter [00:06, 22.26iter/s]
Best score: 4.5105: : 100iter [00:06, 22.09iter/s]
Best score: 4.5105: : 100iter [00:06, 22.09iter/s]
Best score: 4.5105: : 101iter [00:06, 22.09iter/s]
Best score: 4.5105: : 102iter [00:06, 22.09iter/s]
Best score: 4.5105: : 103iter [00:06, 22.26iter/s]
Best score: 4.5105: : 103iter [00:06, 22.26iter/s]
Best score: 4.5105: : 104iter [00:06, 22.26iter/s]
Best score: 4.5105: : 105iter [00:06, 22.26iter/s]
Best score: 4.5105: : 106iter [00:06, 22.39iter/s]
Best score: 4.5105: : 106iter [00:06, 22.39iter/s]
Best score: 4.5105: : 107iter [00:06, 22.39iter/s]
Best score: 4.5105: : 108iter [00:06, 22.39iter/s]
Best score: 4.5105: : 109iter [00:06, 22.46iter/s]
Best score: 3.3864: : 109iter [00:06, 22.46iter/s]
Best score: 3.3864: : 110iter [00:06, 22.46iter/s]
Best score: 3.3864: : 111iter [00:06, 22.46iter/s]
Best score: 3.3864: : 112iter [00:06, 22.28iter/s]
Best score: 3.3864: : 112iter [00:06, 22.28iter/s]
Best score: 3.3864: : 113iter [00:07, 22.28iter/s]
Best score: 3.3864: : 114iter [00:07, 22.28iter/s]
Best score: 3.3864: : 115iter [00:07, 22.36iter/s]
Best score: 3.3864: : 115iter [00:07, 22.36iter/s]
Best score: 3.3864: : 116iter [00:07, 22.36iter/s]
Best score: 3.3864: : 117iter [00:07, 22.36iter/s]
Best score: 3.3864: : 118iter [00:07, 22.48iter/s]
Best score: 3.3864: : 118iter [00:07, 22.48iter/s]
Best score: 2.9083: : 119iter [00:07, 22.48iter/s]
Best score: 2.9083: : 120iter [00:07, 22.48iter/s]
Best score: 2.9083: : 121iter [00:07, 22.33iter/s]
Best score: 2.9083: : 121iter [00:07, 22.33iter/s]
Best score: 2.9083: : 122iter [00:07, 22.33iter/s]
Best score: 2.9083: : 123iter [00:07, 22.33iter/s]
Best score: 2.9083: : 124iter [00:07, 22.46iter/s]
Best score: 2.9083: : 124iter [00:07, 22.46iter/s]
Best score: 2.9083: : 125iter [00:07, 22.46iter/s]
Best score: 2.9083: : 126iter [00:07, 22.46iter/s]
Best score: 2.9083: : 127iter [00:07, 22.49iter/s]
Best score: 2.9083: : 127iter [00:07, 22.49iter/s]
Best score: 2.9083: : 128iter [00:07, 22.49iter/s]
Best score: 1.6169: : 129iter [00:07, 22.49iter/s]
Best score: 1.6169: : 130iter [00:07, 22.27iter/s]
Best score: 1.6169: : 130iter [00:07, 22.27iter/s]
Best score: 1.6169: : 131iter [00:07, 22.27iter/s]
Best score: 1.6169: : 132iter [00:07, 22.27iter/s]
Best score: 1.6169: : 133iter [00:07, 22.36iter/s]
Best score: 1.6169: : 133iter [00:07, 22.36iter/s]
Best score: 1.6169: : 134iter [00:07, 22.36iter/s]
Best score: 1.6169: : 135iter [00:08, 22.36iter/s]
Best score: 1.6169: : 136iter [00:08, 22.47iter/s]
Best score: 1.6169: : 136iter [00:08, 22.47iter/s]
Best score: 1.6169: : 137iter [00:08, 22.47iter/s]
Best score: 1.6169: : 138iter [00:08, 22.47iter/s]
Best score: 1.6169: : 139iter [00:08, 22.55iter/s]
Best score: 1.4315: : 139iter [00:08, 22.55iter/s]
Best score: 1.4315: : 140iter [00:08, 22.55iter/s]
Best score: 1.4315: : 141iter [00:08, 22.55iter/s]
Best score: 1.4315: : 142iter [00:08, 22.40iter/s]
Best score: 1.4315: : 142iter [00:08, 22.40iter/s]
Best score: 1.4315: : 143iter [00:08, 22.40iter/s]
Best score: 1.4315: : 144iter [00:08, 22.40iter/s]
Best score: 1.4315: : 145iter [00:08, 22.47iter/s]
Best score: 1.4315: : 145iter [00:08, 22.47iter/s]
Best score: 1.4315: : 146iter [00:08, 22.47iter/s]
Best score: 1.4315: : 147iter [00:08, 22.47iter/s]
Best score: 1.4315: : 148iter [00:08, 22.53iter/s]
Best score: 1.4315: : 148iter [00:08, 22.53iter/s]
[ITER 150] Best: 0.9815
[PARAMS] Current best parameters:
  fx: 519.6251
  fy: 519.4353
  px: 997.8698
  py: 764.8513
  k1: 0.02633856
  k2: 0.00530370
  k3: -0.01382622
  k4: 0.00336963
  p1: 0.00274551
  p2: 0.00018077
  p3: 0.00394554
  p4: -0.00083954
  scale: 2.9272
  rotation: 0.2648

