🟢 Starting Calibration Pipeline

=== Processing MDC101_W036_2025-12-31 ===

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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 1045 stationary frames, 204 remain


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→ 500 Phase 2: corners:  93%|█████████▎| 189/204 [03:03<00:13,  1.09it/s]

→ 500 Phase 2: corners:  93%|█████████▎| 190/204 [03:04<00:12,  1.11it/s]

→ 500 Phase 2: corners:  94%|█████████▎| 191/204 [03:05<00:11,  1.12it/s]

→ 500 Phase 2: corners:  94%|█████████▍| 192/204 [03:06<00:10,  1.14it/s]

→ 500 Phase 2: corners:  95%|█████████▍| 193/204 [03:06<00:09,  1.14it/s]

→ 500 Phase 2: corners:  95%|█████████▌| 194/204 [03:07<00:08,  1.15it/s]

→ 500 Phase 2: corners:  96%|█████████▌| 195/204 [03:08<00:07,  1.13it/s]

→ 500 Phase 2: corners:  96%|█████████▌| 196/204 [03:09<00:07,  1.13it/s]

→ 500 Phase 2: corners:  97%|█████████▋| 197/204 [03:10<00:06,  1.11it/s]

→ 500 Phase 2: corners:  97%|█████████▋| 198/204 [03:11<00:05,  1.10it/s]

→ 500 Phase 2: corners:  98%|█████████▊| 199/204 [03:12<00:04,  1.09it/s]

→ 500 Phase 2: corners:  98%|█████████▊| 200/204 [03:13<00:03,  1.07it/s]

→ 500 Phase 2: corners:  99%|█████████▊| 201/204 [03:14<00:02,  1.07it/s]

→ 500 Phase 2: corners:  99%|█████████▉| 202/204 [03:15<00:01,  1.04it/s]

→ 500 Phase 2: corners: 100%|█████████▉| 203/204 [03:16<00:00,  1.05it/s]

→ 500 Phase 2: corners: 100%|██████████| 204/204 [03:17<00:00,  1.06it/s]

                                                                         [PASS2] Summary: 0 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<00:17, 11.70it/s]

→ 500 Phase 3: finalize:   2%|▏         | 4/204 [00:00<00:16, 12.39it/s]

→ 500 Phase 3: finalize:   3%|▎         | 6/204 [00:00<00:15, 12.64it/s]

→ 500 Phase 3: finalize:   4%|▍         | 8/204 [00:00<00:15, 12.76it/s]

→ 500 Phase 3: finalize:   5%|▍         | 10/204 [00:00<00:15, 12.78it/s]

→ 500 Phase 3: finalize:   6%|▌         | 12/204 [00:00<00:14, 12.83it/s]

→ 500 Phase 3: finalize:   7%|▋         | 14/204 [00:01<00:14, 12.86it/s]

→ 500 Phase 3: finalize:   8%|▊         | 16/204 [00:01<00:14, 12.86it/s]

→ 500 Phase 3: finalize:   9%|▉         | 18/204 [00:01<00:14, 12.89it/s]

→ 500 Phase 3: finalize:  10%|▉         | 20/204 [00:01<00:14, 12.92it/s]

→ 500 Phase 3: finalize:  11%|█         | 22/204 [00:01<00:14, 12.92it/s]

→ 500 Phase 3: finalize:  12%|█▏        | 24/204 [00:01<00:13, 12.88it/s]

→ 500 Phase 3: finalize:  13%|█▎        | 26/204 [00:01<00:12, 13.88it/s]

→ 500 Phase 3: finalize:  14%|█▎        | 28/204 [00:02<00:12, 13.55it/s]

→ 500 Phase 3: finalize:  15%|█▍        | 30/204 [00:02<00:13, 13.32it/s]

→ 500 Phase 3: finalize:  16%|█▌        | 32/204 [00:02<00:13, 13.17it/s]

→ 500 Phase 3: finalize:  17%|█▋        | 34/204 [00:02<00:13, 13.00it/s]

→ 500 Phase 3: finalize:  18%|█▊        | 36/204 [00:02<00:13, 12.92it/s]

→ 500 Phase 3: finalize:  19%|█▊        | 38/204 [00:02<00:12, 12.84it/s]

→ 500 Phase 3: finalize:  20%|█▉        | 40/204 [00:03<00:12, 12.72it/s]

→ 500 Phase 3: finalize:  21%|██        | 42/204 [00:03<00:12, 12.61it/s]

→ 500 Phase 3: finalize:  22%|██▏       | 44/204 [00:03<00:12, 12.58it/s]

→ 500 Phase 3: finalize:  23%|██▎       | 46/204 [00:03<00:12, 12.54it/s]

→ 500 Phase 3: finalize:  24%|██▎       | 48/204 [00:03<00:12, 12.49it/s]

→ 500 Phase 3: finalize:  25%|██▍       | 50/204 [00:03<00:12, 12.43it/s]

→ 500 Phase 3: finalize:  25%|██▌       | 52/204 [00:04<00:12, 12.40it/s]

→ 500 Phase 3: finalize:  26%|██▋       | 54/204 [00:04<00:12, 12.39it/s]

→ 500 Phase 3: finalize:  27%|██▋       | 56/204 [00:04<00:11, 12.37it/s]

→ 500 Phase 3: finalize:  28%|██▊       | 58/204 [00:04<00:11, 12.38it/s]

→ 500 Phase 3: finalize:  29%|██▉       | 60/204 [00:04<00:11, 12.34it/s]

→ 500 Phase 3: finalize:  30%|███       | 62/204 [00:04<00:11, 12.32it/s]

→ 500 Phase 3: finalize:  31%|███▏      | 64/204 [00:05<00:11, 12.33it/s]

→ 500 Phase 3: finalize:  32%|███▏      | 66/204 [00:05<00:11, 12.30it/s]

→ 500 Phase 3: finalize:  33%|███▎      | 68/204 [00:05<00:11, 12.28it/s]

→ 500 Phase 3: finalize:  34%|███▍      | 70/204 [00:05<00:10, 12.25it/s]

→ 500 Phase 3: finalize:  35%|███▌      | 72/204 [00:05<00:10, 12.20it/s]

→ 500 Phase 3: finalize:  36%|███▋      | 74/204 [00:05<00:10, 12.20it/s]

→ 500 Phase 3: finalize:  37%|███▋      | 76/204 [00:06<00:10, 12.20it/s]

→ 500 Phase 3: finalize:  38%|███▊      | 78/204 [00:06<00:10, 12.21it/s]

→ 500 Phase 3: finalize:  39%|███▉      | 80/204 [00:06<00:10, 12.19it/s]

→ 500 Phase 3: finalize:  40%|████      | 82/204 [00:06<00:10, 12.16it/s]

→ 500 Phase 3: finalize:  41%|████      | 84/204 [00:06<00:09, 12.21it/s]

→ 500 Phase 3: finalize:  42%|████▏     | 86/204 [00:06<00:09, 12.26it/s]

→ 500 Phase 3: finalize:  43%|████▎     | 88/204 [00:07<00:09, 12.29it/s]

→ 500 Phase 3: finalize:  44%|████▍     | 90/204 [00:07<00:09, 12.29it/s]

→ 500 Phase 3: finalize:  45%|████▌     | 92/204 [00:07<00:09, 12.30it/s]

→ 500 Phase 3: finalize:  46%|████▌     | 94/204 [00:07<00:08, 12.37it/s]

→ 500 Phase 3: finalize:  47%|████▋     | 96/204 [00:07<00:08, 12.47it/s]

→ 500 Phase 3: finalize:  48%|████▊     | 98/204 [00:07<00:08, 12.59it/s]

→ 500 Phase 3: finalize:  49%|████▉     | 100/204 [00:07<00:08, 12.74it/s]

→ 500 Phase 3: finalize:  50%|█████     | 102/204 [00:08<00:07, 12.85it/s]

→ 500 Phase 3: finalize:  51%|█████     | 104/204 [00:08<00:07, 13.03it/s]

→ 500 Phase 3: finalize:  52%|█████▏    | 106/204 [00:08<00:07, 13.12it/s]

→ 500 Phase 3: finalize:  53%|█████▎    | 108/204 [00:08<00:07, 13.21it/s]

→ 500 Phase 3: finalize:  54%|█████▍    | 110/204 [00:08<00:07, 13.29it/s]

→ 500 Phase 3: finalize:  55%|█████▍    | 112/204 [00:08<00:06, 13.48it/s]

→ 500 Phase 3: finalize:  56%|█████▌    | 114/204 [00:08<00:06, 13.67it/s]

→ 500 Phase 3: finalize:  57%|█████▋    | 116/204 [00:09<00:06, 13.79it/s]

→ 500 Phase 3: finalize:  58%|█████▊    | 118/204 [00:09<00:06, 13.88it/s]

→ 500 Phase 3: finalize:  59%|█████▉    | 120/204 [00:09<00:06, 13.85it/s]

→ 500 Phase 3: finalize:  60%|█████▉    | 122/204 [00:09<00:05, 14.04it/s]

→ 500 Phase 3: finalize:  61%|██████    | 124/204 [00:09<00:05, 13.94it/s]

→ 500 Phase 3: finalize:  62%|██████▏   | 126/204 [00:09<00:05, 13.98it/s]

→ 500 Phase 3: finalize:  63%|██████▎   | 128/204 [00:09<00:05, 13.83it/s]

→ 500 Phase 3: finalize:  64%|██████▎   | 130/204 [00:10<00:05, 13.72it/s]

→ 500 Phase 3: finalize:  65%|██████▍   | 132/204 [00:10<00:05, 13.65it/s]

→ 500 Phase 3: finalize:  66%|██████▌   | 134/204 [00:10<00:05, 13.60it/s]

→ 500 Phase 3: finalize:  67%|██████▋   | 136/204 [00:10<00:05, 13.59it/s]

→ 500 Phase 3: finalize:  68%|██████▊   | 138/204 [00:10<00:04, 13.56it/s]

→ 500 Phase 3: finalize:  69%|██████▊   | 140/204 [00:10<00:04, 13.54it/s]

→ 500 Phase 3: finalize:  70%|██████▉   | 142/204 [00:11<00:04, 13.54it/s]

→ 500 Phase 3: finalize:  71%|███████   | 144/204 [00:11<00:04, 13.56it/s]

→ 500 Phase 3: finalize:  72%|███████▏  | 146/204 [00:11<00:04, 13.57it/s]

→ 500 Phase 3: finalize:  73%|███████▎  | 148/204 [00:11<00:04, 13.59it/s]

→ 500 Phase 3: finalize:  74%|███████▎  | 150/204 [00:11<00:03, 13.61it/s]

→ 500 Phase 3: finalize:  75%|███████▍  | 152/204 [00:11<00:03, 13.66it/s]

→ 500 Phase 3: finalize:  75%|███████▌  | 154/204 [00:11<00:03, 13.67it/s]

→ 500 Phase 3: finalize:  76%|███████▋  | 156/204 [00:12<00:03, 13.68it/s]

→ 500 Phase 3: finalize:  77%|███████▋  | 158/204 [00:12<00:03, 13.68it/s]

→ 500 Phase 3: finalize:  78%|███████▊  | 160/204 [00:12<00:03, 13.69it/s]

→ 500 Phase 3: finalize:  79%|███████▉  | 162/204 [00:12<00:03, 13.67it/s]

→ 500 Phase 3: finalize:  80%|████████  | 164/204 [00:12<00:02, 13.62it/s]

→ 500 Phase 3: finalize:  81%|████████▏ | 166/204 [00:12<00:02, 13.55it/s]

→ 500 Phase 3: finalize:  82%|████████▏ | 168/204 [00:12<00:02, 13.47it/s]

→ 500 Phase 3: finalize:  83%|████████▎ | 170/204 [00:13<00:02, 13.46it/s]

→ 500 Phase 3: finalize:  84%|████████▍ | 172/204 [00:13<00:02, 13.34it/s]

→ 500 Phase 3: finalize:  85%|████████▌ | 174/204 [00:13<00:02, 13.25it/s]

→ 500 Phase 3: finalize:  86%|████████▋ | 176/204 [00:13<00:02, 13.20it/s]

→ 500 Phase 3: finalize:  87%|████████▋ | 178/204 [00:13<00:01, 13.11it/s]

→ 500 Phase 3: finalize:  88%|████████▊ | 180/204 [00:13<00:01, 13.06it/s]

→ 500 Phase 3: finalize:  89%|████████▉ | 182/204 [00:14<00:01, 13.02it/s]

→ 500 Phase 3: finalize:  90%|█████████ | 184/204 [00:14<00:01, 13.00it/s]

→ 500 Phase 3: finalize:  91%|█████████ | 186/204 [00:14<00:01, 12.97it/s]

→ 500 Phase 3: finalize:  92%|█████████▏| 188/204 [00:14<00:01, 12.88it/s]

→ 500 Phase 3: finalize:  93%|█████████▎| 190/204 [00:14<00:01, 12.86it/s]

→ 500 Phase 3: finalize:  94%|█████████▍| 192/204 [00:14<00:00, 12.86it/s]

→ 500 Phase 3: finalize:  95%|█████████▌| 194/204 [00:14<00:00, 12.85it/s]

→ 500 Phase 3: finalize:  96%|█████████▌| 196/204 [00:15<00:00, 12.83it/s]

→ 500 Phase 3: finalize:  97%|█████████▋| 198/204 [00:15<00:00, 12.83it/s]

→ 500 Phase 3: finalize:  98%|█████████▊| 200/204 [00:15<00:00, 12.83it/s]

→ 500 Phase 3: finalize:  99%|█████████▉| 202/204 [00:15<00:00, 12.83it/s]

→ 500 Phase 3: finalize: 100%|██████████| 204/204 [00:15<00:00, 12.80it/s]

                                                                          
Processing Rigs:  50%|█████     | 1/2 [03:56<03:56, 236.61s/it][INFO] Filtered 1303 stationary frames, 213 remain


→ 1000 (213 images) Phase 1:   0%|          | 0/213 [00:00<?, ?it/s]

→ 1000 (213 images) Phase 1:   0%|          | 1/213 [00:03<11:05,  3.14s/it]

→ 1000 (213 images) Phase 1:  15%|█▌        | 33/213 [00:05<00:26,  6.77it/s]

→ 1000 (213 images) Phase 1:  26%|██▌       | 55/213 [00:05<00:12, 12.90it/s]

→ 1000 (213 images) Phase 1:  31%|███       | 66/213 [00:08<00:17,  8.41it/s]

→ 1000 (213 images) Phase 1:  42%|████▏     | 90/213 [00:08<00:08, 14.71it/s]

→ 1000 (213 images) Phase 1:  48%|████▊     | 102/213 [00:11<00:11,  9.44it/s]

→ 1000 (213 images) Phase 1:  60%|█████▉    | 127/213 [00:11<00:05, 15.80it/s]

→ 1000 (213 images) Phase 1:  66%|██████▌   | 141/213 [00:14<00:06, 10.55it/s]

→ 1000 (213 images) Phase 1:  75%|███████▌  | 160/213 [00:14<00:03, 15.13it/s]

→ 1000 (213 images) Phase 1:  80%|████████  | 171/213 [00:16<00:04,  9.87it/s]

→ 1000 (213 images) Phase 1:  90%|█████████ | 192/213 [00:16<00:01, 15.10it/s]

→ 1000 (213 images) Phase 1:  95%|█████████▌| 203/213 [00:18<00:00, 12.13it/s]

→ 1000 (213 images) Phase 1:  99%|█████████▉| 211/213 [00:18<00:00, 12.66it/s]

                                                                              

→ 1000 Phase 2: corners:   0%|          | 0/213 [00:00<?, ?it/s]

→ 1000 Phase 2: corners:   0%|          | 1/213 [00:00<03:11,  1.11it/s]

→ 1000 Phase 2: corners:   1%|          | 2/213 [00:01<03:08,  1.12it/s]

→ 1000 Phase 2: corners:   1%|▏         | 3/213 [00:02<03:11,  1.09it/s]

→ 1000 Phase 2: corners:   2%|▏         | 4/213 [00:03<03:09,  1.10it/s]

→ 1000 Phase 2: corners:   2%|▏         | 5/213 [00:04<03:04,  1.13it/s]

→ 1000 Phase 2: corners:   3%|▎         | 6/213 [00:05<03:03,  1.13it/s]

→ 1000 Phase 2: corners:   3%|▎         | 7/213 [00:06<03:01,  1.14it/s]

→ 1000 Phase 2: corners:   4%|▍         | 8/213 [00:07<02:59,  1.14it/s]

→ 1000 Phase 2: corners:   4%|▍         | 9/213 [00:07<03:00,  1.13it/s]

→ 1000 Phase 2: corners:   5%|▍         | 10/213 [00:08<03:01,  1.12it/s]

→ 1000 Phase 2: corners:   5%|▌         | 11/213 [00:09<03:00,  1.12it/s]

