2026-05-06T17:58:54 - INFO: Slick 0.0.8a10

🟢 Starting Calibration Pipeline

=== Processing STLC-083WF_W028(6)_2026-02-04 ===
2026-05-06T17:58:54 - WARNING: Camera or wand ID mismatch between laser tracks
2026-05-06T17:58:54 - INFO: Camera ID: 083WF
2026-05-06T17:58:54 - INFO: Wand ID: 00001f0c2bd7
2026-05-06T17:58:54 - INFO: Recorded At: 2026-02-03T23:25:14Z

-------------------------------------------------------------------
                        Step 1: Digitization                       
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[🔄] Full PTD mode: Processing ALL images then creating calibration subset
[📸] Digitizing ALL images...
[📸] Full dataset mode: Processing ALL images (no debug visualizations)
[INFO] Found 4 las0.zip files to process
Processing Rigs:   0%|          | 0/4 [00:00<?, ?it/s][INFO] Filtered 340 stationary frames, 335 remain

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                                                                           [A[PASS2] Frame 0000298: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000461: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000462: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000463: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000464: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000463: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Summary: 3 frames fixed, 2 untrusted, 334 total

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                                                                           [A
[TIMING] 1500 — 335 frames
  Phase 1  radial detect   (parallel)  :   5.32s  (15.9 ms/frame)
  Phase 2a corner detect   (parallel)  :   2.57s  (7.7 ms/frame)
  Phase 2b corner fix      (sequential):   0.27s
  Phase 3  finalize        (sequential):   6.32s  (18.9 ms/frame)
    decode + undistort                 :   3.36s  (10.0 ms/frame)
    corner apply + refinement          :   1.34s  (4.0 ms/frame)
    segment                            :   1.33s  (4.0 ms/frame)
    smooth                             :   0.19s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  14.48s

Processing Rigs:  25%|██▌       | 1/4 [00:16<00:50, 16.96s/it][INFO] Filtered 305 stationary frames, 370 remain

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                                                                            [A[PASS2] Frame 0000196: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000197: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000198: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000199: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000469: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000470: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000471: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000472: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000753: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000754: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000755: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000756: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000471: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000755: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Summary: 6 frames fixed, 8 untrusted, 369 total

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                                                                            [A
[TIMING] 2000L — 370 frames
  Phase 1  radial detect   (parallel)  :   5.86s  (15.8 ms/frame)
  Phase 2a corner detect   (parallel)  :   3.02s  (8.2 ms/frame)
  Phase 2b corner fix      (sequential):   0.43s
  Phase 3  finalize        (sequential):   7.04s  (19.0 ms/frame)
    decode + undistort                 :   3.61s  (9.7 ms/frame)
    corner apply + refinement          :   1.63s  (4.4 ms/frame)
    segment                            :   1.47s  (4.0 ms/frame)
    smooth                             :   0.21s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  16.34s

Processing Rigs:  50%|█████     | 2/4 [00:35<00:35, 17.98s/it][INFO] Filtered 225 stationary frames, 200 remain

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                                                                           [A[PASS2] Frame 0000227: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000241: fixed corners {0, 2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000242: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000243: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000244: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000247: fixed corners {0, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000371: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000372: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000373: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000374: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000413: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000414: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000415: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000416: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000417: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000242: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000243: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000247: fixed corners {0, 3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000373: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000241: fixed corners {0} (was_fixed=False, trusted=False)
[PASS2] Frame 0000247: fixed corners {0, 3} (was_fixed=False, trusted=False)
[PASS2] Summary: 9 frames fixed, 7 untrusted, 199 total

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                                                                           [A
[TIMING] 1000 — 200 frames
  Phase 1  radial detect   (parallel)  :   3.98s  (19.9 ms/frame)
  Phase 2a corner detect   (parallel)  :   2.36s  (11.9 ms/frame)
  Phase 2b corner fix      (sequential):   0.35s
  Phase 3  finalize        (sequential):   3.38s  (16.9 ms/frame)
    decode + undistort                 :   1.73s  (8.6 ms/frame)
    corner apply + refinement          :   0.71s  (3.5 ms/frame)
    segment                            :   0.77s  (3.9 ms/frame)
    smooth                             :   0.11s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  10.08s

Processing Rigs:  75%|███████▌  | 3/4 [00:47<00:15, 15.08s/it][INFO] Filtered 570 stationary frames, 594 remain

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                                                                            [A[PASS2] Frame 0000549: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000550: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000551: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000552: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000939: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000940: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000941: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000954: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000955: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000956: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000957: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000990: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000991: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000992: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000993: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001249: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001250: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0001251: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0001252: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000551: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000956: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000992: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001251: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Summary: 10 frames fixed, 11 untrusted, 593 total