Best score: 0.9815: : 149iter [00:08, 22.53iter/s]
Best score: 0.9815: : 150iter [00:08, 22.53iter/s]
Best score: 0.9815: : 151iter [00:08, 22.34iter/s]
Best score: 0.9815: : 151iter [00:08, 22.34iter/s]
Best score: 0.9815: : 152iter [00:08, 22.34iter/s]
Best score: 0.9815: : 153iter [00:08, 22.34iter/s]
Best score: 0.9815: : 154iter [00:08, 22.44iter/s]
Best score: 0.9815: : 154iter [00:08, 22.44iter/s]
Best score: 0.9815: : 155iter [00:08, 22.44iter/s]
Best score: 0.9815: : 156iter [00:08, 22.44iter/s]
Best score: 0.9815: : 157iter [00:08, 22.54iter/s]
Best score: 0.9815: : 157iter [00:08, 22.54iter/s]
Best score: 0.9815: : 158iter [00:09, 22.54iter/s]
Best score: 0.9025: : 159iter [00:09, 22.54iter/s]
Best score: 0.9025: : 160iter [00:09, 22.29iter/s]
Best score: 0.9025: : 160iter [00:09, 22.29iter/s]
Best score: 0.9025: : 161iter [00:09, 22.29iter/s]
Best score: 0.9025: : 162iter [00:09, 22.29iter/s]
Best score: 0.9025: : 163iter [00:09, 22.39iter/s]
Best score: 0.9025: : 163iter [00:09, 22.39iter/s]
Best score: 0.9025: : 164iter [00:09, 22.39iter/s]
Best score: 0.9025: : 165iter [00:09, 22.39iter/s]
Best score: 0.9025: : 166iter [00:09, 22.44iter/s]
Best score: 0.9025: : 166iter [00:09, 22.44iter/s]
Best score: 0.9025: : 167iter [00:09, 22.44iter/s]
Best score: 0.9025: : 168iter [00:09, 22.44iter/s]
Best score: 0.9025: : 169iter [00:09, 22.44iter/s]
Best score: 0.7824: : 169iter [00:09, 22.44iter/s]
Best score: 0.7824: : 170iter [00:09, 22.44iter/s]
Best score: 0.7824: : 171iter [00:09, 22.44iter/s]
Best score: 0.7824: : 172iter [00:09, 22.22iter/s]
Best score: 0.7824: : 172iter [00:09, 22.22iter/s]
Best score: 0.7824: : 173iter [00:09, 22.22iter/s]
Best score: 0.7824: : 174iter [00:09, 22.22iter/s]
Best score: 0.7824: : 175iter [00:09, 22.36iter/s]
Best score: 0.7824: : 175iter [00:09, 22.36iter/s]
Best score: 0.7824: : 176iter [00:09, 22.36iter/s]
Best score: 0.7824: : 177iter [00:09, 22.36iter/s]
Best score: 0.7824: : 178iter [00:09, 22.40iter/s]
Best score: 0.7824: : 178iter [00:09, 22.40iter/s]
Best score: 0.7088: : 179iter [00:09, 22.40iter/s]
Best score: 0.7088: : 180iter [00:10, 22.40iter/s]
Best score: 0.7088: : 181iter [00:10, 22.24iter/s]
Best score: 0.7088: : 181iter [00:10, 22.24iter/s]
Best score: 0.7088: : 182iter [00:10, 22.24iter/s]
Best score: 0.7088: : 183iter [00:10, 22.24iter/s]
Best score: 0.7088: : 184iter [00:10, 22.25iter/s]
Best score: 0.7088: : 184iter [00:10, 22.25iter/s]
Best score: 0.7088: : 185iter [00:10, 22.25iter/s]
Best score: 0.7088: : 186iter [00:10, 22.25iter/s]
Best score: 0.7088: : 187iter [00:10, 22.33iter/s]
Best score: 0.7088: : 187iter [00:10, 22.33iter/s]
Best score: 0.7088: : 188iter [00:10, 22.33iter/s]
Best score: 0.6570: : 189iter [00:10, 22.33iter/s]
Best score: 0.6570: : 190iter [00:10, 22.20iter/s]
Best score: 0.6570: : 190iter [00:10, 22.20iter/s]
Best score: 0.6570: : 191iter [00:10, 22.20iter/s]
Best score: 0.6570: : 192iter [00:10, 22.20iter/s]
Best score: 0.6570: : 193iter [00:10, 22.25iter/s]
Best score: 0.6570: : 193iter [00:10, 22.25iter/s]
Best score: 0.6570: : 194iter [00:10, 22.25iter/s]
Best score: 0.6570: : 195iter [00:10, 22.25iter/s]
Best score: 0.6570: : 196iter [00:10, 22.25iter/s]
Best score: 0.6570: : 196iter [00:10, 22.25iter/s]
Best score: 0.6570: : 197iter [00:10, 22.25iter/s]
Best score: 0.6570: : 198iter [00:10, 22.25iter/s]
Best score: 0.6570: : 199iter [00:10, 22.31iter/s]
[ITER 200] Best: 0.6570
[PARAMS] Current best parameters:
  fx: 534.4574
  fy: 533.9402
  px: 1000.3863
  py: 761.0743
  k1: 0.01022774
  k2: -0.00600474
  k3: -0.00167934
  k4: 0.00045760
  p1: -0.00590982
  p2: 0.00462647
  p3: 0.00710193
  p4: -0.00071506
  scale: 2.9504
  rotation: 0.2689