→ 1000 Phase 2: corners:   6%|▌         | 12/213 [00:10<03:00,  1.12it/s]

→ 1000 Phase 2: corners:   6%|▌         | 13/213 [00:11<03:00,  1.11it/s]

→ 1000 Phase 2: corners:   7%|▋         | 14/213 [00:12<02:59,  1.11it/s]

→ 1000 Phase 2: corners:   7%|▋         | 15/213 [00:13<02:58,  1.11it/s]

→ 1000 Phase 2: corners:   8%|▊         | 16/213 [00:14<02:57,  1.11it/s]

→ 1000 Phase 2: corners:   8%|▊         | 17/213 [00:15<02:57,  1.11it/s]

→ 1000 Phase 2: corners:   8%|▊         | 18/213 [00:16<02:54,  1.12it/s]

→ 1000 Phase 2: corners:   9%|▉         | 19/213 [00:16<02:51,  1.13it/s]

→ 1000 Phase 2: corners:   9%|▉         | 20/213 [00:17<02:49,  1.14it/s]

→ 1000 Phase 2: corners:  10%|▉         | 21/213 [00:18<02:55,  1.10it/s]

→ 1000 Phase 2: corners:  10%|█         | 22/213 [00:19<02:55,  1.09it/s]

→ 1000 Phase 2: corners:  11%|█         | 23/213 [00:20<02:50,  1.11it/s]

→ 1000 Phase 2: corners:  11%|█▏        | 24/213 [00:21<02:47,  1.13it/s]

→ 1000 Phase 2: corners:  12%|█▏        | 25/213 [00:22<02:47,  1.12it/s]

→ 1000 Phase 2: corners:  12%|█▏        | 26/213 [00:23<02:52,  1.08it/s]

→ 1000 Phase 2: corners:  13%|█▎        | 27/213 [00:24<02:49,  1.10it/s]

→ 1000 Phase 2: corners:  13%|█▎        | 28/213 [00:25<02:46,  1.11it/s]

→ 1000 Phase 2: corners:  14%|█▎        | 29/213 [00:26<02:45,  1.11it/s]

→ 1000 Phase 2: corners:  14%|█▍        | 30/213 [00:26<02:44,  1.11it/s]

→ 1000 Phase 2: corners:  15%|█▍        | 31/213 [00:27<02:41,  1.13it/s]

→ 1000 Phase 2: corners:  15%|█▌        | 32/213 [00:28<02:37,  1.15it/s]

→ 1000 Phase 2: corners:  15%|█▌        | 33/213 [00:29<02:37,  1.14it/s]

→ 1000 Phase 2: corners:  16%|█▌        | 34/213 [00:30<02:41,  1.11it/s]

→ 1000 Phase 2: corners:  16%|█▋        | 35/213 [00:31<02:42,  1.09it/s]

→ 1000 Phase 2: corners:  17%|█▋        | 36/213 [00:32<02:42,  1.09it/s]

→ 1000 Phase 2: corners:  17%|█▋        | 37/213 [00:33<02:39,  1.10it/s]

→ 1000 Phase 2: corners:  18%|█▊        | 38/213 [00:34<02:40,  1.09it/s]

→ 1000 Phase 2: corners:  18%|█▊        | 39/213 [00:35<02:39,  1.09it/s]

→ 1000 Phase 2: corners:  19%|█▉        | 40/213 [00:35<02:37,  1.10it/s]

→ 1000 Phase 2: corners:  19%|█▉        | 41/213 [00:36<02:37,  1.09it/s]

→ 1000 Phase 2: corners:  20%|█▉        | 42/213 [00:37<02:34,  1.10it/s]

→ 1000 Phase 2: corners:  20%|██        | 43/213 [00:38<02:34,  1.10it/s]

→ 1000 Phase 2: corners:  21%|██        | 44/213 [00:39<02:33,  1.10it/s]

→ 1000 Phase 2: corners:  21%|██        | 45/213 [00:40<02:33,  1.10it/s]

→ 1000 Phase 2: corners:  22%|██▏       | 46/213 [00:41<02:33,  1.09it/s]

→ 1000 Phase 2: corners:  22%|██▏       | 47/213 [00:42<02:33,  1.08it/s]

→ 1000 Phase 2: corners:  23%|██▎       | 48/213 [00:43<02:35,  1.06it/s]

→ 1000 Phase 2: corners:  23%|██▎       | 49/213 [00:44<02:32,  1.07it/s]

→ 1000 Phase 2: corners:  23%|██▎       | 50/213 [00:45<02:29,  1.09it/s]

→ 1000 Phase 2: corners:  24%|██▍       | 51/213 [00:46<02:28,  1.09it/s]

→ 1000 Phase 2: corners:  24%|██▍       | 52/213 [00:47<02:30,  1.07it/s]

→ 1000 Phase 2: corners:  25%|██▍       | 53/213 [00:48<02:29,  1.07it/s]

→ 1000 Phase 2: corners:  25%|██▌       | 54/213 [00:48<02:26,  1.08it/s]

→ 1000 Phase 2: corners:  26%|██▌       | 55/213 [00:49<02:27,  1.07it/s]

→ 1000 Phase 2: corners:  26%|██▋       | 56/213 [00:50<02:25,  1.08it/s]

→ 1000 Phase 2: corners:  27%|██▋       | 57/213 [00:51<02:26,  1.06it/s]

→ 1000 Phase 2: corners:  27%|██▋       | 58/213 [00:52<02:23,  1.08it/s]

→ 1000 Phase 2: corners:  28%|██▊       | 59/213 [00:53<02:20,  1.10it/s]

→ 1000 Phase 2: corners:  28%|██▊       | 60/213 [00:54<02:19,  1.10it/s]

→ 1000 Phase 2: corners:  29%|██▊       | 61/213 [00:55<02:16,  1.11it/s]

→ 1000 Phase 2: corners:  29%|██▉       | 62/213 [00:56<02:15,  1.12it/s]

→ 1000 Phase 2: corners:  30%|██▉       | 63/213 [00:57<02:13,  1.12it/s]

→ 1000 Phase 2: corners:  30%|███       | 64/213 [00:58<02:16,  1.09it/s]

→ 1000 Phase 2: corners:  31%|███       | 65/213 [00:58<02:13,  1.11it/s]

→ 1000 Phase 2: corners:  31%|███       | 66/213 [00:59<02:11,  1.12it/s]

→ 1000 Phase 2: corners:  31%|███▏      | 67/213 [01:00<02:08,  1.13it/s]

→ 1000 Phase 2: corners:  32%|███▏      | 68/213 [01:01<02:07,  1.14it/s]

→ 1000 Phase 2: corners:  32%|███▏      | 69/213 [01:02<02:06,  1.14it/s]

→ 1000 Phase 2: corners:  33%|███▎      | 70/213 [01:03<02:04,  1.15it/s]

→ 1000 Phase 2: corners:  33%|███▎      | 71/213 [01:04<02:03,  1.15it/s]

→ 1000 Phase 2: corners:  34%|███▍      | 72/213 [01:05<02:04,  1.14it/s]

→ 1000 Phase 2: corners:  34%|███▍      | 73/213 [01:05<02:03,  1.13it/s]

→ 1000 Phase 2: corners:  35%|███▍      | 74/213 [01:06<02:02,  1.13it/s]

→ 1000 Phase 2: corners:  35%|███▌      | 75/213 [01:07<02:02,  1.13it/s]

→ 1000 Phase 2: corners:  36%|███▌      | 76/213 [01:08<02:00,  1.13it/s]

→ 1000 Phase 2: corners:  36%|███▌      | 77/213 [01:09<01:59,  1.14it/s]

→ 1000 Phase 2: corners:  37%|███▋      | 78/213 [01:10<01:59,  1.13it/s]

→ 1000 Phase 2: corners:  37%|███▋      | 79/213 [01:11<01:58,  1.13it/s]

→ 1000 Phase 2: corners:  38%|███▊      | 80/213 [01:12<01:56,  1.14it/s]

→ 1000 Phase 2: corners:  38%|███▊      | 81/213 [01:13<01:57,  1.12it/s]

→ 1000 Phase 2: corners:  38%|███▊      | 82/213 [01:13<01:58,  1.11it/s]

→ 1000 Phase 2: corners:  39%|███▉      | 83/213 [01:14<01:59,  1.09it/s]

→ 1000 Phase 2: corners:  39%|███▉      | 84/213 [01:15<01:59,  1.08it/s]

→ 1000 Phase 2: corners:  40%|███▉      | 85/213 [01:16<01:59,  1.07it/s]

→ 1000 Phase 2: corners:  40%|████      | 86/213 [01:17<01:58,  1.07it/s]

→ 1000 Phase 2: corners:  41%|████      | 87/213 [01:18<01:57,  1.07it/s]

→ 1000 Phase 2: corners:  41%|████▏     | 88/213 [01:19<01:56,  1.07it/s]

→ 1000 Phase 2: corners:  42%|████▏     | 89/213 [01:20<01:57,  1.06it/s]

→ 1000 Phase 2: corners:  42%|████▏     | 90/213 [01:21<01:53,  1.08it/s]

→ 1000 Phase 2: corners:  43%|████▎     | 91/213 [01:22<01:52,  1.08it/s]

→ 1000 Phase 2: corners:  43%|████▎     | 92/213 [01:23<01:51,  1.08it/s]

→ 1000 Phase 2: corners:  44%|████▎     | 93/213 [01:24<01:49,  1.09it/s]

→ 1000 Phase 2: corners:  44%|████▍     | 94/213 [01:25<01:47,  1.10it/s]

→ 1000 Phase 2: corners:  45%|████▍     | 95/213 [01:25<01:45,  1.12it/s]

→ 1000 Phase 2: corners:  45%|████▌     | 96/213 [01:26<01:43,  1.13it/s]

→ 1000 Phase 2: corners:  46%|████▌     | 97/213 [01:27<01:42,  1.13it/s]

→ 1000 Phase 2: corners:  46%|████▌     | 98/213 [01:28<01:40,  1.14it/s]

→ 1000 Phase 2: corners:  46%|████▋     | 99/213 [01:29<01:42,  1.12it/s]

→ 1000 Phase 2: corners:  47%|████▋     | 100/213 [01:30<01:40,  1.13it/s]

→ 1000 Phase 2: corners:  47%|████▋     | 101/213 [01:31<01:38,  1.14it/s]

→ 1000 Phase 2: corners:  48%|████▊     | 102/213 [01:32<01:40,  1.10it/s]

→ 1000 Phase 2: corners:  48%|████▊     | 103/213 [01:33<01:42,  1.07it/s]

→ 1000 Phase 2: corners:  49%|████▉     | 104/213 [01:34<01:41,  1.08it/s]

→ 1000 Phase 2: corners:  49%|████▉     | 105/213 [01:34<01:38,  1.10it/s]

→ 1000 Phase 2: corners:  50%|████▉     | 106/213 [01:35<01:36,  1.11it/s]

→ 1000 Phase 2: corners:  50%|█████     | 107/213 [01:36<01:35,  1.11it/s]

→ 1000 Phase 2: corners:  51%|█████     | 108/213 [01:37<01:34,  1.11it/s]

→ 1000 Phase 2: corners:  51%|█████     | 109/213 [01:38<01:35,  1.09it/s]

→ 1000 Phase 2: corners:  52%|█████▏    | 110/213 [01:39<01:33,  1.10it/s]

→ 1000 Phase 2: corners:  52%|█████▏    | 111/213 [01:40<01:32,  1.10it/s]

→ 1000 Phase 2: corners:  53%|█████▎    | 112/213 [01:41<01:32,  1.10it/s]

→ 1000 Phase 2: corners:  53%|█████▎    | 113/213 [01:42<01:31,  1.09it/s]

→ 1000 Phase 2: corners:  54%|█████▎    | 114/213 [01:43<01:30,  1.09it/s]

→ 1000 Phase 2: corners:  54%|█████▍    | 115/213 [01:44<01:28,  1.10it/s]

→ 1000 Phase 2: corners:  54%|█████▍    | 116/213 [01:44<01:27,  1.10it/s]

→ 1000 Phase 2: corners:  55%|█████▍    | 117/213 [01:45<01:26,  1.11it/s]

→ 1000 Phase 2: corners:  55%|█████▌    | 118/213 [01:46<01:26,  1.10it/s]

→ 1000 Phase 2: corners:  56%|█████▌    | 119/213 [01:47<01:26,  1.09it/s]

→ 1000 Phase 2: corners:  56%|█████▋    | 120/213 [01:48<01:25,  1.08it/s]

→ 1000 Phase 2: corners:  57%|█████▋    | 121/213 [01:49<01:24,  1.09it/s]

→ 1000 Phase 2: corners:  57%|█████▋    | 122/213 [01:50<01:24,  1.08it/s]

→ 1000 Phase 2: corners:  58%|█████▊    | 123/213 [01:51<01:24,  1.06it/s]

→ 1000 Phase 2: corners:  58%|█████▊    | 124/213 [01:52<01:24,  1.06it/s]

→ 1000 Phase 2: corners:  59%|█████▊    | 125/213 [01:53<01:24,  1.05it/s]

→ 1000 Phase 2: corners:  59%|█████▉    | 126/213 [01:54<01:23,  1.04it/s]

→ 1000 Phase 2: corners:  60%|█████▉    | 127/213 [01:55<01:23,  1.03it/s]

→ 1000 Phase 2: corners:  60%|██████    | 128/213 [01:56<01:21,  1.04it/s]

→ 1000 Phase 2: corners:  61%|██████    | 129/213 [01:57<01:19,  1.06it/s]

→ 1000 Phase 2: corners:  61%|██████    | 130/213 [01:58<01:17,  1.07it/s]

→ 1000 Phase 2: corners:  62%|██████▏   | 131/213 [01:59<01:15,  1.08it/s]

→ 1000 Phase 2: corners:  62%|██████▏   | 132/213 [01:59<01:14,  1.08it/s]

→ 1000 Phase 2: corners:  62%|██████▏   | 133/213 [02:00<01:13,  1.09it/s]

→ 1000 Phase 2: corners:  63%|██████▎   | 134/213 [02:01<01:11,  1.10it/s]

→ 1000 Phase 2: corners:  63%|██████▎   | 135/213 [02:02<01:10,  1.11it/s]

→ 1000 Phase 2: corners:  64%|██████▍   | 136/213 [02:03<01:09,  1.11it/s]

→ 1000 Phase 2: corners:  64%|██████▍   | 137/213 [02:04<01:08,  1.11it/s]

→ 1000 Phase 2: corners:  65%|██████▍   | 138/213 [02:05<01:07,  1.12it/s]

→ 1000 Phase 2: corners:  65%|██████▌   | 139/213 [02:06<01:07,  1.10it/s]

→ 1000 Phase 2: corners:  66%|██████▌   | 140/213 [02:07<01:06,  1.11it/s]

→ 1000 Phase 2: corners:  66%|██████▌   | 141/213 [02:08<01:05,  1.10it/s]

→ 1000 Phase 2: corners:  67%|██████▋   | 142/213 [02:08<01:04,  1.10it/s]

→ 1000 Phase 2: corners:  67%|██████▋   | 143/213 [02:09<01:03,  1.10it/s]

→ 1000 Phase 2: corners:  68%|██████▊   | 144/213 [02:10<01:02,  1.10it/s]

→ 1000 Phase 2: corners:  68%|██████▊   | 145/213 [02:11<01:01,  1.10it/s]

→ 1000 Phase 2: corners:  69%|██████▊   | 146/213 [02:12<01:01,  1.09it/s]

→ 1000 Phase 2: corners:  69%|██████▉   | 147/213 [02:13<01:01,  1.08it/s]

→ 1000 Phase 2: corners:  69%|██████▉   | 148/213 [02:14<01:01,  1.06it/s]

→ 1000 Phase 2: corners:  70%|██████▉   | 149/213 [02:15<01:00,  1.06it/s]

→ 1000 Phase 2: corners:  70%|███████   | 150/213 [02:16<00:59,  1.05it/s]

→ 1000 Phase 2: corners:  71%|███████   | 151/213 [02:17<00:57,  1.08it/s]

→ 1000 Phase 2: corners:  71%|███████▏  | 152/213 [02:18<00:55,  1.09it/s]

→ 1000 Phase 2: corners:  72%|███████▏  | 153/213 [02:19<00:55,  1.09it/s]

→ 1000 Phase 2: corners:  72%|███████▏  | 154/213 [02:20<00:55,  1.07it/s]

→ 1000 Phase 2: corners:  73%|███████▎  | 155/213 [02:21<00:54,  1.06it/s]

→ 1000 Phase 2: corners:  73%|███████▎  | 156/213 [02:22<00:54,  1.05it/s]

→ 1000 Phase 2: corners:  74%|███████▎  | 157/213 [02:23<00:54,  1.03it/s]

→ 1000 Phase 2: corners:  74%|███████▍  | 158/213 [02:23<00:52,  1.06it/s]