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                                                                            [A
[TIMING] 2000R — 594 frames
  Phase 1  radial detect   (parallel)  :   9.49s  (16.0 ms/frame)
  Phase 2a corner detect   (parallel)  :   4.65s  (7.8 ms/frame)
  Phase 2b corner fix      (sequential):   0.68s
  Phase 3  finalize        (sequential):  11.26s  (19.0 ms/frame)
    decode + undistort                 :   5.65s  (9.5 ms/frame)
    corner apply + refinement          :   2.74s  (4.6 ms/frame)
    segment                            :   2.35s  (4.0 ms/frame)
    smooth                             :   0.33s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  26.07s

Processing Rigs: 100%|██████████| 4/4 [01:17<00:00, 21.05s/it]Processing Rigs: 100%|██████████| 4/4 [01:17<00:00, 19.37s/it]
[💾] Saved RigFrameDataset to /working/STLC-083WF_W028(6)_2026-02-04/calibration/debug/1_digitized_full/rig_frames_full.json
[✅] Saved full dataset: 1495 frames from 4 rigs to /working/STLC-083WF_W028(6)_2026-02-04/calibration/debug/1_digitized_full/rig_frames_full.json
[💾] Saved RigFrameDataset to /working/STLC-083WF_W028(6)_2026-02-04/calibration/debug/1_digitized_full/rig_frames_full.json
[📋] Creating calibration subset (100 frames/rig) with visualizations...
[📋] 1500: 100 frames selected from 334
[📋] 2000L: 100 frames selected from 369
[📋] 1000: 100 frames selected from 199
[📋] 2000R: 100 frames selected from 593
[💾] Saved RigFrameDataset to /working/STLC-083WF_W028(6)_2026-02-04/calibration/debug/1_digitized/rig_frames.json
[INFO] Reloading dataset from disk to ensure clean state for multiprocessing...
[📂] Loaded RigFrameDataset from /working/STLC-083WF_W028(6)_2026-02-04/calibration/debug/1_digitized/rig_frames.json