Best score: 0.6570: : 199iter [00:10, 22.31iter/s]
Best score: 0.6570: : 200iter [00:10, 22.31iter/s]
Best score: 0.6570: : 201iter [00:10, 22.31iter/s]
Best score: 0.6570: : 202iter [00:10, 22.17iter/s]
Best score: 0.6570: : 202iter [00:11, 22.17iter/s]
Best score: 0.6570: : 203iter [00:11, 22.17iter/s]
Best score: 0.6570: : 204iter [00:11, 22.17iter/s]
Best score: 0.6570: : 205iter [00:11, 22.26iter/s]
Best score: 0.6570: : 205iter [00:11, 22.26iter/s]
Best score: 0.6570: : 206iter [00:11, 22.26iter/s]
Best score: 0.6570: : 207iter [00:11, 22.26iter/s]
Best score: 0.6570: : 208iter [00:11, 22.31iter/s]
Best score: 0.6570: : 208iter [00:11, 22.31iter/s]
Best score: 0.5871: : 209iter [00:11, 22.31iter/s]
Best score: 0.5871: : 210iter [00:11, 22.31iter/s]
Best score: 0.5871: : 211iter [00:11, 22.13iter/s]
Best score: 0.5871: : 211iter [00:11, 22.13iter/s]
Best score: 0.5871: : 212iter [00:11, 22.13iter/s]
Best score: 0.5871: : 213iter [00:11, 22.13iter/s]
Best score: 0.5871: : 214iter [00:11, 22.31iter/s]
Best score: 0.5871: : 214iter [00:11, 22.31iter/s]
Best score: 0.5871: : 215iter [00:11, 22.31iter/s]
Best score: 0.5871: : 216iter [00:11, 22.31iter/s]
Best score: 0.5871: : 217iter [00:11, 22.37iter/s]
Best score: 0.5871: : 217iter [00:11, 22.37iter/s]
Best score: 0.5871: : 218iter [00:11, 22.37iter/s]
Best score: 0.5094: : 219iter [00:11, 22.37iter/s]
Best score: 0.5094: : 220iter [00:11, 22.23iter/s]
Best score: 0.5094: : 220iter [00:11, 22.23iter/s]
Best score: 0.5094: : 221iter [00:11, 22.23iter/s]
Best score: 0.5094: : 222iter [00:11, 22.23iter/s]
Best score: 0.5094: : 223iter [00:11, 22.35iter/s]
Best score: 0.5094: : 223iter [00:11, 22.35iter/s]
Best score: 0.5094: : 224iter [00:11, 22.35iter/s]
Best score: 0.5094: : 225iter [00:12, 22.35iter/s]
Best score: 0.5094: : 226iter [00:12, 22.41iter/s]
Best score: 0.5094: : 226iter [00:12, 22.41iter/s]
Best score: 0.5094: : 227iter [00:12, 22.41iter/s]
Best score: 0.5094: : 228iter [00:12, 22.41iter/s]
Best score: 0.5094: : 229iter [00:12, 22.52iter/s]
Best score: 0.5094: : 229iter [00:12, 22.52iter/s]
Best score: 0.5094: : 230iter [00:12, 22.52iter/s]
Best score: 0.5094: : 231iter [00:12, 22.52iter/s]
Best score: 0.5094: : 232iter [00:12, 22.35iter/s]
Best score: 0.5094: : 232iter [00:12, 22.35iter/s]
Best score: 0.5094: : 233iter [00:12, 22.35iter/s]
Best score: 0.5094: : 234iter [00:12, 22.35iter/s]
Best score: 0.5094: : 235iter [00:12, 22.40iter/s]
Best score: 0.5094: : 235iter [00:12, 22.40iter/s]
Best score: 0.5094: : 236iter [00:12, 22.40iter/s]
Best score: 0.5094: : 237iter [00:12, 22.40iter/s]
Best score: 0.5094: : 238iter [00:12, 22.51iter/s]
Best score: 0.5094: : 238iter [00:12, 22.51iter/s]
Best score: 0.4694: : 239iter [00:12, 22.51iter/s]
Best score: 0.4694: : 240iter [00:12, 22.51iter/s]
Best score: 0.4694: : 241iter [00:12, 22.31iter/s]
Best score: 0.4694: : 241iter [00:12, 22.31iter/s]
Best score: 0.4694: : 242iter [00:12, 22.31iter/s]
Best score: 0.4694: : 243iter [00:12, 22.31iter/s]
Best score: 0.4694: : 244iter [00:12, 22.37iter/s]
Best score: 0.4694: : 244iter [00:12, 22.37iter/s]
Best score: 0.4694: : 245iter [00:12, 22.37iter/s]
Best score: 0.4694: : 246iter [00:12, 22.37iter/s]
Best score: 0.4694: : 247iter [00:12, 22.41iter/s]
Best score: 0.4694: : 247iter [00:13, 22.41iter/s]
Best score: 0.4694: : 248iter [00:13, 22.41iter/s]
[ITER 250] Best: 0.4694
[PARAMS] Current best parameters:
  fx: 535.2037
  fy: 534.5061
  px: 997.1329
  py: 760.8711
  k1: -0.00019753
  k2: -0.00613956
  k3: 0.00500380
  k4: -0.00174192
  p1: -0.00727459
  p2: -0.00265947
  p3: 0.00901835
  p4: -0.00037924
  scale: 2.9914
  rotation: 0.2107

Best score: 0.4694: : 249iter [00:13, 22.41iter/s]
Best score: 0.4694: : 250iter [00:13, 22.23iter/s]
Best score: 0.4694: : 250iter [00:13, 22.23iter/s]
Best score: 0.4694: : 251iter [00:13, 22.23iter/s]
Best score: 0.4694: : 252iter [00:13, 22.23iter/s]
Best score: 0.4694: : 253iter [00:13, 22.30iter/s]
Best score: 0.4694: : 253iter [00:13, 22.30iter/s]
Best score: 0.4694: : 254iter [00:13, 22.30iter/s]
Best score: 0.4694: : 255iter [00:13, 22.30iter/s]
Best score: 0.4694: : 256iter [00:13, 22.33iter/s]
Best score: 0.4694: : 256iter [00:13, 22.33iter/s]
Best score: 0.4694: : 257iter [00:13, 22.33iter/s]
Best score: 0.4694: : 258iter [00:13, 22.33iter/s]
Best score: 0.4694: : 259iter [00:13, 22.38iter/s]
Best score: 0.4660: : 259iter [00:13, 22.38iter/s]
Best score: 0.4660: : 260iter [00:13, 22.38iter/s]
Best score: 0.4660: : 261iter [00:13, 22.38iter/s]
Best score: 0.4660: : 262iter [00:13, 22.21iter/s]
Best score: 0.4660: : 262iter [00:13, 22.21iter/s]
Best score: 0.4660: : 263iter [00:13, 22.21iter/s]
Best score: 0.4660: : 264iter [00:13, 22.21iter/s]
Best score: 0.4660: : 265iter [00:13, 22.36iter/s]
Best score: 0.4660: : 265iter [00:13, 22.36iter/s]
Best score: 0.4660: : 266iter [00:13, 22.36iter/s]
Best score: 0.4660: : 267iter [00:13, 22.36iter/s]
Best score: 0.4660: : 268iter [00:13, 22.46iter/s]
Best score: 0.4660: : 268iter [00:13, 22.46iter/s]
Best score: 0.4558: : 269iter [00:14, 22.46iter/s]
Best score: 0.4558: : 270iter [00:14, 22.46iter/s]
Best score: 0.4558: : 271iter [00:14, 22.25iter/s]
Best score: 0.4558: : 271iter [00:14, 22.25iter/s]
Best score: 0.4558: : 272iter [00:14, 22.25iter/s]
Best score: 0.4558: : 273iter [00:14, 22.25iter/s]
Best score: 0.4558: : 274iter [00:14, 22.38iter/s]
Best score: 0.4558: : 274iter [00:14, 22.38iter/s]
Best score: 0.4558: : 275iter [00:14, 22.38iter/s]
Best score: 0.4558: : 276iter [00:14, 22.38iter/s]
Best score: 0.4558: : 277iter [00:14, 22.46iter/s]
Best score: 0.4558: : 277iter [00:14, 22.46iter/s]
Best score: 0.4558: : 278iter [00:14, 22.46iter/s]
Best score: 0.4190: : 279iter [00:14, 22.46iter/s]
Best score: 0.4190: : 280iter [00:14, 22.22iter/s]
Best score: 0.4190: : 280iter [00:14, 22.22iter/s]
Best score: 0.4190: : 281iter [00:14, 22.22iter/s]
Best score: 0.4190: : 282iter [00:14, 22.22iter/s]
Best score: 0.4190: : 283iter [00:14, 22.33iter/s]
Best score: 0.4190: : 283iter [00:14, 22.33iter/s]
Best score: 0.4190: : 284iter [00:14, 22.33iter/s]
Best score: 0.4190: : 285iter [00:14, 22.33iter/s]
Best score: 0.4190: : 286iter [00:14, 22.42iter/s]
Best score: 0.4190: : 286iter [00:14, 22.42iter/s]
Best score: 0.4190: : 287iter [00:14, 22.42iter/s]
Best score: 0.4190: : 288iter [00:14, 22.42iter/s]
Best score: 0.4190: : 289iter [00:14, 22.43iter/s]
Best score: 0.4086: : 289iter [00:14, 22.43iter/s]
Best score: 0.4086: : 290iter [00:14, 22.43iter/s]
Best score: 0.4086: : 291iter [00:14, 22.43iter/s]
Best score: 0.4086: : 292iter [00:14, 22.23iter/s]
Best score: 0.4086: : 292iter [00:15, 22.23iter/s]
Best score: 0.4086: : 293iter [00:15, 22.23iter/s]
Best score: 0.4086: : 294iter [00:15, 22.23iter/s]
Best score: 0.4086: : 295iter [00:15, 22.31iter/s]
Best score: 0.4086: : 295iter [00:15, 22.31iter/s]
Best score: 0.4086: : 296iter [00:15, 22.31iter/s]
Best score: 0.4086: : 297iter [00:15, 22.31iter/s]
Best score: 0.4086: : 298iter [00:15, 22.34iter/s]
Best score: 0.4086: : 298iter [00:15, 22.34iter/s]
[ITER 300] Best: 0.4003
[PARAMS] Current best parameters:
  fx: 528.2945
  fy: 527.8294
  px: 996.8531
  py: 760.4575
  k1: 0.01751607
  k2: -0.01465478
  k3: 0.00584308
  k4: -0.00145796
  p1: -0.00818231
  p2: -0.00333704
  p3: 0.00831049
  p4: 0.00019966
  scale: 2.9669
  rotation: 0.1974