→ 1000 Phase 2: corners:  75%|███████▍  | 159/213 [02:24<00:50,  1.07it/s]

→ 1000 Phase 2: corners:  75%|███████▌  | 160/213 [02:25<00:49,  1.07it/s]

→ 1000 Phase 2: corners:  76%|███████▌  | 161/213 [02:26<00:48,  1.07it/s]

→ 1000 Phase 2: corners:  76%|███████▌  | 162/213 [02:27<00:47,  1.07it/s]

→ 1000 Phase 2: corners:  77%|███████▋  | 163/213 [02:28<00:47,  1.06it/s]

→ 1000 Phase 2: corners:  77%|███████▋  | 164/213 [02:29<00:46,  1.06it/s]

→ 1000 Phase 2: corners:  77%|███████▋  | 165/213 [02:30<00:44,  1.07it/s]

→ 1000 Phase 2: corners:  78%|███████▊  | 166/213 [02:31<00:43,  1.08it/s]

→ 1000 Phase 2: corners:  78%|███████▊  | 167/213 [02:32<00:42,  1.09it/s]

→ 1000 Phase 2: corners:  79%|███████▉  | 168/213 [02:33<00:41,  1.09it/s]

→ 1000 Phase 2: corners:  79%|███████▉  | 169/213 [02:34<00:40,  1.09it/s]

→ 1000 Phase 2: corners:  80%|███████▉  | 170/213 [02:35<00:40,  1.07it/s]

→ 1000 Phase 2: corners:  80%|████████  | 171/213 [02:36<00:39,  1.06it/s]

→ 1000 Phase 2: corners:  81%|████████  | 172/213 [02:36<00:38,  1.07it/s]

→ 1000 Phase 2: corners:  81%|████████  | 173/213 [02:37<00:37,  1.07it/s]

→ 1000 Phase 2: corners:  82%|████████▏ | 174/213 [02:38<00:36,  1.07it/s]

→ 1000 Phase 2: corners:  82%|████████▏ | 175/213 [02:39<00:35,  1.07it/s]

→ 1000 Phase 2: corners:  83%|████████▎ | 176/213 [02:40<00:34,  1.07it/s]

→ 1000 Phase 2: corners:  83%|████████▎ | 177/213 [02:41<00:33,  1.07it/s]

→ 1000 Phase 2: corners:  84%|████████▎ | 178/213 [02:42<00:32,  1.07it/s]

→ 1000 Phase 2: corners:  84%|████████▍ | 179/213 [02:43<00:31,  1.08it/s]

→ 1000 Phase 2: corners:  85%|████████▍ | 180/213 [02:44<00:30,  1.07it/s]

→ 1000 Phase 2: corners:  85%|████████▍ | 181/213 [02:45<00:30,  1.06it/s]

→ 1000 Phase 2: corners:  85%|████████▌ | 182/213 [02:46<00:29,  1.06it/s]

→ 1000 Phase 2: corners:  86%|████████▌ | 183/213 [02:47<00:28,  1.06it/s]

→ 1000 Phase 2: corners:  86%|████████▋ | 184/213 [02:48<00:27,  1.07it/s]

→ 1000 Phase 2: corners:  87%|████████▋ | 185/213 [02:49<00:26,  1.07it/s]

→ 1000 Phase 2: corners:  87%|████████▋ | 186/213 [02:50<00:25,  1.07it/s]

→ 1000 Phase 2: corners:  88%|████████▊ | 187/213 [02:51<00:24,  1.08it/s]

→ 1000 Phase 2: corners:  88%|████████▊ | 188/213 [02:51<00:23,  1.07it/s]

→ 1000 Phase 2: corners:  89%|████████▊ | 189/213 [02:52<00:22,  1.08it/s]

→ 1000 Phase 2: corners:  89%|████████▉ | 190/213 [02:53<00:21,  1.09it/s]

→ 1000 Phase 2: corners:  90%|████████▉ | 191/213 [02:54<00:20,  1.10it/s]

→ 1000 Phase 2: corners:  90%|█████████ | 192/213 [02:55<00:18,  1.11it/s]

→ 1000 Phase 2: corners:  91%|█████████ | 193/213 [02:56<00:17,  1.12it/s]

→ 1000 Phase 2: corners:  91%|█████████ | 194/213 [02:57<00:17,  1.12it/s]

→ 1000 Phase 2: corners:  92%|█████████▏| 195/213 [02:58<00:15,  1.13it/s]

→ 1000 Phase 2: corners:  92%|█████████▏| 196/213 [02:59<00:15,  1.12it/s]

→ 1000 Phase 2: corners:  92%|█████████▏| 197/213 [02:59<00:14,  1.12it/s]

→ 1000 Phase 2: corners:  93%|█████████▎| 198/213 [03:00<00:13,  1.13it/s]

→ 1000 Phase 2: corners:  93%|█████████▎| 199/213 [03:01<00:12,  1.13it/s]

→ 1000 Phase 2: corners:  94%|█████████▍| 200/213 [03:02<00:11,  1.13it/s]

→ 1000 Phase 2: corners:  94%|█████████▍| 201/213 [03:03<00:10,  1.13it/s]

→ 1000 Phase 2: corners:  95%|█████████▍| 202/213 [03:04<00:09,  1.13it/s]

→ 1000 Phase 2: corners:  95%|█████████▌| 203/213 [03:05<00:08,  1.13it/s]

→ 1000 Phase 2: corners:  96%|█████████▌| 204/213 [03:06<00:08,  1.11it/s]

→ 1000 Phase 2: corners:  96%|█████████▌| 205/213 [03:07<00:07,  1.12it/s]

→ 1000 Phase 2: corners:  97%|█████████▋| 206/213 [03:07<00:06,  1.13it/s]

→ 1000 Phase 2: corners:  97%|█████████▋| 207/213 [03:08<00:05,  1.13it/s]

→ 1000 Phase 2: corners:  98%|█████████▊| 208/213 [03:09<00:04,  1.14it/s]

→ 1000 Phase 2: corners:  98%|█████████▊| 209/213 [03:10<00:03,  1.14it/s]

→ 1000 Phase 2: corners:  99%|█████████▊| 210/213 [03:11<00:02,  1.14it/s]

→ 1000 Phase 2: corners:  99%|█████████▉| 211/213 [03:12<00:01,  1.15it/s]

→ 1000 Phase 2: corners: 100%|█████████▉| 212/213 [03:13<00:00,  1.15it/s]

→ 1000 Phase 2: corners: 100%|██████████| 213/213 [03:14<00:00,  1.15it/s]

                                                                          [PASS2] Frame 0000684: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000685: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000686: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000687: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000686: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Summary: 2 frames fixed, 2 untrusted, 213 total


→ 1000 Phase 3: finalize:   0%|          | 0/213 [00:00<?, ?it/s]

→ 1000 Phase 3: finalize:   1%|          | 2/213 [00:00<00:17, 12.25it/s]

→ 1000 Phase 3: finalize:   2%|▏         | 4/213 [00:00<00:16, 12.68it/s]

→ 1000 Phase 3: finalize:   3%|▎         | 6/213 [00:00<00:16, 12.82it/s]

→ 1000 Phase 3: finalize:   4%|▍         | 8/213 [00:00<00:15, 12.89it/s]

→ 1000 Phase 3: finalize:   5%|▍         | 10/213 [00:00<00:15, 12.95it/s]

→ 1000 Phase 3: finalize:   6%|▌         | 12/213 [00:00<00:15, 12.98it/s]

→ 1000 Phase 3: finalize:   7%|▋         | 14/213 [00:01<00:15, 12.83it/s]

→ 1000 Phase 3: finalize:   8%|▊         | 16/213 [00:01<00:15, 12.86it/s]

→ 1000 Phase 3: finalize:   8%|▊         | 18/213 [00:01<00:15, 12.88it/s]

→ 1000 Phase 3: finalize:   9%|▉         | 20/213 [00:01<00:14, 12.88it/s]

→ 1000 Phase 3: finalize:  10%|█         | 22/213 [00:01<00:14, 12.93it/s]

→ 1000 Phase 3: finalize:  11%|█▏        | 24/213 [00:01<00:14, 12.95it/s]

→ 1000 Phase 3: finalize:  12%|█▏        | 26/213 [00:02<00:14, 12.94it/s]

→ 1000 Phase 3: finalize:  13%|█▎        | 28/213 [00:02<00:14, 12.94it/s]

→ 1000 Phase 3: finalize:  14%|█▍        | 30/213 [00:02<00:14, 12.90it/s]

→ 1000 Phase 3: finalize:  15%|█▌        | 32/213 [00:02<00:14, 12.85it/s]

→ 1000 Phase 3: finalize:  16%|█▌        | 34/213 [00:02<00:13, 12.81it/s]

→ 1000 Phase 3: finalize:  17%|█▋        | 36/213 [00:02<00:13, 12.78it/s]

→ 1000 Phase 3: finalize:  18%|█▊        | 38/213 [00:02<00:13, 12.75it/s]

→ 1000 Phase 3: finalize:  19%|█▉        | 40/213 [00:03<00:13, 12.73it/s]

→ 1000 Phase 3: finalize:  20%|█▉        | 42/213 [00:03<00:13, 12.70it/s]

→ 1000 Phase 3: finalize:  21%|██        | 44/213 [00:03<00:13, 12.70it/s]

→ 1000 Phase 3: finalize:  22%|██▏       | 46/213 [00:03<00:13, 12.66it/s]

→ 1000 Phase 3: finalize:  23%|██▎       | 48/213 [00:03<00:13, 12.64it/s]

→ 1000 Phase 3: finalize:  23%|██▎       | 50/213 [00:03<00:12, 12.63it/s]

→ 1000 Phase 3: finalize:  24%|██▍       | 52/213 [00:04<00:12, 12.61it/s]

→ 1000 Phase 3: finalize:  25%|██▌       | 54/213 [00:04<00:12, 12.58it/s]

→ 1000 Phase 3: finalize:  26%|██▋       | 56/213 [00:04<00:12, 12.57it/s]

→ 1000 Phase 3: finalize:  27%|██▋       | 58/213 [00:04<00:12, 12.56it/s]

→ 1000 Phase 3: finalize:  28%|██▊       | 60/213 [00:04<00:12, 12.56it/s]

→ 1000 Phase 3: finalize:  29%|██▉       | 62/213 [00:04<00:12, 12.54it/s]

→ 1000 Phase 3: finalize:  30%|███       | 64/213 [00:05<00:11, 12.54it/s]

→ 1000 Phase 3: finalize:  31%|███       | 66/213 [00:05<00:11, 12.52it/s]

→ 1000 Phase 3: finalize:  32%|███▏      | 68/213 [00:05<00:11, 12.47it/s]

→ 1000 Phase 3: finalize:  33%|███▎      | 70/213 [00:05<00:11, 12.45it/s]

→ 1000 Phase 3: finalize:  34%|███▍      | 72/213 [00:05<00:11, 12.42it/s]

→ 1000 Phase 3: finalize:  35%|███▍      | 74/213 [00:05<00:11, 12.37it/s]

→ 1000 Phase 3: finalize:  36%|███▌      | 76/213 [00:05<00:11, 12.42it/s]

→ 1000 Phase 3: finalize:  37%|███▋      | 78/213 [00:06<00:10, 12.44it/s]

→ 1000 Phase 3: finalize:  38%|███▊      | 80/213 [00:06<00:10, 12.45it/s]

→ 1000 Phase 3: finalize:  38%|███▊      | 82/213 [00:06<00:10, 12.45it/s]

→ 1000 Phase 3: finalize:  39%|███▉      | 84/213 [00:06<00:10, 12.43it/s]

→ 1000 Phase 3: finalize:  40%|████      | 86/213 [00:06<00:10, 12.42it/s]

→ 1000 Phase 3: finalize:  41%|████▏     | 88/213 [00:06<00:10, 12.41it/s]

→ 1000 Phase 3: finalize:  42%|████▏     | 90/213 [00:07<00:09, 12.41it/s]

→ 1000 Phase 3: finalize:  43%|████▎     | 92/213 [00:07<00:09, 12.42it/s]

→ 1000 Phase 3: finalize:  44%|████▍     | 94/213 [00:07<00:09, 12.46it/s]

→ 1000 Phase 3: finalize:  45%|████▌     | 96/213 [00:07<00:09, 12.48it/s]

→ 1000 Phase 3: finalize:  46%|████▌     | 98/213 [00:07<00:09, 12.52it/s]

→ 1000 Phase 3: finalize:  47%|████▋     | 100/213 [00:07<00:08, 12.61it/s]

→ 1000 Phase 3: finalize:  48%|████▊     | 102/213 [00:08<00:08, 12.68it/s]

→ 1000 Phase 3: finalize:  49%|████▉     | 104/213 [00:08<00:08, 12.71it/s]

→ 1000 Phase 3: finalize:  50%|████▉     | 106/213 [00:08<00:08, 12.70it/s]

→ 1000 Phase 3: finalize:  51%|█████     | 108/213 [00:08<00:08, 12.73it/s]

→ 1000 Phase 3: finalize:  52%|█████▏    | 110/213 [00:08<00:08, 12.77it/s]

→ 1000 Phase 3: finalize:  53%|█████▎    | 112/213 [00:08<00:07, 12.80it/s]

→ 1000 Phase 3: finalize:  54%|█████▎    | 114/213 [00:09<00:07, 12.82it/s]

→ 1000 Phase 3: finalize:  54%|█████▍    | 116/213 [00:09<00:07, 12.80it/s]

→ 1000 Phase 3: finalize:  55%|█████▌    | 118/213 [00:09<00:07, 12.91it/s]

→ 1000 Phase 3: finalize:  56%|█████▋    | 120/213 [00:09<00:07, 12.90it/s]

→ 1000 Phase 3: finalize:  57%|█████▋    | 122/213 [00:09<00:07, 12.92it/s]

→ 1000 Phase 3: finalize:  58%|█████▊    | 124/213 [00:09<00:06, 12.95it/s]

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→ 1000 Phase 3: finalize:  60%|██████    | 128/213 [00:10<00:06, 12.95it/s]

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→ 1000 Phase 3: finalize:  88%|████████▊ | 188/213 [00:14<00:01, 12.99it/s]

→ 1000 Phase 3: finalize:  89%|████████▉ | 190/213 [00:14<00:01, 12.96it/s]

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→ 1000 Phase 3: finalize:  94%|█████████▍| 200/213 [00:15<00:01, 12.87it/s]

→ 1000 Phase 3: finalize:  95%|█████████▍| 202/213 [00:15<00:00, 12.87it/s]

→ 1000 Phase 3: finalize:  96%|█████████▌| 204/213 [00:15<00:00, 12.88it/s]

→ 1000 Phase 3: finalize:  97%|█████████▋| 206/213 [00:16<00:00, 12.88it/s]

→ 1000 Phase 3: finalize:  98%|█████████▊| 208/213 [00:16<00:00, 12.88it/s]

→ 1000 Phase 3: finalize:  99%|█████████▊| 210/213 [00:16<00:00, 12.90it/s]

→ 1000 Phase 3: finalize: 100%|█████████▉| 212/213 [00:16<00:00, 12.88it/s]