Best score: 0.4003: : 299iter [00:15, 22.34iter/s]
Best score: 0.4003: : 300iter [00:15, 22.34iter/s]
Best score: 0.4003: : 301iter [00:15, 22.11iter/s]
Best score: 0.4003: : 301iter [00:15, 22.11iter/s]
Best score: 0.4003: : 302iter [00:15, 22.11iter/s]
Best score: 0.4003: : 303iter [00:15, 22.11iter/s]
Best score: 0.4003: : 304iter [00:15, 22.21iter/s]
Best score: 0.4003: : 304iter [00:15, 22.21iter/s]
Best score: 0.4003: : 305iter [00:15, 22.21iter/s]
Best score: 0.4003: : 306iter [00:15, 22.21iter/s]
Best score: 0.4003: : 307iter [00:15, 22.28iter/s]
Best score: 0.4003: : 307iter [00:15, 22.28iter/s]
Best score: 0.4003: : 308iter [00:15, 22.28iter/s]
Best score: 0.3877: : 309iter [00:15, 22.28iter/s]
Best score: 0.3877: : 310iter [00:15, 22.07iter/s]
Best score: 0.3877: : 310iter [00:15, 22.07iter/s]
Best score: 0.3877: : 311iter [00:15, 22.07iter/s]
Best score: 0.3877: : 312iter [00:15, 22.07iter/s]
Best score: 0.3877: : 313iter [00:15, 22.25iter/s]
Best score: 0.3877: : 313iter [00:15, 22.25iter/s]
Best score: 0.3877: : 314iter [00:16, 22.25iter/s]
Best score: 0.3877: : 315iter [00:16, 22.25iter/s]
Best score: 0.3877: : 316iter [00:16, 22.36iter/s]
Best score: 0.3877: : 316iter [00:16, 22.36iter/s]
Best score: 0.3877: : 317iter [00:16, 22.36iter/s]
Best score: 0.3877: : 318iter [00:16, 22.36iter/s]
Best score: 0.3877: : 319iter [00:16, 22.41iter/s]
Best score: 0.3843: : 319iter [00:16, 22.41iter/s]
Best score: 0.3843: : 320iter [00:16, 22.41iter/s]
Best score: 0.3843: : 321iter [00:16, 22.41iter/s]
Best score: 0.3843: : 322iter [00:16, 22.20iter/s]
Best score: 0.3843: : 322iter [00:16, 22.20iter/s]
Best score: 0.3843: : 323iter [00:16, 22.20iter/s]
Best score: 0.3843: : 324iter [00:16, 22.20iter/s]
Best score: 0.3843: : 325iter [00:16, 22.28iter/s]
Best score: 0.3843: : 325iter [00:16, 22.28iter/s]
Best score: 0.3843: : 326iter [00:16, 22.28iter/s]
Best score: 0.3843: : 327iter [00:16, 22.28iter/s]
Best score: 0.3843: : 328iter [00:16, 22.30iter/s]
Best score: 0.3843: : 328iter [00:16, 22.30iter/s]
Best score: 0.3838: : 329iter [00:16, 22.30iter/s]
Best score: 0.3838: : 330iter [00:16, 22.30iter/s]
Best score: 0.3838: : 331iter [00:16, 22.15iter/s]
Best score: 0.3838: : 331iter [00:16, 22.15iter/s]
Best score: 0.3838: : 332iter [00:16, 22.15iter/s]
Best score: 0.3838: : 333iter [00:16, 22.15iter/s]
Best score: 0.3838: : 334iter [00:16, 22.25iter/s]
Best score: 0.3838: : 334iter [00:16, 22.25iter/s]
Best score: 0.3838: : 335iter [00:16, 22.25iter/s]
Best score: 0.3838: : 336iter [00:17, 22.25iter/s]
Best score: 0.3838: : 337iter [00:17, 22.31iter/s]
Best score: 0.3838: : 337iter [00:17, 22.31iter/s]
Best score: 0.3838: : 338iter [00:17, 22.31iter/s]
Best score: 0.3815: : 339iter [00:17, 22.31iter/s]
Best score: 0.3815: : 340iter [00:17, 22.18iter/s]
Best score: 0.3815: : 340iter [00:17, 22.18iter/s]
Best score: 0.3815: : 341iter [00:17, 22.18iter/s]
Best score: 0.3815: : 342iter [00:17, 22.18iter/s]
Best score: 0.3815: : 343iter [00:17, 22.32iter/s]
Best score: 0.3815: : 343iter [00:17, 22.32iter/s]
Best score: 0.3815: : 344iter [00:17, 22.32iter/s]
Best score: 0.3815: : 345iter [00:17, 22.32iter/s]
Best score: 0.3815: : 346iter [00:17, 22.28iter/s]
Best score: 0.3815: : 346iter [00:17, 22.28iter/s]
Best score: 0.3815: : 347iter [00:17, 22.28iter/s]
Best score: 0.3815: : 348iter [00:17, 22.28iter/s]
Best score: 0.3815: : 349iter [00:17, 22.33iter/s]
[ITER 350] Best: 0.3800
[PARAMS] Current best parameters:
  fx: 528.6429
  fy: 528.2113
  px: 996.5023
  py: 760.0835
  k1: 0.02189856
  k2: -0.01927499
  k3: 0.00740547
  k4: -0.00165082
  p1: -0.00896837
  p2: -0.00415531
  p3: 0.00947193
  p4: -0.00019791
  scale: 2.9558
  rotation: 0.2267

Best score: 0.3800: : 349iter [00:17, 22.33iter/s]
Best score: 0.3800: : 350iter [00:17, 22.33iter/s]
Best score: 0.3800: : 351iter [00:17, 22.33iter/s]
Best score: 0.3800: : 352iter [00:17, 22.13iter/s]
Best score: 0.3800: : 352iter [00:17, 22.13iter/s]
Best score: 0.3800: : 353iter [00:17, 22.13iter/s]
Best score: 0.3800: : 354iter [00:17, 22.13iter/s]
Best score: 0.3800: : 355iter [00:17, 22.21iter/s]
Best score: 0.3800: : 355iter [00:17, 22.21iter/s]
Best score: 0.3800: : 356iter [00:17, 22.21iter/s]
Best score: 0.3800: : 357iter [00:17, 22.21iter/s]
Best score: 0.3800: : 358iter [00:17, 22.26iter/s]
Best score: 0.3800: : 358iter [00:18, 22.26iter/s]
Best score: 0.3800: : 359iter [00:18, 22.26iter/s]
Best score: 0.3800: : 360iter [00:18, 22.26iter/s]
Best score: 0.3800: : 361iter [00:18, 22.15iter/s]
Best score: 0.3800: : 361iter [00:18, 22.15iter/s]
Best score: 0.3800: : 362iter [00:18, 22.15iter/s]
Best score: 0.3800: : 363iter [00:18, 22.15iter/s]
Best score: 0.3800: : 364iter [00:18, 22.32iter/s]
Best score: 0.3800: : 364iter [00:18, 22.32iter/s]
Best score: 0.3800: : 365iter [00:18, 22.32iter/s]
Best score: 0.3800: : 366iter [00:18, 22.32iter/s]
Best score: 0.3800: : 367iter [00:18, 22.44iter/s]
Best score: 0.3800: : 367iter [00:18, 22.44iter/s]
Best score: 0.3800: : 368iter [00:18, 22.44iter/s]
Best score: 0.3769: : 369iter [00:18, 22.44iter/s]
Best score: 0.3769: : 370iter [00:18, 22.28iter/s]
Best score: 0.3769: : 370iter [00:18, 22.28iter/s]
Best score: 0.3769: : 371iter [00:18, 22.28iter/s]
Best score: 0.3769: : 372iter [00:18, 22.28iter/s]
Best score: 0.3769: : 373iter [00:18, 22.44iter/s]
Best score: 0.3769: : 373iter [00:18, 22.44iter/s]
Best score: 0.3769: : 374iter [00:18, 22.44iter/s]
Best score: 0.3769: : 375iter [00:18, 22.44iter/s]
Best score: 0.3769: : 376iter [00:18, 22.61iter/s]
Best score: 0.3769: : 376iter [00:18, 22.61iter/s]
Best score: 0.3769: : 377iter [00:18, 22.61iter/s]
Best score: 0.3769: : 378iter [00:18, 22.61iter/s]
Best score: 0.3769: : 379iter [00:18, 22.70iter/s]
Best score: 0.3756: : 379iter [00:18, 22.70iter/s]
Best score: 0.3756: : 380iter [00:18, 22.70iter/s]
Best score: 0.3756: : 381iter [00:19, 22.70iter/s]
Best score: 0.3756: : 382iter [00:19, 22.52iter/s]
Best score: 0.3756: : 382iter [00:19, 22.52iter/s]
Best score: 0.3756: : 383iter [00:19, 22.52iter/s]
Best score: 0.3756: : 384iter [00:19, 22.52iter/s]
Best score: 0.3756: : 385iter [00:19, 22.65iter/s]
Best score: 0.3756: : 385iter [00:19, 22.65iter/s]
Best score: 0.3756: : 386iter [00:19, 22.65iter/s]
Best score: 0.3756: : 387iter [00:19, 22.65iter/s]
Best score: 0.3756: : 388iter [00:19, 22.62iter/s]
Best score: 0.3756: : 388iter [00:19, 22.62iter/s]
Best score: 0.3756: : 389iter [00:19, 22.62iter/s]
Best score: 0.3756: : 390iter [00:19, 22.62iter/s]
Best score: 0.3756: : 391iter [00:19, 22.41iter/s]
Best score: 0.3756: : 391iter [00:19, 22.41iter/s]
Best score: 0.3756: : 392iter [00:19, 22.41iter/s]
Best score: 0.3756: : 393iter [00:19, 22.41iter/s]
Best score: 0.3756: : 394iter [00:19, 22.48iter/s]
Best score: 0.3756: : 394iter [00:19, 22.48iter/s]
Best score: 0.3756: : 395iter [00:19, 22.48iter/s]
Best score: 0.3756: : 396iter [00:19, 22.48iter/s]
Best score: 0.3756: : 397iter [00:19, 22.47iter/s]
Best score: 0.3756: : 397iter [00:19, 22.47iter/s]
Best score: 0.3756: : 398iter [00:19, 22.47iter/s]
[ITER 400] Best: 0.3756
[PARAMS] Current best parameters:
  fx: 529.4942
  fy: 529.0077
  px: 996.1178
  py: 759.6819
  k1: 0.02000620
  k2: -0.01879844
  k3: 0.00764666
  k4: -0.00175533
  p1: -0.00995555
  p2: -0.00510379
  p3: 0.00999570
  p4: -0.00016532
  scale: 2.9589
  rotation: 0.2203