                                                                           
Processing Rigs: 100%|██████████| 2/2 [07:50<00:00, 235.28s/it]
Processing Rigs: 100%|██████████| 2/2 [07:50<00:00, 235.48s/it]
[💾] Saved RigFrameDataset to /working/MDC101_W036_2025-12-31/calibration/debug/1_digitized_full/rig_frames_full.json
[✅] Saved full dataset: 417 frames from 2 rigs to /working/MDC101_W036_2025-12-31/calibration/debug/1_digitized_full/rig_frames_full.json
[💾] Saved RigFrameDataset to /working/MDC101_W036_2025-12-31/calibration/debug/1_digitized_full/rig_frames_full.json
[📋] Creating calibration subset (100 frames/rig) with visualizations...
[📋] 500: 100 frames selected from 204
[📋] 1000: 100 frames selected from 213
[💾] Saved RigFrameDataset to /working/MDC101_W036_2025-12-31/calibration/debug/1_digitized/rig_frames.json
[INFO] Reloading dataset from disk to ensure clean state for multiprocessing...
[📂] Loaded RigFrameDataset from /working/MDC101_W036_2025-12-31/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<01:59,  3.07s/it]
Computing max image from bright frames:   5%|▌         | 2/40 [00:06<01:56,  3.06s/it]
Computing max image from bright frames:   8%|▊         | 3/40 [00:09<01:53,  3.06s/it]
Computing max image from bright frames:  10%|█         | 4/40 [00:12<01:49,  3.05s/it]
Computing max image from bright frames:  12%|█▎        | 5/40 [00:15<01:47,  3.06s/it]
Computing max image from bright frames:  15%|█▌        | 6/40 [00:18<01:44,  3.07s/it]
Computing max image from bright frames:  18%|█▊        | 7/40 [00:21<01:41,  3.08s/it]
Computing max image from bright frames:  20%|██        | 8/40 [00:24<01:38,  3.08s/it]
Computing max image from bright frames:  22%|██▎       | 9/40 [00:27<01:34,  3.05s/it]
Computing max image from bright frames:  25%|██▌       | 10/40 [00:30<01:30,  3.03s/it]
Computing max image from bright frames:  28%|██▊       | 11/40 [00:33<01:26,  2.98s/it]
Computing max image from bright frames:  30%|███       | 12/40 [00:36<01:22,  2.94s/it]
Computing max image from bright frames:  32%|███▎      | 13/40 [00:39<01:18,  2.92s/it]
Computing max image from bright frames:  35%|███▌      | 14/40 [00:41<01:15,  2.89s/it]
Computing max image from bright frames:  38%|███▊      | 15/40 [00:44<01:13,  2.92s/it]
Computing max image from bright frames:  40%|████      | 16/40 [00:47<01:11,  2.96s/it]
Computing max image from bright frames:  42%|████▎     | 17/40 [00:51<01:08,  2.98s/it]
Computing max image from bright frames:  45%|████▌     | 18/40 [00:54<01:06,  3.00s/it]
Computing max image from bright frames:  48%|████▊     | 19/40 [00:57<01:03,  3.00s/it]
Computing max image from bright frames:  50%|█████     | 20/40 [01:00<01:00,  3.00s/it]
Computing max image from bright frames:  52%|█████▎    | 21/40 [01:03<00:57,  3.02s/it]
Computing max image from bright frames:  55%|█████▌    | 22/40 [01:06<00:54,  3.04s/it]
Computing max image from bright frames:  57%|█████▊    | 23/40 [01:09<00:51,  3.05s/it]
Computing max image from bright frames:  60%|██████    | 24/40 [01:12<00:48,  3.05s/it]
Computing max image from bright frames:  62%|██████▎   | 25/40 [01:15<00:45,  3.05s/it]
Computing max image from bright frames:  65%|██████▌   | 26/40 [01:18<00:42,  3.03s/it]
Computing max image from bright frames:  68%|██████▊   | 27/40 [01:21<00:39,  3.04s/it]
Computing max image from bright frames:  70%|███████   | 28/40 [01:24<00:36,  3.06s/it]
Computing max image from bright frames:  72%|███████▎  | 29/40 [01:27<00:33,  3.06s/it]
Computing max image from bright frames:  75%|███████▌  | 30/40 [01:30<00:30,  3.04s/it]
Computing max image from bright frames:  78%|███████▊  | 31/40 [01:33<00:27,  3.00s/it]
Computing max image from bright frames:  80%|████████  | 32/40 [01:36<00:23,  2.93s/it]
Computing max image from bright frames:  82%|████████▎ | 33/40 [01:39<00:20,  2.88s/it]
Computing max image from bright frames:  85%|████████▌ | 34/40 [01:41<00:17,  2.86s/it]
Computing max image from bright frames:  88%|████████▊ | 35/40 [01:45<00:14,  2.95s/it]
Computing max image from bright frames:  90%|█████████ | 36/40 [01:48<00:11,  2.99s/it]
Computing max image from bright frames:  92%|█████████▎| 37/40 [01:51<00:09,  3.01s/it]
Computing max image from bright frames:  95%|█████████▌| 38/40 [01:54<00:06,  3.04s/it]
Computing max image from bright frames:  98%|█████████▊| 39/40 [01:57<00:03,  3.05s/it]
Computing max image from bright frames: 100%|██████████| 40/40 [01:59<00:00,  2.84s/it]
                                                                                       

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Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   0%|          | 0/100 [00:00<?, ?it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   1%|          | 1/100 [00:00<00:13,  7.58it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   1%|          | 1/100 [00:00<00:13,  7.58it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   2%|▏         | 2/100 [00:00<00:12,  7.58it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   3%|▎         | 3/100 [00:00<00:12,  7.58it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   4%|▍         | 4/100 [00:00<00:12,  7.58it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   5%|▌         | 5/100 [00:00<00:12,  7.58it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   6%|▌         | 6/100 [00:00<00:12,  7.58it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   7%|▋         | 7/100 [00:00<00:12,  7.58it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   8%|▊         | 8/100 [00:00<00:12,  7.58it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   9%|▉         | 9/100 [00:00<00:12,  7.58it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  10%|█         | 10/100 [00:00<00:11,  7.58it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  11%|█         | 11/100 [00:00<00:11,  7.58it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  12%|█▏        | 12/100 [00:00<00:11,  7.58it/s]
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Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  14%|█▍        | 14/100 [00:00<00:11,  7.58it/s]
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Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  16%|█▌        | 16/100 [00:00<00:11,  7.58it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  17%|█▋        | 17/100 [00:00<00:00, 85.22it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  17%|█▋        | 17/100 [00:00<00:00, 85.22it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  18%|█▊        | 18/100 [00:00<00:00, 85.22it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  19%|█▉        | 19/100 [00:00<00:00, 85.22it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  20%|██        | 20/100 [00:00<00:00, 85.22it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  21%|██        | 21/100 [00:00<00:00, 85.22it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  22%|██▏       | 22/100 [00:00<00:00, 85.22it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  23%|██▎       | 23/100 [00:00<00:00, 85.22it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  24%|██▍       | 24/100 [00:00<00:00, 85.22it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 300.0} (0.000):  25%|██▌       | 25/100 [00:00<00:00, 85.22it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.001 | Best: {'fx': 490.909} (0.001):  26%|██▌       | 26/100 [00:00<00:00, 85.22it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.001 | Best: {'fx': 490.909} (0.001):  27%|██▋       | 27/100 [00:00<00:00, 91.21it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.000 | Best: {'fx': 490.909} (0.001):  27%|██▋       | 27/100 [00:00<00:00, 91.21it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.018 | Best: {'fx': 519.192} (0.018):  28%|██▊       | 28/100 [00:00<00:00, 91.21it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.003 | Best: {'fx': 519.192} (0.018):  29%|██▉       | 29/100 [00:00<00:00, 91.21it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.005 | Best: {'fx': 519.192} (0.018):  30%|███       | 30/100 [00:00<00:00, 91.21it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 519.192} (0.018):  31%|███       | 31/100 [00:00<00:00, 91.21it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.040 | Best: {'fx': 526.263} (0.040):  32%|███▏      | 32/100 [00:00<00:00, 91.21it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.030 | Best: {'fx': 526.263} (0.040):  33%|███▎      | 33/100 [00:00<00:00, 91.21it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.070 | Best: {'fx': 533.333} (0.070):  34%|███▍      | 34/100 [00:00<00:00, 91.21it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.039 | Best: {'fx': 533.333} (0.070):  35%|███▌      | 35/100 [00:00<00:00, 91.21it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.025 | Best: {'fx': 533.333} (0.070):  36%|███▌      | 36/100 [00:00<00:00, 91.21it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.020 | Best: {'fx': 533.333} (0.070):  37%|███▋      | 37/100 [00:00<00:00, 91.21it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.022 | Best: {'fx': 533.333} (0.070):  38%|███▊      | 38/100 [00:00<00:00, 91.21it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.015 | Best: {'fx': 533.333} (0.070):  39%|███▉      | 39/100 [00:00<00:00, 91.21it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.014 | Best: {'fx': 533.333} (0.070):  40%|████      | 40/100 [00:00<00:00, 91.21it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.014 | Best: {'fx': 533.333} (0.070):  41%|████      | 41/100 [00:00<00:00, 91.21it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.018 | Best: {'fx': 533.333} (0.070):  42%|████▏     | 42/100 [00:00<00:00, 91.21it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.016 | Best: {'fx': 533.333} (0.070):  43%|████▎     | 43/100 [00:00<00:00, 91.21it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.016 | Best: {'fx': 533.333} (0.070):  44%|████▍     | 44/100 [00:00<00:00, 115.46it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.013 | Best: {'fx': 533.333} (0.070):  44%|████▍     | 44/100 [00:00<00:00, 115.46it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.013 | Best: {'fx': 533.333} (0.070):  45%|████▌     | 45/100 [00:00<00:00, 115.46it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.011 | Best: {'fx': 533.333} (0.070):  46%|████▌     | 46/100 [00:00<00:00, 115.46it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.012 | Best: {'fx': 533.333} (0.070):  47%|████▋     | 47/100 [00:00<00:00, 115.46it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.012 | Best: {'fx': 533.333} (0.070):  48%|████▊     | 48/100 [00:00<00:00, 115.46it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.011 | Best: {'fx': 533.333} (0.070):  49%|████▉     | 49/100 [00:00<00:00, 115.46it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.011 | Best: {'fx': 533.333} (0.070):  50%|█████     | 50/100 [00:00<00:00, 115.46it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.012 | Best: {'fx': 533.333} (0.070):  51%|█████     | 51/100 [00:00<00:00, 115.46it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.011 | Best: {'fx': 533.333} (0.070):  52%|█████▏    | 52/100 [00:00<00:00, 115.46it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.070):  53%|█████▎    | 53/100 [00:00<00:00, 115.46it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.011 | Best: {'fx': 533.333} (0.070):  54%|█████▍    | 54/100 [00:00<00:00, 115.46it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.070):  55%|█████▌    | 55/100 [00:00<00:00, 115.46it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.070):  56%|█████▌    | 56/100 [00:00<00:00, 115.46it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.070):  57%|█████▋    | 57/100 [00:00<00:00, 115.46it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.070):  58%|█████▊    | 58/100 [00:00<00:00, 115.46it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.070):  59%|█████▉    | 59/100 [00:00<00:00, 125.07it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.070):  59%|█████▉    | 59/100 [00:00<00:00, 125.07it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.070):  60%|██████    | 60/100 [00:00<00:00, 125.07it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.070):  61%|██████    | 61/100 [00:00<00:00, 125.07it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.070):  62%|██████▏   | 62/100 [00:00<00:00, 125.07it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.070):  63%|██████▎   | 63/100 [00:00<00:00, 125.07it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.070):  64%|██████▍   | 64/100 [00:00<00:00, 125.07it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.070):  65%|██████▌   | 65/100 [00:00<00:00, 125.07it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  66%|██████▌   | 66/100 [00:00<00:00, 125.07it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.010 | Best: {'fx': 533.333} (0.070):  67%|██████▋   | 67/100 [00:00<00:00, 125.07it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  68%|██████▊   | 68/100 [00:00<00:00, 125.07it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  69%|██████▉   | 69/100 [00:00<00:00, 125.07it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  70%|███████   | 70/100 [00:00<00:00, 125.07it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  71%|███████   | 71/100 [00:00<00:00, 125.07it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  72%|███████▏  | 72/100 [00:00<00:00, 125.07it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  73%|███████▎  | 73/100 [00:00<00:00, 125.07it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  74%|███████▍  | 74/100 [00:00<00:00, 125.07it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  75%|███████▌  | 75/100 [00:00<00:00, 125.07it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  76%|███████▌  | 76/100 [00:00<00:00, 125.07it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  77%|███████▋  | 77/100 [00:00<00:00, 125.07it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  78%|███████▊  | 78/100 [00:00<00:00, 136.88it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  78%|███████▊  | 78/100 [00:00<00:00, 136.88it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  79%|███████▉  | 79/100 [00:00<00:00, 136.88it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  80%|████████  | 80/100 [00:00<00:00, 136.88it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  81%|████████  | 81/100 [00:00<00:00, 136.88it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  82%|████████▏ | 82/100 [00:00<00:00, 136.88it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  83%|████████▎ | 83/100 [00:00<00:00, 136.88it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  84%|████████▍ | 84/100 [00:00<00:00, 136.88it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  85%|████████▌ | 85/100 [00:00<00:00, 136.88it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  86%|████████▌ | 86/100 [00:00<00:00, 136.88it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  87%|████████▋ | 87/100 [00:00<00:00, 136.88it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  88%|████████▊ | 88/100 [00:00<00:00, 136.88it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  89%|████████▉ | 89/100 [00:00<00:00, 136.88it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  90%|█████████ | 90/100 [00:00<00:00, 136.88it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  91%|█████████ | 91/100 [00:00<00:00, 136.88it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  92%|█████████▏| 92/100 [00:00<00:00, 136.88it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  93%|█████████▎| 93/100 [00:00<00:00, 136.88it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  94%|█████████▍| 94/100 [00:00<00:00, 143.26it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  94%|█████████▍| 94/100 [00:00<00:00, 143.26it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  95%|█████████▌| 95/100 [00:00<00:00, 143.26it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  96%|█████████▌| 96/100 [00:00<00:00, 143.26it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  97%|█████████▋| 97/100 [00:00<00:00, 143.26it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  98%|█████████▊| 98/100 [00:00<00:00, 143.26it/s]
Brute | Start: {'fx': 500.0} (0.004) | Current: 0.009 | Best: {'fx': 533.333} (0.070):  99%|█████████▉| 99/100 [00:00<00:00, 143.26it/s]
                                                                                                                                        

  0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.007 | Best: {'fx': 508.333} (0.007):   0%|          | 0/50 [00:00<?, ?it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.007 | Best: {'fx': 508.333} (0.007):   2%|▏         | 1/50 [00:00<00:05,  8.75it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.008 | Best: {'fx': 509.354} (0.008):   2%|▏         | 1/50 [00:00<00:05,  8.75it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.009 | Best: {'fx': 510.374} (0.009):   4%|▍         | 2/50 [00:00<00:05,  8.75it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.011 | Best: {'fx': 512.415} (0.011):   6%|▌         | 3/50 [00:00<00:05,  8.75it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.013 | Best: {'fx': 515.476} (0.013):   8%|▊         | 4/50 [00:00<00:05,  8.75it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.009 | Best: {'fx': 515.476} (0.013):  10%|█         | 5/50 [00:00<00:05,  8.75it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.011 | Best: {'fx': 515.476} (0.013):  12%|█▏        | 6/50 [00:00<00:05,  8.75it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.015 | Best: {'fx': 516.497} (0.015):  14%|█▍        | 7/50 [00:00<00:04,  8.75it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.012 | Best: {'fx': 516.497} (0.015):  16%|█▌        | 8/50 [00:00<00:04,  8.75it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.016 | Best: {'fx': 517.517} (0.016):  18%|█▊        | 9/50 [00:00<00:04,  8.75it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.018 | Best: {'fx': 518.537} (0.018):  20%|██        | 10/50 [00:00<00:04,  8.75it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.020 | Best: {'fx': 519.558} (0.020):  22%|██▏       | 11/50 [00:00<00:04,  8.75it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.024 | Best: {'fx': 520.578} (0.024):  24%|██▍       | 12/50 [00:00<00:04,  8.75it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.024 | Best: {'fx': 520.578} (0.024):  26%|██▌       | 13/50 [00:00<00:00, 65.37it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.040 | Best: {'fx': 526.701} (0.040):  26%|██▌       | 13/50 [00:00<00:00, 65.37it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.026 | Best: {'fx': 526.701} (0.040):  28%|██▊       | 14/50 [00:00<00:00, 65.37it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.033 | Best: {'fx': 526.701} (0.040):  30%|███       | 15/50 [00:00<00:00, 65.37it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.029 | Best: {'fx': 526.701} (0.040):  32%|███▏      | 16/50 [00:00<00:00, 65.37it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.031 | Best: {'fx': 526.701} (0.040):  34%|███▍      | 17/50 [00:00<00:00, 65.37it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.037 | Best: {'fx': 526.701} (0.040):  36%|███▌      | 18/50 [00:00<00:00, 65.37it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.056 | Best: {'fx': 529.762} (0.056):  38%|███▊      | 19/50 [00:00<00:00, 65.37it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.051 | Best: {'fx': 529.762} (0.056):  40%|████      | 20/50 [00:00<00:00, 65.37it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.046 | Best: {'fx': 529.762} (0.056):  42%|████▏     | 21/50 [00:00<00:00, 65.37it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.066 | Best: {'fx': 532.823} (0.066):  44%|████▍     | 22/50 [00:00<00:00, 65.37it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.070 | Best: {'fx': 533.844} (0.070):  46%|████▌     | 23/50 [00:00<00:00, 65.37it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.065 | Best: {'fx': 533.844} (0.070):  48%|████▊     | 24/50 [00:00<00:00, 65.37it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.067 | Best: {'fx': 533.844} (0.070):  50%|█████     | 25/50 [00:00<00:00, 65.37it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.055 | Best: {'fx': 533.844} (0.070):  52%|█████▏    | 26/50 [00:00<00:00, 65.37it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.049 | Best: {'fx': 533.844} (0.070):  54%|█████▍    | 27/50 [00:00<00:00, 65.37it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.049 | Best: {'fx': 533.844} (0.070):  56%|█████▌    | 28/50 [00:00<00:00, 97.85it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.039 | Best: {'fx': 533.844} (0.070):  56%|█████▌    | 28/50 [00:00<00:00, 97.85it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.052 | Best: {'fx': 533.844} (0.070):  58%|█████▊    | 29/50 [00:00<00:00, 97.85it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.050 | Best: {'fx': 533.844} (0.070):  60%|██████    | 30/50 [00:00<00:00, 97.85it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.043 | Best: {'fx': 533.844} (0.070):  62%|██████▏   | 31/50 [00:00<00:00, 97.85it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.032 | Best: {'fx': 533.844} (0.070):  64%|██████▍   | 32/50 [00:00<00:00, 97.85it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.034 | Best: {'fx': 533.844} (0.070):  66%|██████▌   | 33/50 [00:00<00:00, 97.85it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.037 | Best: {'fx': 533.844} (0.070):  68%|██████▊   | 34/50 [00:00<00:00, 97.85it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.036 | Best: {'fx': 533.844} (0.070):  70%|███████   | 35/50 [00:00<00:00, 97.85it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.033 | Best: {'fx': 533.844} (0.070):  72%|███████▏  | 36/50 [00:00<00:00, 97.85it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.029 | Best: {'fx': 533.844} (0.070):  74%|███████▍  | 37/50 [00:00<00:00, 97.85it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.027 | Best: {'fx': 533.844} (0.070):  76%|███████▌  | 38/50 [00:00<00:00, 97.85it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.030 | Best: {'fx': 533.844} (0.070):  78%|███████▊  | 39/50 [00:00<00:00, 97.85it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.030 | Best: {'fx': 533.844} (0.070):  80%|████████  | 40/50 [00:00<00:00, 97.85it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.028 | Best: {'fx': 533.844} (0.070):  82%|████████▏ | 41/50 [00:00<00:00, 97.85it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.025 | Best: {'fx': 533.844} (0.070):  84%|████████▍ | 42/50 [00:00<00:00, 97.85it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.025 | Best: {'fx': 533.844} (0.070):  86%|████████▌ | 43/50 [00:00<00:00, 117.01it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.028 | Best: {'fx': 533.844} (0.070):  86%|████████▌ | 43/50 [00:00<00:00, 117.01it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.025 | Best: {'fx': 533.844} (0.070):  88%|████████▊ | 44/50 [00:00<00:00, 117.01it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.026 | Best: {'fx': 533.844} (0.070):  90%|█████████ | 45/50 [00:00<00:00, 117.01it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.024 | Best: {'fx': 533.844} (0.070):  92%|█████████▏| 46/50 [00:00<00:00, 117.01it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.024 | Best: {'fx': 533.844} (0.070):  94%|█████████▍| 47/50 [00:00<00:00, 117.01it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.024 | Best: {'fx': 533.844} (0.070):  96%|█████████▌| 48/50 [00:00<00:00, 117.01it/s]
Brute | Start: {'fx': 533.333} (0.070) | Current: 0.023 | Best: {'fx': 533.844} (0.070):  98%|█████████▊| 49/50 [00:00<00:00, 117.01it/s]
                                                                                                                                         