Best score: 0.3756: : 399iter [00:19, 22.47iter/s]
Best score: 0.3756: : 400iter [00:19, 22.24iter/s]
Best score: 0.3756: : 400iter [00:19, 22.24iter/s]
Best score: 0.3756: : 401iter [00:19, 22.24iter/s]
Best score: 0.3756: : 402iter [00:19, 22.24iter/s]
Best score: 0.3756: : 403iter [00:19, 22.34iter/s]
Best score: 0.3756: : 403iter [00:20, 22.34iter/s]
Best score: 0.3756: : 404iter [00:20, 22.34iter/s]
Best score: 0.3756: : 405iter [00:20, 22.34iter/s]
Best score: 0.3756: : 406iter [00:20, 22.39iter/s]
Best score: 0.3756: : 406iter [00:20, 22.39iter/s]
Best score: 0.3756: : 407iter [00:20, 22.39iter/s]
Best score: 0.3756: : 408iter [00:20, 22.39iter/s]
Best score: 0.3756: : 409iter [00:20, 22.50iter/s]
Best score: 0.3749: : 409iter [00:20, 22.50iter/s]
Best score: 0.3749: : 410iter [00:20, 22.50iter/s]
Best score: 0.3749: : 411iter [00:20, 22.50iter/s]
Best score: 0.3749: : 412iter [00:20, 22.29iter/s]
Best score: 0.3749: : 412iter [00:20, 22.29iter/s]
Best score: 0.3749: : 413iter [00:20, 22.29iter/s]
Best score: 0.3749: : 414iter [00:20, 22.29iter/s]
Best score: 0.3749: : 415iter [00:20, 22.41iter/s]
Best score: 0.3749: : 415iter [00:20, 22.41iter/s]
Best score: 0.3749: : 416iter [00:20, 22.41iter/s]
Best score: 0.3749: : 417iter [00:20, 22.41iter/s]
Best score: 0.3749: : 418iter [00:20, 22.44iter/s]
Best score: 0.3749: : 418iter [00:20, 22.44iter/s]
Best score: 0.3745: : 419iter [00:20, 22.44iter/s]
Best score: 0.3745: : 420iter [00:20, 22.44iter/s]
Best score: 0.3745: : 421iter [00:20, 22.26iter/s]
Best score: 0.3745: : 421iter [00:20, 22.26iter/s]
Best score: 0.3745: : 422iter [00:20, 22.26iter/s]
Best score: 0.3745: : 423iter [00:20, 22.26iter/s]
Best score: 0.3745: : 424iter [00:20, 22.44iter/s]
Best score: 0.3745: : 424iter [00:20, 22.44iter/s]
Best score: 0.3745: : 425iter [00:20, 22.44iter/s]
Best score: 0.3745: : 426iter [00:21, 22.44iter/s]
Best score: 0.3745: : 427iter [00:21, 22.51iter/s]
Best score: 0.3745: : 427iter [00:21, 22.51iter/s]
Best score: 0.3745: : 428iter [00:21, 22.51iter/s]
Best score: 0.3744: : 429iter [00:21, 22.51iter/s]
Best score: 0.3744: : 430iter [00:21, 22.36iter/s]
Best score: 0.3744: : 430iter [00:21, 22.36iter/s]
Best score: 0.3744: : 431iter [00:21, 22.36iter/s]
Best score: 0.3744: : 432iter [00:21, 22.36iter/s]
Best score: 0.3744: : 433iter [00:21, 22.48iter/s]
Best score: 0.3744: : 433iter [00:21, 22.48iter/s]
Best score: 0.3744: : 434iter [00:21, 22.48iter/s]
Best score: 0.3744: : 435iter [00:21, 22.48iter/s]
Best score: 0.3744: : 436iter [00:21, 22.55iter/s]
Best score: 0.3744: : 436iter [00:21, 22.55iter/s]
Best score: 0.3744: : 437iter [00:21, 22.55iter/s]
Best score: 0.3744: : 438iter [00:21, 22.55iter/s]
Best score: 0.3744: : 439iter [00:21, 22.62iter/s]
Best score: 0.3742: : 439iter [00:21, 22.62iter/s]
Best score: 0.3742: : 440iter [00:21, 22.62iter/s]
Best score: 0.3742: : 441iter [00:21, 22.62iter/s]
Best score: 0.3742: : 442iter [00:21, 22.44iter/s]
Best score: 0.3742: : 442iter [00:21, 22.44iter/s]
Best score: 0.3742: : 443iter [00:21, 22.44iter/s]
Best score: 0.3742: : 444iter [00:21, 22.44iter/s]
Best score: 0.3742: : 445iter [00:21, 22.55iter/s]
Best score: 0.3742: : 445iter [00:21, 22.55iter/s]
Best score: 0.3742: : 446iter [00:21, 22.55iter/s]
Best score: 0.3742: : 447iter [00:22, 22.55iter/s]
Best score: 0.3742: : 448iter [00:22, 18.50iter/s]
Best score: 0.3742: : 448iter [00:22, 18.50iter/s]
[ITER 450] Best: 0.3735
[PARAMS] Current best parameters:
  fx: 530.1128
  fy: 529.6366
  px: 996.1863
  py: 759.7171
  k1: 0.01986231
  k2: -0.01867516
  k3: 0.00724312
  k4: -0.00162555
  p1: -0.00991568
  p2: -0.00491484
  p3: 0.00993362
  p4: -0.00019344
  scale: 2.9564
  rotation: 0.2177