[DEBUG] Parameters after Step 5 (before square optimization):
    fx: 533.3333333333334
    px: 993.0
    py: 767.0
    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=1375.7 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: 332.7532: 0iter [00:00, ?iter/s]  [Ring mask] 25,731/25,731 points within ring radius 1375.7 px
[DEBUG] objective(x0) = 332.7532, picklable_objective(x0) = 332.9443

Best score: 332.9443: : 0iter [00:01, ?iter/s] 
Best score: 332.9443: : 1iter [00:01,  1.92s/iter]
Best score: 332.9443: : 1iter [00:01,  1.92s/iter]
Best score: 332.9443: : 2iter [00:02,  1.92s/iter]
Best score: 332.9443: : 3iter [00:02,  1.92s/iter]
Best score: 332.9443: : 4iter [00:02,  2.51iter/s]
Best score: 332.9443: : 4iter [00:02,  2.51iter/s]
Best score: 332.9443: : 5iter [00:02,  2.51iter/s]
Best score: 332.9443: : 6iter [00:02,  2.51iter/s]
Best score: 332.9443: : 7iter [00:02,  4.80iter/s]
Best score: 332.9443: : 7iter [00:02,  4.80iter/s]
Best score: 332.9443: : 8iter [00:02,  4.80iter/s]
Best score: 152.2824: : 9iter [00:02,  4.80iter/s]
Best score: 152.2824: : 10iter [00:02,  7.26iter/s]
Best score: 152.2824: : 10iter [00:02,  7.26iter/s]
Best score: 152.2824: : 11iter [00:02,  7.26iter/s]
Best score: 152.2824: : 12iter [00:02,  7.26iter/s]
Best score: 152.2824: : 13iter [00:02,  9.78iter/s]
Best score: 152.2824: : 13iter [00:02,  9.78iter/s]
Best score: 152.2824: : 14iter [00:02,  9.78iter/s]
Best score: 152.2824: : 15iter [00:02,  9.78iter/s]
Best score: 152.2824: : 16iter [00:02, 12.25iter/s]
Best score: 152.2824: : 16iter [00:02, 12.25iter/s]
Best score: 152.2824: : 17iter [00:02, 12.25iter/s]
Best score: 152.2824: : 18iter [00:02, 12.25iter/s]
Best score: 152.2824: : 19iter [00:02, 14.51iter/s]
Best score: 122.1351: : 19iter [00:02, 14.51iter/s]
Best score: 122.1351: : 20iter [00:02, 14.51iter/s]
Best score: 122.1351: : 21iter [00:02, 14.51iter/s]
Best score: 122.1351: : 22iter [00:02, 16.26iter/s]
Best score: 122.1351: : 22iter [00:02, 16.26iter/s]
Best score: 122.1351: : 23iter [00:02, 16.26iter/s]
Best score: 122.1351: : 24iter [00:02, 16.26iter/s]
Best score: 122.1351: : 25iter [00:02, 17.87iter/s]
Best score: 122.1351: : 25iter [00:03, 17.87iter/s]
Best score: 122.1351: : 26iter [00:03, 17.87iter/s]
Best score: 122.1351: : 27iter [00:03, 17.87iter/s]
Best score: 122.1351: : 28iter [00:03, 19.13iter/s]
Best score: 122.1351: : 28iter [00:03, 19.13iter/s]
Best score: 94.2988: : 29iter [00:03, 19.13iter/s] 
Best score: 94.2988: : 30iter [00:03, 19.13iter/s]
Best score: 94.2988: : 31iter [00:03, 19.89iter/s]
Best score: 94.2988: : 31iter [00:03, 19.89iter/s]
Best score: 94.2988: : 32iter [00:03, 19.89iter/s]
Best score: 94.2988: : 33iter [00:03, 19.89iter/s]
Best score: 94.2988: : 34iter [00:03, 20.65iter/s]
Best score: 94.2988: : 34iter [00:03, 20.65iter/s]
Best score: 94.2988: : 35iter [00:03, 20.65iter/s]
Best score: 94.2988: : 36iter [00:03, 20.65iter/s]
Best score: 94.2988: : 37iter [00:03, 21.16iter/s]
Best score: 94.2988: : 37iter [00:03, 21.16iter/s]
Best score: 94.2988: : 38iter [00:03, 21.16iter/s]
Best score: 53.0905: : 39iter [00:03, 21.16iter/s]
Best score: 53.0905: : 40iter [00:03, 21.33iter/s]
Best score: 53.0905: : 40iter [00:03, 21.33iter/s]
Best score: 53.0905: : 41iter [00:03, 21.33iter/s]
Best score: 53.0905: : 42iter [00:03, 21.33iter/s]
Best score: 53.0905: : 43iter [00:03, 21.64iter/s]
Best score: 53.0905: : 43iter [00:03, 21.64iter/s]
Best score: 53.0905: : 44iter [00:03, 21.64iter/s]
Best score: 53.0905: : 45iter [00:03, 21.64iter/s]
Best score: 53.0905: : 46iter [00:03, 21.92iter/s]
Best score: 53.0905: : 46iter [00:03, 21.92iter/s]
Best score: 53.0905: : 47iter [00:04, 21.92iter/s]
Best score: 53.0905: : 48iter [00:04, 21.92iter/s]
Best score: 53.0905: : 49iter [00:04, 22.19iter/s]
[ITER 50] Best: 25.5308
[PARAMS] Current best parameters:
  fx: 520.6156
  fy: 519.2806
  px: 975.1018
  py: 779.4002
  k1: 0.03378913
  k2: -0.00824786
  k3: -0.01760109
  k4: 0.00843838
  p1: 0.00630221
  p2: -0.00489968
  p3: -0.00847198
  p4: 0.00266379
  scale: 2.9909
  rotation: -0.0511

Best score: 25.5308: : 49iter [00:04, 22.19iter/s]
Best score: 25.5308: : 50iter [00:04, 22.19iter/s]
Best score: 25.5308: : 51iter [00:04, 22.19iter/s]
Best score: 25.5308: : 52iter [00:04, 22.07iter/s]
Best score: 25.5308: : 52iter [00:04, 22.07iter/s]
Best score: 25.5308: : 53iter [00:04, 22.07iter/s]
Best score: 25.5308: : 54iter [00:04, 22.07iter/s]
Best score: 25.5308: : 55iter [00:04, 22.21iter/s]
Best score: 25.5308: : 55iter [00:04, 22.21iter/s]
Best score: 25.5308: : 56iter [00:04, 22.21iter/s]
Best score: 25.5308: : 57iter [00:04, 22.21iter/s]
Best score: 25.5308: : 58iter [00:04, 22.40iter/s]
Best score: 25.5308: : 58iter [00:04, 22.40iter/s]
Best score: 25.2265: : 59iter [00:04, 22.40iter/s]
Best score: 25.2265: : 60iter [00:04, 22.40iter/s]
Best score: 25.2265: : 61iter [00:04, 22.28iter/s]
Best score: 25.2265: : 61iter [00:04, 22.28iter/s]
Best score: 25.2265: : 62iter [00:04, 22.28iter/s]
Best score: 25.2265: : 63iter [00:04, 22.28iter/s]
Best score: 25.2265: : 64iter [00:04, 22.41iter/s]
Best score: 25.2265: : 64iter [00:04, 22.41iter/s]
Best score: 25.2265: : 65iter [00:04, 22.41iter/s]
Best score: 25.2265: : 66iter [00:04, 22.41iter/s]
Best score: 25.2265: : 67iter [00:04, 22.54iter/s]
Best score: 25.2265: : 67iter [00:04, 22.54iter/s]
Best score: 25.2265: : 68iter [00:04, 22.54iter/s]
Best score: 13.7830: : 69iter [00:04, 22.54iter/s]
Best score: 13.7830: : 70iter [00:04, 22.35iter/s]
Best score: 13.7830: : 70iter [00:05, 22.35iter/s]
Best score: 13.7830: : 71iter [00:05, 22.35iter/s]
Best score: 13.7830: : 72iter [00:05, 22.35iter/s]
Best score: 13.7830: : 73iter [00:05, 22.49iter/s]
Best score: 13.7830: : 73iter [00:05, 22.49iter/s]
Best score: 13.7830: : 74iter [00:05, 22.49iter/s]
Best score: 13.7830: : 75iter [00:05, 22.49iter/s]
Best score: 13.7830: : 76iter [00:05, 22.51iter/s]
Best score: 13.7830: : 76iter [00:05, 22.51iter/s]
Best score: 13.7830: : 77iter [00:05, 22.51iter/s]
Best score: 13.7830: : 78iter [00:05, 22.51iter/s]
Best score: 13.7830: : 79iter [00:05, 22.53iter/s]
Best score: 7.5966: : 79iter [00:05, 22.53iter/s] 
Best score: 7.5966: : 80iter [00:05, 22.53iter/s]
Best score: 7.5966: : 81iter [00:05, 22.53iter/s]
Best score: 7.5966: : 82iter [00:05, 22.31iter/s]
Best score: 7.5966: : 82iter [00:05, 22.31iter/s]
Best score: 7.5966: : 83iter [00:05, 22.31iter/s]
Best score: 7.5966: : 84iter [00:05, 22.31iter/s]
Best score: 7.5966: : 85iter [00:05, 22.40iter/s]
Best score: 7.5966: : 85iter [00:05, 22.40iter/s]
Best score: 7.5966: : 86iter [00:05, 22.40iter/s]
Best score: 7.5966: : 87iter [00:05, 22.40iter/s]
Best score: 7.5966: : 88iter [00:05, 22.40iter/s]
Best score: 7.5966: : 88iter [00:05, 22.40iter/s]
Best score: 6.6006: : 89iter [00:05, 22.40iter/s]
Best score: 6.6006: : 90iter [00:05, 22.40iter/s]
Best score: 6.6006: : 91iter [00:05, 22.30iter/s]
Best score: 6.6006: : 91iter [00:05, 22.30iter/s]
Best score: 6.6006: : 92iter [00:06, 22.30iter/s]
Best score: 6.6006: : 93iter [00:06, 22.30iter/s]
Best score: 6.6006: : 94iter [00:06, 22.42iter/s]
Best score: 6.6006: : 94iter [00:06, 22.42iter/s]
Best score: 6.6006: : 95iter [00:06, 22.42iter/s]
Best score: 6.6006: : 96iter [00:06, 22.42iter/s]
Best score: 6.6006: : 97iter [00:06, 22.52iter/s]
Best score: 6.6006: : 97iter [00:06, 22.52iter/s]
Best score: 6.6006: : 98iter [00:06, 22.52iter/s]
[ITER 100] Best: 6.6006
[PARAMS] Current best parameters:
  fx: 550.8062
  fy: 549.6270
  px: 974.6702
  py: 778.8383
  k1: 0.01651259
  k2: 0.00672880
  k3: -0.03460309
  k4: 0.01179700
  p1: 0.00559256
  p2: -0.00684684
  p3: -0.00379218
  p4: -0.00177816
  scale: 2.8708
  rotation: -0.2949

Best score: 6.6006: : 99iter [00:06, 22.52iter/s]
Best score: 6.6006: : 100iter [00:06, 22.38iter/s]
Best score: 6.6006: : 100iter [00:06, 22.38iter/s]
Best score: 6.6006: : 101iter [00:06, 22.38iter/s]
Best score: 6.6006: : 102iter [00:06, 22.38iter/s]
Best score: 6.6006: : 103iter [00:06, 22.52iter/s]
Best score: 6.6006: : 103iter [00:06, 22.52iter/s]
Best score: 6.6006: : 104iter [00:06, 22.52iter/s]
Best score: 6.6006: : 105iter [00:06, 22.52iter/s]
Best score: 6.6006: : 106iter [00:06, 22.60iter/s]
Best score: 6.6006: : 106iter [00:06, 22.60iter/s]
Best score: 6.6006: : 107iter [00:06, 22.60iter/s]
Best score: 6.6006: : 108iter [00:06, 22.60iter/s]
Best score: 6.6006: : 109iter [00:06, 22.66iter/s]
Best score: 4.8198: : 109iter [00:06, 22.66iter/s]
Best score: 4.8198: : 110iter [00:06, 22.66iter/s]
Best score: 4.8198: : 111iter [00:06, 22.66iter/s]
Best score: 4.8198: : 112iter [00:06, 22.50iter/s]
Best score: 4.8198: : 112iter [00:06, 22.50iter/s]
Best score: 4.8198: : 113iter [00:06, 22.50iter/s]
Best score: 4.8198: : 114iter [00:06, 22.50iter/s]
Best score: 4.8198: : 115iter [00:06, 22.59iter/s]
Best score: 4.8198: : 115iter [00:07, 22.59iter/s]
Best score: 4.8198: : 116iter [00:07, 22.59iter/s]
Best score: 4.8198: : 117iter [00:07, 22.59iter/s]
Best score: 4.8198: : 118iter [00:07, 22.58iter/s]
Best score: 4.8198: : 118iter [00:07, 22.58iter/s]
Best score: 4.3171: : 119iter [00:07, 22.58iter/s]
Best score: 4.3171: : 120iter [00:07, 22.58iter/s]
Best score: 4.3171: : 121iter [00:07, 22.38iter/s]
Best score: 4.3171: : 121iter [00:07, 22.38iter/s]
Best score: 4.3171: : 122iter [00:07, 22.38iter/s]
Best score: 4.3171: : 123iter [00:07, 22.38iter/s]
Best score: 4.3171: : 124iter [00:07, 22.49iter/s]
Best score: 4.3171: : 124iter [00:07, 22.49iter/s]
Best score: 4.3171: : 125iter [00:07, 22.49iter/s]
Best score: 4.3171: : 126iter [00:07, 22.49iter/s]
Best score: 4.3171: : 127iter [00:07, 22.62iter/s]
Best score: 4.3171: : 127iter [00:07, 22.62iter/s]
Best score: 4.3171: : 128iter [00:07, 22.62iter/s]
Best score: 4.3171: : 129iter [00:07, 22.62iter/s]
Best score: 4.3171: : 130iter [00:07, 22.42iter/s]
Best score: 4.3171: : 130iter [00:07, 22.42iter/s]
Best score: 4.3171: : 131iter [00:07, 22.42iter/s]
Best score: 4.3171: : 132iter [00:07, 22.42iter/s]
Best score: 4.3171: : 133iter [00:07, 22.59iter/s]
Best score: 4.3171: : 133iter [00:07, 22.59iter/s]
Best score: 4.3171: : 134iter [00:07, 22.59iter/s]
Best score: 4.3171: : 135iter [00:07, 22.59iter/s]
Best score: 4.3171: : 136iter [00:07, 22.67iter/s]
Best score: 4.3171: : 136iter [00:07, 22.67iter/s]
Best score: 4.3171: : 137iter [00:08, 22.67iter/s]
Best score: 4.3171: : 138iter [00:08, 22.67iter/s]
Best score: 4.3171: : 139iter [00:08, 22.70iter/s]
Best score: 3.5629: : 139iter [00:08, 22.70iter/s]
Best score: 3.5629: : 140iter [00:08, 22.70iter/s]
Best score: 3.5629: : 141iter [00:08, 22.70iter/s]
Best score: 3.5629: : 142iter [00:08, 22.29iter/s]
Best score: 3.5629: : 142iter [00:08, 22.29iter/s]
Best score: 3.5629: : 143iter [00:08, 22.29iter/s]
Best score: 3.5629: : 144iter [00:08, 22.29iter/s]
Best score: 3.5629: : 145iter [00:08, 22.45iter/s]
Best score: 3.5629: : 145iter [00:08, 22.45iter/s]
Best score: 3.5629: : 146iter [00:08, 22.45iter/s]
Best score: 3.5629: : 147iter [00:08, 22.45iter/s]
Best score: 3.5629: : 148iter [00:08, 22.59iter/s]
Best score: 3.5629: : 148iter [00:08, 22.59iter/s]
[ITER 150] Best: 2.9037
[PARAMS] Current best parameters:
  fx: 554.8982
  fy: 554.5710
  px: 976.2783
  py: 778.6030
  k1: -0.03165530
  k2: 0.01998287
  k3: -0.01110845
  k4: 0.00187255
  p1: 0.00453824
  p2: -0.00636286
  p3: 0.00044141
  p4: -0.00066353
  scale: 2.9588
  rotation: -0.2231