Best score: 0.3735: : 449iter [00:22, 18.50iter/s]
Best score: 0.3735: : 450iter [00:22, 18.50iter/s]
Best score: 0.3735: : 451iter [00:22, 19.42iter/s]
Best score: 0.3735: : 451iter [00:22, 19.42iter/s]
Best score: 0.3735: : 452iter [00:22, 19.42iter/s]
Best score: 0.3735: : 453iter [00:22, 19.42iter/s]
Best score: 0.3735: : 454iter [00:22, 20.27iter/s]
Best score: 0.3735: : 454iter [00:22, 20.27iter/s]
Best score: 0.3735: : 455iter [00:22, 20.27iter/s]
Best score: 0.3735: : 456iter [00:22, 20.27iter/s]
Best score: 0.3735: : 457iter [00:22, 20.89iter/s]
Best score: 0.3735: : 457iter [00:22, 20.89iter/s]
Best score: 0.3735: : 458iter [00:22, 20.89iter/s]
Best score: 0.3735: : 459iter [00:22, 20.89iter/s]
Best score: 0.3735: : 460iter [00:22, 21.09iter/s]
Best score: 0.3735: : 460iter [00:22, 21.09iter/s]
Best score: 0.3735: : 461iter [00:22, 21.09iter/s]
Best score: 0.3735: : 462iter [00:22, 21.09iter/s]
Best score: 0.3735: : 463iter [00:22, 21.49iter/s]
Best score: 0.3735: : 463iter [00:22, 21.49iter/s]
Best score: 0.3735: : 464iter [00:22, 21.49iter/s]
Best score: 0.3735: : 465iter [00:22, 21.49iter/s]
Best score: 0.3735: : 466iter [00:22, 21.83iter/s]
Best score: 0.3735: : 466iter [00:22, 21.83iter/s]
Best score: 0.3735: : 467iter [00:22, 21.83iter/s]
Best score: 0.3735: : 468iter [00:22, 21.83iter/s]
Best score: 0.3735: : 469iter [00:22, 22.04iter/s]
Best score: 0.3733: : 469iter [00:23, 22.04iter/s]
Best score: 0.3733: : 470iter [00:23, 22.04iter/s]
Best score: 0.3733: : 471iter [00:23, 22.04iter/s]
Best score: 0.3733: : 472iter [00:23, 21.99iter/s]
Best score: 0.3733: : 472iter [00:23, 21.99iter/s]
Best score: 0.3733: : 473iter [00:23, 21.99iter/s]
Best score: 0.3733: : 474iter [00:23, 21.99iter/s]
Best score: 0.3733: : 475iter [00:23, 22.12iter/s]
Best score: 0.3733: : 475iter [00:23, 22.12iter/s]
Best score: 0.3733: : 476iter [00:23, 22.12iter/s]
Best score: 0.3733: : 477iter [00:23, 22.12iter/s]
Best score: 0.3733: : 478iter [00:23, 22.26iter/s]
Best score: 0.3733: : 478iter [00:23, 22.26iter/s]
Best score: 0.3726: : 479iter [00:23, 22.26iter/s]
Best score: 0.3726: : 480iter [00:23, 22.26iter/s]
Best score: 0.3726: : 481iter [00:23, 22.15iter/s]
Best score: 0.3726: : 481iter [00:23, 22.15iter/s]
Best score: 0.3726: : 482iter [00:23, 22.15iter/s]
Best score: 0.3726: : 483iter [00:23, 22.15iter/s]
Best score: 0.3726: : 484iter [00:23, 22.29iter/s]
Best score: 0.3726: : 484iter [00:23, 22.29iter/s]
Best score: 0.3726: : 485iter [00:23, 22.29iter/s]
Best score: 0.3726: : 486iter [00:23, 22.29iter/s]
Best score: 0.3726: : 487iter [00:23, 22.35iter/s]
Best score: 0.3726: : 487iter [00:23, 22.35iter/s]
Best score: 0.3726: : 488iter [00:23, 22.35iter/s]
Best score: 0.3719: : 489iter [00:23, 22.35iter/s]
Best score: 0.3719: : 490iter [00:23, 22.18iter/s]
Best score: 0.3719: : 490iter [00:23, 22.18iter/s]
Best score: 0.3719: : 491iter [00:24, 22.18iter/s]
Best score: 0.3719: : 492iter [00:24, 22.18iter/s]
Best score: 0.3719: : 493iter [00:24, 22.31iter/s]
Best score: 0.3719: : 493iter [00:24, 22.31iter/s]
Best score: 0.3719: : 494iter [00:24, 22.31iter/s]
Best score: 0.3719: : 495iter [00:24, 22.31iter/s]
Best score: 0.3719: : 496iter [00:24, 22.41iter/s]
Best score: 0.3719: : 496iter [00:24, 22.41iter/s]
Best score: 0.3719: : 497iter [00:24, 22.41iter/s]
Best score: 0.3719: : 498iter [00:24, 22.41iter/s]
Best score: 0.3719: : 499iter [00:24, 22.42iter/s]
[ITER 500] Best: 0.3717
[PARAMS] Current best parameters:
  fx: 522.9545
  fy: 522.4998
  px: 996.0401
  py: 759.6720
  k1: 0.01506150
  k2: -0.00027787
  k3: -0.00319593
  k4: 0.00034219
  p1: -0.00992336
  p2: -0.00520770
  p3: 0.00999919
  p4: -0.00017193
  scale: 2.9709
  rotation: 0.2192

Best score: 0.3717: : 499iter [00:24, 22.42iter/s]
Best score: 0.3717: : 500iter [00:24, 20.50iter/s]

[📈] Running L-BFGS-B polish after 500 DE iterations...
  Polish improved score: 0.371741 -> 0.371319
  Success: True
  Tangential distortion: p1=-0.009942, p2=-0.005187, p3=0.010000, p4=-0.000169
  ✓ Tangential correction is significant for corner improvement
[✅] Square reference optimization complete. Score: 0.3713
[✅] Parameters copied to: /working/MDC102_W039_2025-08-29/calibration/params.json
[📌] Selecting best parameters...
[✅] Saved final refined parameters.


-------------------------------------------------------------------
                        Step 3: Undistortion                       
-------------------------------------------------------------------


[DEBUG] Parameters being applied to PTD conversion:
    fx: 522.9544818184715
    fy: 522.4997699927152
    px: 996.0401396936945
    py: 759.6719713518529
    k1: 0.015061244911094434
    k2: -0.00027465230134462727
    k3: -0.0031934662389700784
    k4: 0.0003386902513743419
    p1: -0.009942469975180716
    p2: -0.00518672384242054
    p3: 0.01
    p4: -0.00016874546990622625
    scale: 2.9710511005945928
    rotation: 0.21923026261704132
    mmpp: 1.2683584512278088
    nmpp: 1268358.4512278088

[🔄] Converting 412 frames to PTD, creating debug images for 200 calibration frames...