Best score: 2.9037: : 149iter [00:08, 22.59iter/s]
Best score: 2.9037: : 150iter [00:08, 22.59iter/s]
Best score: 2.9037: : 151iter [00:08, 22.43iter/s]
Best score: 2.9037: : 151iter [00:08, 22.43iter/s]
Best score: 2.9037: : 152iter [00:08, 22.43iter/s]
Best score: 2.9037: : 153iter [00:08, 22.43iter/s]
Best score: 2.9037: : 154iter [00:08, 22.57iter/s]
Best score: 2.9037: : 154iter [00:08, 22.57iter/s]
Best score: 2.9037: : 155iter [00:08, 22.57iter/s]
Best score: 2.9037: : 156iter [00:08, 22.57iter/s]
Best score: 2.9037: : 157iter [00:08, 22.64iter/s]
Best score: 2.9037: : 157iter [00:08, 22.64iter/s]
Best score: 2.9037: : 158iter [00:08, 22.64iter/s]
Best score: 2.6569: : 159iter [00:08, 22.64iter/s]
Best score: 2.6569: : 160iter [00:08, 22.49iter/s]
Best score: 2.6569: : 160iter [00:09, 22.49iter/s]
Best score: 2.6569: : 161iter [00:09, 22.49iter/s]
Best score: 2.6569: : 162iter [00:09, 22.49iter/s]
Best score: 2.6569: : 163iter [00:09, 22.59iter/s]
Best score: 2.6569: : 163iter [00:09, 22.59iter/s]
Best score: 2.6569: : 164iter [00:09, 22.59iter/s]
Best score: 2.6569: : 165iter [00:09, 22.59iter/s]
Best score: 2.6569: : 166iter [00:09, 22.71iter/s]
Best score: 2.6569: : 166iter [00:09, 22.71iter/s]
Best score: 2.6569: : 167iter [00:09, 22.71iter/s]
Best score: 2.6569: : 168iter [00:09, 22.71iter/s]
Best score: 2.6569: : 169iter [00:09, 22.77iter/s]
Best score: 2.4670: : 169iter [00:09, 22.77iter/s]
Best score: 2.4670: : 170iter [00:09, 22.77iter/s]
Best score: 2.4670: : 171iter [00:09, 22.77iter/s]
Best score: 2.4670: : 172iter [00:09, 22.53iter/s]
Best score: 2.4670: : 172iter [00:09, 22.53iter/s]
Best score: 2.4670: : 173iter [00:09, 22.53iter/s]
Best score: 2.4670: : 174iter [00:09, 22.53iter/s]
Best score: 2.4670: : 175iter [00:09, 22.62iter/s]
Best score: 2.4670: : 175iter [00:09, 22.62iter/s]
Best score: 2.4670: : 176iter [00:09, 22.62iter/s]
Best score: 2.4670: : 177iter [00:09, 22.62iter/s]
Best score: 2.4670: : 178iter [00:09, 22.74iter/s]
Best score: 2.4670: : 178iter [00:09, 22.74iter/s]
Best score: 2.3520: : 179iter [00:09, 22.74iter/s]
Best score: 2.3520: : 180iter [00:09, 22.74iter/s]
Best score: 2.3520: : 181iter [00:09, 22.55iter/s]
Best score: 2.3520: : 181iter [00:09, 22.55iter/s]
Best score: 2.3520: : 182iter [00:10, 22.55iter/s]
Best score: 2.3520: : 183iter [00:10, 22.55iter/s]
Best score: 2.3520: : 184iter [00:10, 22.68iter/s]
Best score: 2.3520: : 184iter [00:10, 22.68iter/s]
Best score: 2.3520: : 185iter [00:10, 22.68iter/s]
Best score: 2.3520: : 186iter [00:10, 22.68iter/s]
Best score: 2.3520: : 187iter [00:10, 22.77iter/s]
Best score: 2.3520: : 187iter [00:10, 22.77iter/s]
Best score: 2.3520: : 188iter [00:10, 22.77iter/s]
Best score: 2.1716: : 189iter [00:10, 22.77iter/s]
Best score: 2.1716: : 190iter [00:10, 22.56iter/s]
Best score: 2.1716: : 190iter [00:10, 22.56iter/s]
Best score: 2.1716: : 191iter [00:10, 22.56iter/s]
Best score: 2.1716: : 192iter [00:10, 22.56iter/s]
Best score: 2.1716: : 193iter [00:10, 22.65iter/s]
Best score: 2.1716: : 193iter [00:10, 22.65iter/s]
Best score: 2.1716: : 194iter [00:10, 22.65iter/s]
Best score: 2.1716: : 195iter [00:10, 22.65iter/s]
Best score: 2.1716: : 196iter [00:10, 22.75iter/s]
Best score: 2.1716: : 196iter [00:10, 22.75iter/s]
Best score: 2.1716: : 197iter [00:10, 22.75iter/s]
Best score: 2.1716: : 198iter [00:10, 22.75iter/s]
Best score: 2.1716: : 199iter [00:10, 22.83iter/s]
[ITER 200] Best: 2.0544
[PARAMS] Current best parameters:
  fx: 572.2671
  fy: 572.3292
  px: 974.8687
  py: 781.3235
  k1: -0.06385513
  k2: 0.03676457
  k3: -0.01773916
  k4: 0.00333175
  p1: 0.00927932
  p2: -0.00998319
  p3: 0.00074638
  p4: -0.00007473
  scale: 2.9906
  rotation: -0.1239

Best score: 2.0544: : 199iter [00:10, 22.83iter/s]
Best score: 2.0544: : 200iter [00:10, 22.83iter/s]
Best score: 2.0544: : 201iter [00:10, 22.83iter/s]
Best score: 2.0544: : 202iter [00:10, 22.66iter/s]
Best score: 2.0544: : 202iter [00:10, 22.66iter/s]
Best score: 2.0544: : 203iter [00:10, 22.66iter/s]
Best score: 2.0544: : 204iter [00:10, 22.66iter/s]
Best score: 2.0544: : 205iter [00:10, 22.70iter/s]
Best score: 2.0544: : 205iter [00:11, 22.70iter/s]
Best score: 2.0544: : 206iter [00:11, 22.70iter/s]
Best score: 2.0544: : 207iter [00:11, 22.70iter/s]
Best score: 2.0544: : 208iter [00:11, 22.76iter/s]
Best score: 2.0544: : 208iter [00:11, 22.76iter/s]
Best score: 1.9494: : 209iter [00:11, 22.76iter/s]
Best score: 1.9494: : 210iter [00:11, 22.76iter/s]
Best score: 1.9494: : 211iter [00:11, 22.55iter/s]
Best score: 1.9494: : 211iter [00:11, 22.55iter/s]
Best score: 1.9494: : 212iter [00:11, 22.55iter/s]
Best score: 1.9494: : 213iter [00:11, 22.55iter/s]
Best score: 1.9494: : 214iter [00:11, 22.65iter/s]
Best score: 1.9494: : 214iter [00:11, 22.65iter/s]
Best score: 1.9494: : 215iter [00:11, 22.65iter/s]
Best score: 1.9494: : 216iter [00:11, 22.65iter/s]
Best score: 1.9494: : 217iter [00:11, 22.75iter/s]
Best score: 1.9494: : 217iter [00:11, 22.75iter/s]
Best score: 1.9494: : 218iter [00:11, 22.75iter/s]
Best score: 1.8819: : 219iter [00:11, 22.75iter/s]
Best score: 1.8819: : 220iter [00:11, 22.54iter/s]
Best score: 1.8819: : 220iter [00:11, 22.54iter/s]
Best score: 1.8819: : 221iter [00:11, 22.54iter/s]
Best score: 1.8819: : 222iter [00:11, 22.54iter/s]
Best score: 1.8819: : 223iter [00:11, 22.67iter/s]
Best score: 1.8819: : 223iter [00:11, 22.67iter/s]
Best score: 1.8819: : 224iter [00:11, 22.67iter/s]
Best score: 1.8819: : 225iter [00:11, 22.67iter/s]
Best score: 1.8819: : 226iter [00:11, 22.78iter/s]
Best score: 1.8819: : 226iter [00:11, 22.78iter/s]
Best score: 1.8819: : 227iter [00:11, 22.78iter/s]
Best score: 1.8819: : 228iter [00:12, 22.78iter/s]
Best score: 1.8819: : 229iter [00:12, 22.87iter/s]
Best score: 1.8819: : 229iter [00:12, 22.87iter/s]
Best score: 1.8819: : 230iter [00:12, 22.87iter/s]
Best score: 1.8819: : 231iter [00:12, 22.87iter/s]
Best score: 1.8819: : 232iter [00:12, 22.65iter/s]
Best score: 1.8819: : 232iter [00:12, 22.65iter/s]
Best score: 1.8819: : 233iter [00:12, 22.65iter/s]
Best score: 1.8819: : 234iter [00:12, 22.65iter/s]
Best score: 1.8819: : 235iter [00:12, 22.76iter/s]
Best score: 1.8819: : 235iter [00:12, 22.76iter/s]
Best score: 1.8819: : 236iter [00:12, 22.76iter/s]
Best score: 1.8819: : 237iter [00:12, 22.76iter/s]
Best score: 1.8819: : 238iter [00:12, 22.88iter/s]
Best score: 1.8819: : 238iter [00:12, 22.88iter/s]
Best score: 1.8304: : 239iter [00:12, 22.88iter/s]
Best score: 1.8304: : 240iter [00:12, 22.88iter/s]
Best score: 1.8304: : 241iter [00:12, 22.67iter/s]
Best score: 1.8304: : 241iter [00:12, 22.67iter/s]
Best score: 1.8304: : 242iter [00:12, 22.67iter/s]
Best score: 1.8304: : 243iter [00:12, 22.67iter/s]
Best score: 1.8304: : 244iter [00:12, 22.74iter/s]
Best score: 1.8304: : 244iter [00:12, 22.74iter/s]
Best score: 1.8304: : 245iter [00:12, 22.74iter/s]
Best score: 1.8304: : 246iter [00:12, 22.74iter/s]
Best score: 1.8304: : 247iter [00:12, 22.77iter/s]
Best score: 1.8304: : 247iter [00:12, 22.77iter/s]
Best score: 1.8304: : 248iter [00:12, 22.77iter/s]
[ITER 250] Best: 1.7978
[PARAMS] Current best parameters:
  fx: 567.6207
  fy: 567.1772
  px: 974.6941
  py: 781.6560
  k1: -0.05475056
  k2: 0.03487586
  k3: -0.01911594
  k4: 0.00381733
  p1: 0.00985834
  p2: -0.00999168
  p3: -0.00083968
  p4: 0.00043702
  scale: 2.9762
  rotation: -0.1705

Best score: 1.7978: : 249iter [00:12, 22.77iter/s]
Best score: 1.7978: : 250iter [00:12, 22.58iter/s]
Best score: 1.7978: : 250iter [00:13, 22.58iter/s]
Best score: 1.7978: : 251iter [00:13, 22.58iter/s]
Best score: 1.7978: : 252iter [00:13, 22.58iter/s]
Best score: 1.7978: : 253iter [00:13, 22.72iter/s]
Best score: 1.7978: : 253iter [00:13, 22.72iter/s]
Best score: 1.7978: : 254iter [00:13, 22.72iter/s]
Best score: 1.7978: : 255iter [00:13, 22.72iter/s]
Best score: 1.7978: : 256iter [00:13, 22.81iter/s]
Best score: 1.7978: : 256iter [00:13, 22.81iter/s]
Best score: 1.7978: : 257iter [00:13, 22.81iter/s]
Best score: 1.7978: : 258iter [00:13, 22.81iter/s]
Best score: 1.7978: : 259iter [00:13, 22.86iter/s]
Best score: 1.7957: : 259iter [00:13, 22.86iter/s]
Best score: 1.7957: : 260iter [00:13, 22.86iter/s]
Best score: 1.7957: : 261iter [00:13, 22.86iter/s]
Best score: 1.7957: : 262iter [00:13, 22.67iter/s]
Best score: 1.7957: : 262iter [00:13, 22.67iter/s]
Best score: 1.7957: : 263iter [00:13, 22.67iter/s]
Best score: 1.7957: : 264iter [00:13, 22.67iter/s]
Best score: 1.7957: : 265iter [00:13, 22.75iter/s]
Best score: 1.7957: : 265iter [00:13, 22.75iter/s]
Best score: 1.7957: : 266iter [00:13, 22.75iter/s]
Best score: 1.7957: : 267iter [00:13, 22.75iter/s]
Best score: 1.7957: : 268iter [00:13, 22.78iter/s]
Best score: 1.7957: : 268iter [00:13, 22.78iter/s]
Best score: 1.7649: : 269iter [00:13, 22.78iter/s]
Best score: 1.7649: : 270iter [00:13, 22.78iter/s]
Best score: 1.7649: : 271iter [00:13, 22.58iter/s]
Best score: 1.7649: : 271iter [00:13, 22.58iter/s]
Best score: 1.7649: : 272iter [00:13, 22.58iter/s]
Best score: 1.7649: : 273iter [00:14, 22.58iter/s]
Best score: 1.7649: : 274iter [00:14, 22.71iter/s]
Best score: 1.7649: : 274iter [00:14, 22.71iter/s]
Best score: 1.7649: : 275iter [00:14, 22.71iter/s]
Best score: 1.7649: : 276iter [00:14, 22.71iter/s]
Best score: 1.7649: : 277iter [00:14, 22.76iter/s]
Best score: 1.7649: : 277iter [00:14, 22.76iter/s]
Best score: 1.7649: : 278iter [00:14, 22.76iter/s]
Best score: 1.7544: : 279iter [00:14, 22.76iter/s]
Best score: 1.7544: : 280iter [00:14, 22.61iter/s]
Best score: 1.7544: : 280iter [00:14, 22.61iter/s]
Best score: 1.7544: : 281iter [00:14, 22.61iter/s]
Best score: 1.7544: : 282iter [00:14, 22.61iter/s]
Best score: 1.7544: : 283iter [00:14, 22.73iter/s]
Best score: 1.7544: : 283iter [00:14, 22.73iter/s]
Best score: 1.7544: : 284iter [00:14, 22.73iter/s]
Best score: 1.7544: : 285iter [00:14, 22.73iter/s]
Best score: 1.7544: : 286iter [00:14, 22.79iter/s]
Best score: 1.7544: : 286iter [00:14, 22.79iter/s]
Best score: 1.7544: : 287iter [00:14, 22.79iter/s]
Best score: 1.7544: : 288iter [00:14, 22.79iter/s]
Best score: 1.7544: : 289iter [00:14, 22.83iter/s]
Best score: 1.7384: : 289iter [00:14, 22.83iter/s]
Best score: 1.7384: : 290iter [00:14, 22.83iter/s]
Best score: 1.7384: : 291iter [00:14, 22.83iter/s]
Best score: 1.7384: : 292iter [00:14, 22.64iter/s]
Best score: 1.7384: : 292iter [00:14, 22.64iter/s]
Best score: 1.7384: : 293iter [00:14, 22.64iter/s]
Best score: 1.7384: : 294iter [00:14, 22.64iter/s]
Best score: 1.7384: : 295iter [00:14, 22.76iter/s]
Best score: 1.7384: : 295iter [00:14, 22.76iter/s]
Best score: 1.7384: : 296iter [00:15, 22.76iter/s]
Best score: 1.7384: : 297iter [00:15, 22.76iter/s]
Best score: 1.7384: : 298iter [00:15, 22.87iter/s]
Best score: 1.7384: : 298iter [00:15, 22.87iter/s]
[ITER 300] Best: 1.7384
[PARAMS] Current best parameters:
  fx: 565.6650
  fy: 565.3593
  px: 974.5951
  py: 781.5452
  k1: -0.05250111
  k2: 0.03503341
  k3: -0.01816600
  k4: 0.00314699
  p1: 0.00996020
  p2: -0.00995467
  p3: -0.00021271
  p4: -0.00045003
  scale: 2.9643
  rotation: -0.1912

Best score: 1.7384: : 299iter [00:15, 22.87iter/s]
Best score: 1.7384: : 300iter [00:15, 22.87iter/s]
Best score: 1.7384: : 301iter [00:15, 22.63iter/s]
Best score: 1.7384: : 301iter [00:15, 22.63iter/s]
Best score: 1.7384: : 302iter [00:15, 22.63iter/s]
Best score: 1.7384: : 303iter [00:15, 22.63iter/s]
Best score: 1.7384: : 304iter [00:15, 22.70iter/s]
Best score: 1.7384: : 304iter [00:15, 22.70iter/s]
Best score: 1.7384: : 305iter [00:15, 22.70iter/s]
Best score: 1.7384: : 306iter [00:15, 22.70iter/s]
Best score: 1.7384: : 307iter [00:15, 22.78iter/s]
Best score: 1.7384: : 307iter [00:15, 22.78iter/s]
Best score: 1.7384: : 308iter [00:15, 22.78iter/s]
Best score: 1.7189: : 309iter [00:15, 22.78iter/s]
Best score: 1.7189: : 310iter [00:15, 22.64iter/s]
Best score: 1.7189: : 310iter [00:15, 22.64iter/s]
Best score: 1.7189: : 311iter [00:15, 22.64iter/s]
Best score: 1.7189: : 312iter [00:15, 22.64iter/s]
Best score: 1.7189: : 313iter [00:15, 22.69iter/s]
Best score: 1.7189: : 313iter [00:15, 22.69iter/s]
Best score: 1.7189: : 314iter [00:15, 22.69iter/s]
Best score: 1.7189: : 315iter [00:15, 22.69iter/s]
Best score: 1.7189: : 316iter [00:15, 22.77iter/s]
Best score: 1.7189: : 316iter [00:15, 22.77iter/s]
Best score: 1.7189: : 317iter [00:15, 22.77iter/s]
Best score: 1.7189: : 318iter [00:15, 22.77iter/s]
Best score: 1.7189: : 319iter [00:15, 22.87iter/s]
Best score: 1.7189: : 319iter [00:16, 22.87iter/s]
Best score: 1.7189: : 320iter [00:16, 22.87iter/s]
Best score: 1.7189: : 321iter [00:16, 22.87iter/s]
Best score: 1.7189: : 322iter [00:16, 22.66iter/s]
Best score: 1.7189: : 322iter [00:16, 22.66iter/s]
Best score: 1.7189: : 323iter [00:16, 22.66iter/s]
Best score: 1.7189: : 324iter [00:16, 22.66iter/s]
Best score: 1.7189: : 325iter [00:16, 22.74iter/s]
Best score: 1.7189: : 325iter [00:16, 22.74iter/s]
Best score: 1.7189: : 326iter [00:16, 22.74iter/s]
Best score: 1.7189: : 327iter [00:16, 22.74iter/s]
Best score: 1.7189: : 328iter [00:16, 22.83iter/s]
Best score: 1.7189: : 328iter [00:16, 22.83iter/s]
Best score: 1.7155: : 329iter [00:16, 22.83iter/s]
Best score: 1.7155: : 330iter [00:16, 22.83iter/s]
Best score: 1.7155: : 331iter [00:16, 22.69iter/s]
Best score: 1.7155: : 331iter [00:16, 22.69iter/s]
Best score: 1.7155: : 332iter [00:16, 22.69iter/s]
Best score: 1.7155: : 333iter [00:16, 22.69iter/s]
Best score: 1.7155: : 334iter [00:16, 22.75iter/s]
Best score: 1.7155: : 334iter [00:16, 22.75iter/s]
Best score: 1.7155: : 335iter [00:16, 22.75iter/s]
Best score: 1.7155: : 336iter [00:16, 22.75iter/s]
Best score: 1.7155: : 337iter [00:16, 22.78iter/s]
Best score: 1.7155: : 337iter [00:16, 22.78iter/s]
Best score: 1.7155: : 338iter [00:16, 22.78iter/s]
Best score: 1.7011: : 339iter [00:16, 22.78iter/s]
Best score: 1.7011: : 340iter [00:16, 22.62iter/s]
Best score: 1.7011: : 340iter [00:16, 22.62iter/s]
Best score: 1.7011: : 341iter [00:17, 22.62iter/s]
Best score: 1.7011: : 342iter [00:17, 22.62iter/s]
Best score: 1.7011: : 343iter [00:17, 22.68iter/s]
Best score: 1.7011: : 343iter [00:17, 22.68iter/s]
Best score: 1.7011: : 344iter [00:17, 22.68iter/s]
Best score: 1.7011: : 345iter [00:17, 22.68iter/s]
Best score: 1.7011: : 346iter [00:17, 22.74iter/s]
Best score: 1.7011: : 346iter [00:17, 22.74iter/s]
Best score: 1.7011: : 347iter [00:17, 22.74iter/s]
Best score: 1.7011: : 348iter [00:17, 22.74iter/s]
Best score: 1.7011: : 349iter [00:17, 22.78iter/s]
[ITER 350] Best: 1.6968
[PARAMS] Current best parameters:
  fx: 556.9252
  fy: 556.5212
  px: 974.6409
  py: 781.7560
  k1: -0.03940174
  k2: 0.03326527
  k3: -0.02109744
  k4: 0.00430495
  p1: 0.00999066
  p2: -0.00998624
  p3: 0.00090950
  p4: -0.00078549
  scale: 2.9612
  rotation: -0.1835

Best score: 1.6968: : 349iter [00:17, 22.78iter/s]
Best score: 1.6968: : 350iter [00:17, 22.78iter/s]
Best score: 1.6968: : 351iter [00:17, 22.78iter/s]
Best score: 1.6968: : 352iter [00:17, 22.63iter/s]
Best score: 1.6968: : 352iter [00:17, 22.63iter/s]
Best score: 1.6968: : 353iter [00:17, 22.63iter/s]
Best score: 1.6968: : 354iter [00:17, 22.63iter/s]
Best score: 1.6968: : 355iter [00:17, 22.72iter/s]
Best score: 1.6968: : 355iter [00:17, 22.72iter/s]
Best score: 1.6968: : 356iter [00:17, 22.72iter/s]
Best score: 1.6968: : 357iter [00:17, 22.72iter/s]
Best score: 1.6968: : 358iter [00:17, 22.78iter/s]
Best score: 1.6968: : 358iter [00:17, 22.78iter/s]
Best score: 1.6851: : 359iter [00:17, 22.78iter/s]
Best score: 1.6851: : 360iter [00:17, 22.78iter/s]
Best score: 1.6851: : 361iter [00:17, 22.61iter/s]
Best score: 1.6851: : 361iter [00:17, 22.61iter/s]
Best score: 1.6851: : 362iter [00:17, 22.61iter/s]
Best score: 1.6851: : 363iter [00:17, 22.61iter/s]
Best score: 1.6851: : 364iter [00:17, 22.74iter/s]
Best score: 1.6851: : 364iter [00:18, 22.74iter/s]
Best score: 1.6851: : 365iter [00:18, 22.74iter/s]
Best score: 1.6851: : 366iter [00:18, 22.74iter/s]
Best score: 1.6851: : 367iter [00:18, 22.79iter/s]
Best score: 1.6851: : 367iter [00:18, 22.79iter/s]
Best score: 1.6851: : 368iter [00:18, 22.79iter/s]
Best score: 1.6569: : 369iter [00:18, 22.79iter/s]
Best score: 1.6569: : 370iter [00:18, 22.60iter/s]
Best score: 1.6569: : 370iter [00:18, 22.60iter/s]
Best score: 1.6569: : 371iter [00:18, 22.60iter/s]
Best score: 1.6569: : 372iter [00:18, 22.60iter/s]
Best score: 1.6569: : 373iter [00:18, 22.73iter/s]
Best score: 1.6569: : 373iter [00:18, 22.73iter/s]
Best score: 1.6569: : 374iter [00:18, 22.73iter/s]
Best score: 1.6569: : 375iter [00:18, 22.73iter/s]
Best score: 1.6569: : 376iter [00:18, 22.72iter/s]
Best score: 1.6569: : 376iter [00:18, 22.72iter/s]
Best score: 1.6569: : 377iter [00:18, 22.72iter/s]
Best score: 1.6569: : 378iter [00:18, 22.72iter/s]
Best score: 1.6569: : 379iter [00:18, 22.76iter/s]
Best score: 1.6486: : 379iter [00:18, 22.76iter/s]
Best score: 1.6486: : 380iter [00:18, 22.76iter/s]
Best score: 1.6486: : 381iter [00:18, 22.76iter/s]
Best score: 1.6486: : 382iter [00:18, 22.51iter/s]
Best score: 1.6486: : 382iter [00:18, 22.51iter/s]
Best score: 1.6486: : 383iter [00:18, 22.51iter/s]
Best score: 1.6486: : 384iter [00:18, 22.51iter/s]
Best score: 1.6486: : 385iter [00:18, 22.61iter/s]
Best score: 1.6486: : 385iter [00:18, 22.61iter/s]
Best score: 1.6486: : 386iter [00:18, 22.61iter/s]
Best score: 1.6486: : 387iter [00:19, 22.61iter/s]
Best score: 1.6486: : 388iter [00:19, 22.68iter/s]
Best score: 1.6486: : 388iter [00:19, 22.68iter/s]
Best score: 1.6438: : 389iter [00:19, 22.68iter/s]
Best score: 1.6438: : 390iter [00:19, 22.68iter/s]
Best score: 1.6438: : 391iter [00:19, 22.42iter/s]
Best score: 1.6438: : 391iter [00:19, 22.42iter/s]
Best score: 1.6438: : 392iter [00:19, 22.42iter/s]
Best score: 1.6438: : 393iter [00:19, 22.42iter/s]
Best score: 1.6438: : 394iter [00:19, 22.50iter/s]
Best score: 1.6438: : 394iter [00:19, 22.50iter/s]
Best score: 1.6438: : 395iter [00:19, 22.50iter/s]
Best score: 1.6438: : 396iter [00:19, 22.50iter/s]
Best score: 1.6438: : 397iter [00:19, 22.54iter/s]
Best score: 1.6438: : 397iter [00:19, 22.54iter/s]
Best score: 1.6438: : 398iter [00:19, 22.54iter/s]
[ITER 400] Best: 1.6407
[PARAMS] Current best parameters:
  fx: 535.6560
  fy: 535.4050
  px: 974.3790
  py: 781.8199
  k1: -0.04588759
  k2: 0.07608633
  k3: -0.04625966
  k4: 0.00908007
  p1: 0.00998638
  p2: -0.00993646
  p3: 0.00025729
  p4: -0.00081665
  scale: 2.9942
  rotation: -0.1732

Best score: 1.6407: : 399iter [00:19, 22.54iter/s]
Best score: 1.6407: : 400iter [00:19, 22.40iter/s]
Best score: 1.6407: : 400iter [00:19, 22.40iter/s]
Best score: 1.6407: : 401iter [00:19, 22.40iter/s]
Best score: 1.6407: : 402iter [00:19, 22.40iter/s]
Best score: 1.6407: : 403iter [00:19, 22.54iter/s]
Best score: 1.6407: : 403iter [00:19, 22.54iter/s]
Best score: 1.6407: : 404iter [00:19, 22.54iter/s]
Best score: 1.6407: : 405iter [00:19, 22.54iter/s]
Best score: 1.6407: : 406iter [00:19, 22.57iter/s]
Best score: 1.6407: : 406iter [00:19, 22.57iter/s]
Best score: 1.6407: : 407iter [00:19, 22.57iter/s]
Best score: 1.6407: : 408iter [00:19, 22.57iter/s]
Best score: 1.6407: : 409iter [00:19, 22.64iter/s]
Best score: 1.6366: : 409iter [00:20, 22.64iter/s]
Best score: 1.6366: : 410iter [00:20, 22.64iter/s]
Best score: 1.6366: : 411iter [00:20, 22.64iter/s]
Best score: 1.6366: : 412iter [00:20, 22.45iter/s]
Best score: 1.6366: : 412iter [00:20, 22.45iter/s]
Best score: 1.6366: : 413iter [00:20, 22.45iter/s]
Best score: 1.6366: : 414iter [00:20, 22.45iter/s]
Best score: 1.6366: : 415iter [00:20, 22.49iter/s]
Best score: 1.6366: : 415iter [00:20, 22.49iter/s]
Best score: 1.6366: : 416iter [00:20, 22.49iter/s]
Best score: 1.6366: : 417iter [00:20, 22.49iter/s]
Best score: 1.6366: : 418iter [00:20, 22.54iter/s]
Best score: 1.6366: : 418iter [00:20, 22.54iter/s]
Best score: 1.6330: : 419iter [00:20, 22.54iter/s]
Best score: 1.6330: : 420iter [00:20, 22.54iter/s]
Best score: 1.6330: : 421iter [00:20, 22.42iter/s]
Best score: 1.6330: : 421iter [00:20, 22.42iter/s]
Best score: 1.6330: : 422iter [00:20, 22.42iter/s]
Best score: 1.6330: : 423iter [00:20, 22.42iter/s]
Best score: 1.6330: : 424iter [00:20, 22.55iter/s]
Best score: 1.6330: : 424iter [00:20, 22.55iter/s]
Best score: 1.6330: : 425iter [00:20, 22.55iter/s]
Best score: 1.6330: : 426iter [00:20, 22.55iter/s]
Best score: 1.6330: : 427iter [00:20, 18.30iter/s]
Best score: 1.6330: : 427iter [00:20, 18.30iter/s]
Best score: 1.6330: : 428iter [00:20, 18.30iter/s]
Best score: 1.6279: : 429iter [00:21, 18.30iter/s]
Best score: 1.6279: : 430iter [00:21, 19.34iter/s]
Best score: 1.6279: : 430iter [00:21, 19.34iter/s]
Best score: 1.6279: : 431iter [00:21, 19.34iter/s]
Best score: 1.6279: : 432iter [00:21, 19.34iter/s]
Best score: 1.6279: : 433iter [00:21, 20.28iter/s]
Best score: 1.6279: : 433iter [00:21, 20.28iter/s]
Best score: 1.6279: : 434iter [00:21, 20.28iter/s]
Best score: 1.6279: : 435iter [00:21, 20.28iter/s]
Best score: 1.6279: : 436iter [00:21, 20.95iter/s]
Best score: 1.6279: : 436iter [00:21, 20.95iter/s]
Best score: 1.6279: : 437iter [00:21, 20.95iter/s]
Best score: 1.6279: : 438iter [00:21, 20.95iter/s]
Best score: 1.6279: : 439iter [00:21, 21.51iter/s]
Best score: 1.6230: : 439iter [00:21, 21.51iter/s]
Best score: 1.6230: : 440iter [00:21, 21.51iter/s]
Best score: 1.6230: : 441iter [00:21, 21.51iter/s]
Best score: 1.6230: : 442iter [00:21, 21.72iter/s]
Best score: 1.6230: : 442iter [00:21, 21.72iter/s]
Best score: 1.6230: : 443iter [00:21, 21.72iter/s]
Best score: 1.6230: : 444iter [00:21, 21.72iter/s]
Best score: 1.6230: : 445iter [00:21, 22.09iter/s]
Best score: 1.6230: : 445iter [00:21, 22.09iter/s]
Best score: 1.6230: : 446iter [00:21, 22.09iter/s]
Best score: 1.6230: : 447iter [00:21, 22.09iter/s]
Best score: 1.6230: : 448iter [00:21, 22.30iter/s]
Best score: 1.6230: : 448iter [00:21, 22.30iter/s]
[ITER 450] Best: 1.6194
[PARAMS] Current best parameters:
  fx: 527.0941
  fy: 526.8306
  px: 974.2969
  py: 781.8718
  k1: -0.04021852
  k2: 0.07861710
  k3: -0.04744354
  k4: 0.00920131
  p1: 0.00997007
  p2: -0.00998889
  p3: 0.00032023
  p4: -0.00072289
  scale: 3.0071
  rotation: -0.1738