📁 Rigs:   0%|          | 0/2 [00:00<?, ?rig/s]

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   🔄 1000:  96%|█████████▌| 199/208 [00:01<00:00, 176.00frame/s]

                                                                 
📁 Rigs:  50%|█████     | 1/2 [00:02<00:02,  2.18s/rig]

   🔄 500:   0%|          | 0/204 [00:00<?, ?frame/s]

   🔄 500:   9%|▉         | 18/204 [00:00<00:01, 177.25frame/s]

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   🔄 500:  71%|███████   | 145/204 [00:00<00:00, 178.06frame/s]

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   🔄 500:  98%|█████████▊| 199/204 [00:01<00:00, 175.79frame/s]

                                                                
📁 Rigs: 100%|██████████| 2/2 [00:04<00:00,  2.18s/rig]
📁 Rigs: 100%|██████████| 2/2 [00:04<00:00,  2.18s/rig]
[✅] Saved PTDs: /working/MDC102_W039_2025-08-29/calibration/debug/3_undistorted/output/ptd

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📁 Rigs:  50%|█████     | 1/2 [00:00<00:00,  1.10rig/s]

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   🔄 500:  72%|███████▏  | 72/100 [00:00<00:00, 174.82frame/s]

   🔄 500:  90%|█████████ | 90/100 [00:00<00:00, 175.86frame/s]

                                                               
📁 Rigs: 100%|██████████| 2/2 [00:01<00:00,  1.01rig/s]
📁 Rigs: 100%|██████████| 2/2 [00:01<00:00,  1.02rig/s]
[✅] Saved PTDs: /working/MDC102_W039_2025-08-29/calibration/debug/3_undistorted/temp_ptd
[WARN] No .tfd files found for serial extraction
[WARN] Failed to extract serial number from .tfd file. Check that .tfd files exist and contain 'LASERbidh' or 'LASERbidg' pattern. Using 'unknown' as fallback.

📤 Writing LUT:   0%|          | 0/3080448 [00:00<?, ?px/s]
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📤 Writing LUT:  14%|█▍        | 429048/3080448 [00:00<00:03, 867240.64px/s]
📤 Writing LUT:  17%|█▋        | 517105/3080448 [00:00<00:02, 871769.37px/s]
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📤 Writing LUT:  22%|██▏       | 691047/3080448 [00:00<00:02, 864892.42px/s]
📤 Writing LUT:  25%|██▌       | 778479/3080448 [00:00<00:02, 867824.96px/s]
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📤 Writing LUT:  51%|█████     | 1561912/3080448 [00:01<00:01, 876895.61px/s]
📤 Writing LUT:  54%|█████▎    | 1649673/3080448 [00:01<00:01, 877108.25px/s]
📤 Writing LUT:  56%|█████▋    | 1737388/3080448 [00:02<00:01, 873717.52px/s]
📤 Writing LUT:  59%|█████▉    | 1824927/3080448 [00:02<00:01, 874216.85px/s]
📤 Writing LUT:  62%|██████▏   | 1912503/3080448 [00:02<00:01, 874678.51px/s]
📤 Writing LUT:  65%|██████▍   | 1999975/3080448 [00:02<00:01, 874689.31px/s]
📤 Writing LUT:  68%|██████▊   | 2087694/3080448 [00:02<00:01, 875438.41px/s]
📤 Writing LUT:  71%|███████   | 2176518/3080448 [00:02<00:01, 879274.64px/s]
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📤 Writing LUT:  76%|███████▋  | 2352384/3080448 [00:02<00:00, 876935.42px/s]
📤 Writing LUT:  79%|███████▉  | 2440080/3080448 [00:02<00:00, 871682.09px/s]
📤 Writing LUT:  82%|████████▏ | 2527256/3080448 [00:02<00:00, 870652.94px/s]
📤 Writing LUT:  85%|████████▍ | 2614752/3080448 [00:03<00:00, 871937.20px/s]
📤 Writing LUT:  88%|████████▊ | 2703739/3080448 [00:03<00:00, 877297.81px/s]
📤 Writing LUT:  91%|█████████ | 2792230/3080448 [00:03<00:00, 879574.41px/s]
📤 Writing LUT:  94%|█████████▎| 2880365/3080448 [00:03<00:00, 880105.20px/s]
📤 Writing LUT:  96%|█████████▋| 2968379/3080448 [00:03<00:00, 878731.61px/s]
📤 Writing LUT:  99%|█████████▉| 3056258/3080448 [00:03<00:00, 878745.58px/s]
📤 Writing LUT: 100%|██████████| 3080448/3080448 [00:03<00:00, 870332.18px/s]
[✅] LUT written to: /working/MDC102_W039_2025-08-29/calibration/debug/3_undistorted/output/LUT.lut
[WARN] Folder name 'MDC102_W039_2025-08-29' does not match expected pattern MDC042_W007_5_28_2025. Using simple naming convention.
[✅] LUT copied to: /working/MDC102_W039_2025-08-29/calibration/MDC102_W039_2025-08-29_unknown.lut

-------------------------------------------------------------------
                          Step 4: Heatmap                          
-------------------------------------------------------------------


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   🔥 1000:  47%|████▋     | 98/208 [00:00<00:00, 156.86frame/s]

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   🔥 1000:  62%|██████▎   | 130/208 [00:00<00:00, 156.25frame/s]

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   🔥 1000:  94%|█████████▍| 195/208 [00:01<00:00, 158.96frame/s]

                                                                 [✅] 1000: /working/MDC102_W039_2025-08-29/calibration/debug/4_heatmap/1000_heatmap.png

📁 Rigs (heatmap):  50%|█████     | 1/2 [00:01<00:01,  1.93s/rig]

   🔥 500:   0%|          | 0/204 [00:00<?, ?frame/s]

   🔥 500:   8%|▊         | 16/204 [00:00<00:01, 155.33frame/s]

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   🔥 500:  24%|██▎       | 48/204 [00:00<00:00, 157.58frame/s]

   🔥 500:  31%|███▏      | 64/204 [00:00<00:00, 157.87frame/s]

   🔥 500:  40%|███▉      | 81/204 [00:00<00:00, 158.90frame/s]

   🔥 500:  48%|████▊     | 98/204 [00:00<00:00, 159.86frame/s]

   🔥 500:  56%|█████▋    | 115/204 [00:00<00:00, 160.09frame/s]

   🔥 500:  65%|██████▍   | 132/204 [00:00<00:00, 159.30frame/s]

   🔥 500:  73%|███████▎  | 148/204 [00:00<00:00, 158.81frame/s]

   🔥 500:  80%|████████  | 164/204 [00:01<00:00, 158.65frame/s]

   🔥 500:  88%|████████▊ | 180/204 [00:01<00:00, 158.74frame/s]

   🔥 500:  96%|█████████▌| 196/204 [00:01<00:00, 158.54frame/s]

                                                                [✅] 500: /working/MDC102_W039_2025-08-29/calibration/debug/4_heatmap/500_heatmap.png

📁 Rigs (heatmap): 100%|██████████| 2/2 [00:03<00:00,  1.82s/rig]
📁 Rigs (heatmap): 100%|██████████| 2/2 [00:03<00:00,  1.83s/rig]
[✅] all_rigs_average.png
[✅] all_rigs_best.png
[✅] Heatmaps saved to: /working/MDC102_W039_2025-08-29/calibration/debug/4_heatmap
[🏁] Finished processing MDC102_W039_2025-08-29


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