Best score: 1.6194: : 449iter [00:21, 22.30iter/s]
Best score: 1.6194: : 450iter [00:21, 22.30iter/s]
Best score: 1.6194: : 451iter [00:21, 22.25iter/s]
Best score: 1.6194: : 451iter [00:21, 22.25iter/s]
Best score: 1.6194: : 452iter [00:22, 22.25iter/s]
Best score: 1.6194: : 453iter [00:22, 22.25iter/s]
Best score: 1.6194: : 454iter [00:22, 22.39iter/s]
Best score: 1.6194: : 454iter [00:22, 22.39iter/s]
Best score: 1.6194: : 455iter [00:22, 22.39iter/s]
Best score: 1.6194: : 456iter [00:22, 22.39iter/s]
Best score: 1.6194: : 457iter [00:22, 22.46iter/s]
Best score: 1.6194: : 457iter [00:22, 22.46iter/s]
Best score: 1.6194: : 458iter [00:22, 22.46iter/s]
Best score: 1.6151: : 459iter [00:22, 22.46iter/s]
Best score: 1.6151: : 460iter [00:22, 22.26iter/s]
Best score: 1.6151: : 460iter [00:22, 22.26iter/s]
Best score: 1.6151: : 461iter [00:22, 22.26iter/s]
Best score: 1.6151: : 462iter [00:22, 22.26iter/s]
Best score: 1.6151: : 463iter [00:22, 22.43iter/s]
Best score: 1.6151: : 463iter [00:22, 22.43iter/s]
Best score: 1.6151: : 464iter [00:22, 22.43iter/s]
Best score: 1.6151: : 465iter [00:22, 22.43iter/s]
Best score: 1.6151: : 466iter [00:22, 22.46iter/s]
Best score: 1.6151: : 466iter [00:22, 22.46iter/s]
Best score: 1.6151: : 467iter [00:22, 22.46iter/s]
Best score: 1.6151: : 468iter [00:22, 22.46iter/s]
Best score: 1.6151: : 469iter [00:22, 22.53iter/s]
Best score: 1.6127: : 469iter [00:22, 22.53iter/s]
Best score: 1.6127: : 470iter [00:22, 22.53iter/s]
Best score: 1.6127: : 471iter [00:22, 22.53iter/s]
Best score: 1.6127: : 472iter [00:22, 22.42iter/s]
Best score: 1.6127: : 472iter [00:22, 22.42iter/s]
Best score: 1.6127: : 473iter [00:22, 22.42iter/s]
Best score: 1.6127: : 474iter [00:22, 22.42iter/s]
Best score: 1.6127: : 475iter [00:22, 22.64iter/s]
Best score: 1.6127: : 475iter [00:23, 22.64iter/s]
Best score: 1.6127: : 476iter [00:23, 22.64iter/s]
Best score: 1.6127: : 477iter [00:23, 22.64iter/s]
Best score: 1.6127: : 478iter [00:23, 22.72iter/s]
Best score: 1.6127: : 478iter [00:23, 22.72iter/s]
Best score: 1.6035: : 479iter [00:23, 22.72iter/s]
Best score: 1.6035: : 480iter [00:23, 22.72iter/s]
Best score: 1.6035: : 481iter [00:23, 22.52iter/s]
Best score: 1.6035: : 481iter [00:23, 22.52iter/s]
Best score: 1.6035: : 482iter [00:23, 22.52iter/s]
Best score: 1.6035: : 483iter [00:23, 22.52iter/s]
Best score: 1.6035: : 484iter [00:23, 22.64iter/s]
Best score: 1.6035: : 484iter [00:23, 22.64iter/s]
Best score: 1.6035: : 485iter [00:23, 22.64iter/s]
Best score: 1.6035: : 486iter [00:23, 22.64iter/s]
Best score: 1.6035: : 487iter [00:23, 22.70iter/s]
Best score: 1.6035: : 487iter [00:23, 22.70iter/s]
Best score: 1.6035: : 488iter [00:23, 22.70iter/s]
Best score: 1.5985: : 489iter [00:23, 22.70iter/s]
Best score: 1.5985: : 490iter [00:23, 22.62iter/s]
Best score: 1.5985: : 490iter [00:23, 22.62iter/s]
Best score: 1.5985: : 491iter [00:23, 22.62iter/s]
Best score: 1.5985: : 492iter [00:23, 22.62iter/s]
Best score: 1.5985: : 493iter [00:23, 22.72iter/s]
Best score: 1.5985: : 493iter [00:23, 22.72iter/s]
Best score: 1.5985: : 494iter [00:23, 22.72iter/s]
Best score: 1.5985: : 495iter [00:23, 22.72iter/s]
Best score: 1.5985: : 496iter [00:23, 22.84iter/s]
Best score: 1.5985: : 496iter [00:23, 22.84iter/s]
Best score: 1.5985: : 497iter [00:24, 22.84iter/s]
Best score: 1.5985: : 498iter [00:24, 22.84iter/s]
Best score: 1.5985: : 499iter [00:24, 22.91iter/s]
[ITER 500] Best: 1.5880
[PARAMS] Current best parameters:
  fx: 515.7860
  fy: 515.5656
  px: 974.1301
  py: 781.9707
  k1: -0.01829665
  k2: 0.06527738
  k3: -0.04121827
  k4: 0.00791573
  p1: 0.00999718
  p2: -0.00999141
  p3: 0.00016658
  p4: -0.00065602
  scale: 2.9932
  rotation: -0.1520

Best score: 1.5880: : 499iter [00:24, 22.91iter/s]
Best score: 1.5880: : 500iter [00:24, 20.75iter/s]

[📈] Running L-BFGS-B polish after 500 DE iterations...
  Polish improved score: 1.587957 -> 1.584320
  Success: True
  Tangential distortion: p1=0.010000, p2=-0.010000, p3=0.000166, p4=-0.000659
  ✓ Tangential correction is significant for corner improvement
[✅] Square reference optimization complete. Score: 1.5843
[✅] Parameters copied to: /working/MDC101_W036_2025-12-31/calibration/params.json
[📌] Selecting best parameters...
[✅] Saved final refined parameters.


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


[DEBUG] Parameters being applied to PTD conversion:
    fx: 515.7860292205551
    fy: 515.5655849690464
    px: 974.1301528693934
    py: 781.9707356505188
    k1: -0.018291845619892857
    k2: 0.06527962398869694
    k3: -0.04121293578263903
    k4: 0.007913070300808558
    p1: 0.01
    p2: -0.01
    p3: 0.00016556395684660507
    p4: -0.0006585136736578798
    scale: 2.9933211984060146
    rotation: -0.15205919990569192
    mmpp: 1.2721213450338371
    nmpp: 1272121.345033837

[🔄] Converting 417 frames to PTD, creating debug images for 200 calibration frames...

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

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   🔄 500:  73%|███████▎  | 148/204 [00:00<00:00, 179.62frame/s]

   🔄 500:  81%|████████▏ | 166/204 [00:00<00:00, 178.88frame/s]

   🔄 500:  90%|█████████ | 184/204 [00:01<00:00, 178.49frame/s]

   🔄 500:  99%|█████████▉| 202/204 [00:01<00:00, 178.02frame/s]

                                                                
📁 Rigs:  50%|█████     | 1/2 [00:02<00:02,  2.10s/rig]

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   🔄 1000:  68%|██████▊   | 145/213 [00:00<00:00, 177.73frame/s]

   🔄 1000:  77%|███████▋  | 163/213 [00:00<00:00, 178.29frame/s]

   🔄 1000:  85%|████████▌ | 182/213 [00:01<00:00, 178.92frame/s]

   🔄 1000:  94%|█████████▍| 200/213 [00:01<00:00, 178.37frame/s]

                                                                 
📁 Rigs: 100%|██████████| 2/2 [00:04<00:00,  2.12s/rig]
📁 Rigs: 100%|██████████| 2/2 [00:04<00:00,  2.11s/rig]
[✅] Saved PTDs: /working/MDC101_W036_2025-12-31/calibration/debug/3_undistorted/output/ptd

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

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   🔄 500:  18%|█▊        | 18/100 [00:00<00:00, 178.21frame/s]

   🔄 500:  36%|███▌      | 36/100 [00:00<00:00, 176.07frame/s]

   🔄 500:  55%|█████▌    | 55/100 [00:00<00:00, 177.99frame/s]

   🔄 500:  74%|███████▍  | 74/100 [00:00<00:00, 179.49frame/s]

   🔄 500:  92%|█████████▏| 92/100 [00:00<00:00, 178.15frame/s]

                                                               
📁 Rigs:  50%|█████     | 1/2 [00:00<00:00,  1.00rig/s]

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

   🔄 1000:  18%|█▊        | 18/100 [00:00<00:00, 178.26frame/s]

   🔄 1000:  36%|███▌      | 36/100 [00:00<00:00, 177.61frame/s]

   🔄 1000:  54%|█████▍    | 54/100 [00:00<00:00, 176.32frame/s]

   🔄 1000:  72%|███████▏  | 72/100 [00:00<00:00, 177.24frame/s]

   🔄 1000:  90%|█████████ | 90/100 [00:00<00:00, 177.96frame/s]

                                                                
📁 Rigs: 100%|██████████| 2/2 [00:02<00:00,  1.02s/rig]
📁 Rigs: 100%|██████████| 2/2 [00:02<00:00,  1.02s/rig]
[✅] Saved PTDs: /working/MDC101_W036_2025-12-31/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]
📤 Writing LUT:   3%|▎         | 81191/3080448 [00:00<00:03, 811901.10px/s]
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📤 Writing LUT:   8%|▊         | 259946/3080448 [00:00<00:03, 878203.54px/s]
📤 Writing LUT:  11%|█▏        | 350990/3080448 [00:00<00:03, 890927.90px/s]
📤 Writing LUT:  14%|█▍        | 441436/3080448 [00:00<00:02, 895804.11px/s]
📤 Writing LUT:  17%|█▋        | 532453/3080448 [00:00<00:02, 900688.06px/s]
📤 Writing LUT:  20%|██        | 624601/3080448 [00:00<00:02, 907483.57px/s]
📤 Writing LUT:  23%|██▎       | 717174/3080448 [00:00<00:02, 913291.23px/s]
📤 Writing LUT:  26%|██▋       | 809738/3080448 [00:00<00:02, 917149.85px/s]
📤 Writing LUT:  29%|██▉       | 901453/3080448 [00:01<00:02, 911431.80px/s]
📤 Writing LUT:  32%|███▏      | 992605/3080448 [00:01<00:02, 903553.98px/s]
📤 Writing LUT:  35%|███▌      | 1082978/3080448 [00:01<00:02, 900667.13px/s]
📤 Writing LUT:  38%|███▊      | 1173828/3080448 [00:01<00:02, 903018.55px/s]
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📤 Writing LUT:  50%|████▉     | 1536541/3080448 [00:01<00:01, 905543.50px/s]
📤 Writing LUT:  53%|█████▎    | 1628574/3080448 [00:01<00:01, 909973.36px/s]
📤 Writing LUT:  56%|█████▌    | 1721494/3080448 [00:01<00:01, 915734.45px/s]
📤 Writing LUT:  59%|█████▉    | 1813211/3080448 [00:02<00:01, 916161.83px/s]
📤 Writing LUT:  62%|██████▏   | 1905121/3080448 [00:02<00:01, 917039.88px/s]
📤 Writing LUT:  65%|██████▍   | 1996828/3080448 [00:02<00:01, 912369.05px/s]
📤 Writing LUT:  68%|██████▊   | 2088606/3080448 [00:02<00:01, 913982.52px/s]
📤 Writing LUT:  71%|███████   | 2180843/3080448 [00:02<00:00, 916489.71px/s]
📤 Writing LUT:  74%|███████▍  | 2272497/3080448 [00:02<00:00, 915183.92px/s]
📤 Writing LUT:  77%|███████▋  | 2364399/3080448 [00:02<00:00, 916331.69px/s]
📤 Writing LUT:  80%|███████▉  | 2456035/3080448 [00:02<00:00, 914149.67px/s]
📤 Writing LUT:  83%|████████▎ | 2547453/3080448 [00:02<00:00, 912290.23px/s]
📤 Writing LUT:  86%|████████▌ | 2639833/3080448 [00:02<00:00, 915729.07px/s]
📤 Writing LUT:  89%|████████▊ | 2731765/3080448 [00:03<00:00, 916801.43px/s]
📤 Writing LUT:  92%|█████████▏| 2824945/3080448 [00:03<00:00, 921283.22px/s]
📤 Writing LUT:  95%|█████████▍| 2917076/3080448 [00:03<00:00, 918697.04px/s]
📤 Writing LUT:  98%|█████████▊| 3008949/3080448 [00:03<00:00, 916184.75px/s]
📤 Writing LUT: 100%|██████████| 3080448/3080448 [00:03<00:00, 908753.61px/s]
[✅] LUT written to: /working/MDC101_W036_2025-12-31/calibration/debug/3_undistorted/output/LUT.lut
[WARN] Folder name 'MDC101_W036_2025-12-31' does not match expected pattern MDC042_W007_5_28_2025. Using simple naming convention.
[✅] LUT copied to: /working/MDC101_W036_2025-12-31/calibration/MDC101_W036_2025-12-31_unknown.lut

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


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

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

   🔥 500:   7%|▋         | 15/204 [00:00<00:01, 147.40frame/s]

   🔥 500:  15%|█▌        | 31/204 [00:00<00:01, 153.16frame/s]

   🔥 500:  23%|██▎       | 47/204 [00:00<00:01, 154.01frame/s]

   🔥 500:  31%|███       | 63/204 [00:00<00:00, 154.47frame/s]

   🔥 500:  39%|███▊      | 79/204 [00:00<00:00, 154.58frame/s]

   🔥 500:  47%|████▋     | 95/204 [00:00<00:00, 156.07frame/s]

   🔥 500:  55%|█████▍    | 112/204 [00:00<00:00, 158.23frame/s]

   🔥 500:  64%|██████▎   | 130/204 [00:00<00:00, 162.50frame/s]

   🔥 500:  72%|███████▏  | 147/204 [00:00<00:00, 160.38frame/s]

   🔥 500:  80%|████████  | 164/204 [00:01<00:00, 158.91frame/s]

   🔥 500:  88%|████████▊ | 180/204 [00:01<00:00, 157.90frame/s]

   🔥 500:  96%|█████████▌| 196/204 [00:01<00:00, 157.17frame/s]

                                                                [✅] 500: /working/MDC101_W036_2025-12-31/calibration/debug/4_heatmap/500_heatmap.png

📁 Rigs (heatmap):  50%|█████     | 1/2 [00:01<00:01,  1.76s/rig]

   🔥 1000:   0%|          | 0/213 [00:00<?, ?frame/s]

   🔥 1000:   8%|▊         | 16/213 [00:00<00:01, 153.77frame/s]

   🔥 1000:  15%|█▌        | 32/213 [00:00<00:01, 155.62frame/s]

   🔥 1000:  23%|██▎       | 48/213 [00:00<00:01, 156.35frame/s]

   🔥 1000:  30%|███       | 64/213 [00:00<00:00, 157.01frame/s]

   🔥 1000:  38%|███▊      | 80/213 [00:00<00:00, 156.43frame/s]

   🔥 1000:  45%|████▌     | 96/213 [00:00<00:00, 155.64frame/s]

   🔥 1000:  53%|█████▎    | 112/213 [00:00<00:00, 154.86frame/s]

   🔥 1000:  60%|██████    | 128/213 [00:00<00:00, 154.86frame/s]

   🔥 1000:  68%|██████▊   | 144/213 [00:00<00:00, 155.23frame/s]

   🔥 1000:  75%|███████▌  | 160/213 [00:01<00:00, 155.84frame/s]

   🔥 1000:  83%|████████▎ | 176/213 [00:01<00:00, 156.43frame/s]

   🔥 1000:  90%|█████████ | 192/213 [00:01<00:00, 156.83frame/s]

   🔥 1000:  98%|█████████▊| 208/213 [00:01<00:00, 157.11frame/s]

                                                                 [✅] 1000: /working/MDC101_W036_2025-12-31/calibration/debug/4_heatmap/1000_heatmap.png

📁 Rigs (heatmap): 100%|██████████| 2/2 [00:03<00:00,  1.88s/rig]
📁 Rigs (heatmap): 100%|██████████| 2/2 [00:03<00:00,  1.86s/rig]
[✅] all_rigs_average.png
[✅] all_rigs_best.png
[✅] Heatmaps saved to: /working/MDC101_W036_2025-12-31/calibration/debug/4_heatmap
[🏁] Finished processing MDC101_W036_2025-12-31


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