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

-> Calculating the casing center ...
[INFO] Using 80 total sampled bright frames
Computing max image from bright frames:   0%|          | 0/80 [00:00<?, ?it/s]Computing max image from bright frames:   1%|▏         | 1/80 [00:02<03:53,  2.96s/it]Computing max image from bright frames:   2%|▎         | 2/80 [00:05<03:49,  2.94s/it]Computing max image from bright frames:   4%|▍         | 3/80 [00:08<03:46,  2.95s/it]Computing max image from bright frames:   5%|▌         | 4/80 [00:11<03:42,  2.92s/it]Computing max image from bright frames:   6%|▋         | 5/80 [00:14<03:39,  2.92s/it]Computing max image from bright frames:   8%|▊         | 6/80 [00:17<03:36,  2.93s/it]Computing max image from bright frames:   9%|▉         | 7/80 [00:20<03:32,  2.91s/it]Computing max image from bright frames:  10%|█         | 8/80 [00:23<03:26,  2.87s/it]Computing max image from bright frames:  11%|█▏        | 9/80 [00:25<03:20,  2.83s/it]Computing max image from bright frames:  12%|█▎        | 10/80 [00:28<03:15,  2.79s/it]Computing max image from bright frames:  14%|█▍        | 11/80 [00:31<03:09,  2.74s/it]Computing max image from bright frames:  15%|█▌        | 12/80 [00:33<03:04,  2.72s/it]Computing max image from bright frames:  16%|█▋        | 13/80 [00:36<02:58,  2.66s/it]Computing max image from bright frames:  18%|█▊        | 14/80 [00:39<02:55,  2.66s/it]Computing max image from bright frames:  19%|█▉        | 15/80 [00:41<02:52,  2.66s/it]Computing max image from bright frames:  20%|██        | 16/80 [00:44<02:49,  2.65s/it]Computing max image from bright frames:  21%|██▏       | 17/80 [00:47<02:51,  2.72s/it]Computing max image from bright frames:  22%|██▎       | 18/80 [00:50<02:54,  2.81s/it]Computing max image from bright frames:  24%|██▍       | 19/80 [00:53<02:53,  2.84s/it]Computing max image from bright frames:  25%|██▌       | 20/80 [00:56<02:52,  2.88s/it]Computing max image from bright frames:  26%|██▋       | 21/80 [00:59<02:50,  2.90s/it]Computing max image from bright frames:  28%|██▊       | 22/80 [01:02<02:48,  2.90s/it]Computing max image from bright frames:  29%|██▉       | 23/80 [01:05<02:46,  2.92s/it]Computing max image from bright frames:  30%|███       | 24/80 [01:07<02:43,  2.92s/it]Computing max image from bright frames:  31%|███▏      | 25/80 [01:10<02:40,  2.92s/it]Computing max image from bright frames:  32%|███▎      | 26/80 [01:13<02:38,  2.93s/it]Computing max image from bright frames:  34%|███▍      | 27/80 [01:16<02:34,  2.92s/it]Computing max image from bright frames:  35%|███▌      | 28/80 [01:19<02:28,  2.86s/it]Computing max image from bright frames:  36%|███▋      | 29/80 [01:22<02:23,  2.81s/it]Computing max image from bright frames:  38%|███▊      | 30/80 [01:24<02:18,  2.78s/it]Computing max image from bright frames:  39%|███▉      | 31/80 [01:27<02:15,  2.76s/it]Computing max image from bright frames:  40%|████      | 32/80 [01:30<02:12,  2.76s/it]Computing max image from bright frames:  41%|████▏     | 33/80 [01:33<02:08,  2.74s/it]Computing max image from bright frames:  42%|████▎     | 34/80 [01:35<02:05,  2.73s/it]Computing max image from bright frames:  44%|████▍     | 35/80 [01:38<02:03,  2.74s/it]Computing max image from bright frames:  45%|████▌     | 36/80 [01:41<02:00,  2.74s/it]Computing max image from bright frames:  46%|████▋     | 37/80 [01:44<02:00,  2.79s/it]Computing max image from bright frames:  48%|████▊     | 38/80 [01:47<01:59,  2.84s/it]Computing max image from bright frames:  49%|████▉     | 39/80 [01:50<01:58,  2.88s/it]Computing max image from bright frames:  50%|█████     | 40/80 [01:53<01:56,  2.91s/it]Computing max image from bright frames:  51%|█████▏    | 41/80 [01:55<01:53,  2.91s/it]Computing max image from bright frames:  52%|█████▎    | 42/80 [01:58<01:51,  2.93s/it]Computing max image from bright frames:  54%|█████▍    | 43/80 [02:01<01:48,  2.94s/it]Computing max image from bright frames:  55%|█████▌    | 44/80 [02:04<01:46,  2.95s/it]Computing max image from bright frames:  56%|█████▋    | 45/80 [02:08<01:54,  3.26s/it]Computing max image from bright frames:  57%|█████▊    | 46/80 [02:13<02:04,  3.66s/it]Computing max image from bright frames:  59%|█████▉    | 47/80 [02:16<01:58,  3.58s/it]Computing max image from bright frames:  60%|██████    | 48/80 [02:19<01:46,  3.32s/it]Computing max image from bright frames:  61%|██████▏   | 49/80 [02:22<01:40,  3.24s/it]Computing max image from bright frames:  62%|██████▎   | 50/80 [02:27<01:51,  3.71s/it]Computing max image from bright frames:  64%|██████▍   | 51/80 [02:31<01:47,  3.70s/it]Computing max image from bright frames:  65%|██████▌   | 52/80 [02:33<01:35,  3.40s/it]Computing max image from bright frames:  66%|██████▋   | 53/80 [02:36<01:26,  3.19s/it]Computing max image from bright frames:  68%|██████▊   | 54/80 [02:39<01:18,  3.03s/it]Computing max image from bright frames:  69%|██████▉   | 55/80 [02:41<01:12,  2.91s/it]Computing max image from bright frames:  70%|███████   | 56/80 [02:44<01:11,  2.96s/it]Computing max image from bright frames:  71%|███████▏  | 57/80 [02:47<01:07,  2.94s/it]Computing max image from bright frames:  72%|███████▎  | 58/80 [02:50<01:04,  2.94s/it]Computing max image from bright frames:  74%|███████▍  | 59/80 [02:53<01:01,  2.93s/it]Computing max image from bright frames:  75%|███████▌  | 60/80 [02:56<00:58,  2.93s/it]Computing max image from bright frames:  76%|███████▋  | 61/80 [02:59<00:55,  2.93s/it]Computing max image from bright frames:  78%|███████▊  | 62/80 [03:02<00:52,  2.93s/it]Computing max image from bright frames:  79%|███████▉  | 63/80 [03:05<00:49,  2.93s/it]Computing max image from bright frames:  80%|████████  | 64/80 [03:08<00:46,  2.92s/it]Computing max image from bright frames:  81%|████████▏ | 65/80 [03:11<00:43,  2.92s/it]Computing max image from bright frames:  82%|████████▎ | 66/80 [03:14<00:40,  2.92s/it]Computing max image from bright frames:  84%|████████▍ | 67/80 [03:16<00:36,  2.84s/it]Computing max image from bright frames:  85%|████████▌ | 68/80 [03:19<00:33,  2.80s/it]Computing max image from bright frames:  86%|████████▋ | 69/80 [03:22<00:30,  2.79s/it]Computing max image from bright frames:  88%|████████▊ | 70/80 [03:24<00:27,  2.76s/it]Computing max image from bright frames:  89%|████████▉ | 71/80 [03:27<00:24,  2.73s/it]Computing max image from bright frames:  90%|█████████ | 72/80 [03:30<00:21,  2.72s/it]Computing max image from bright frames:  91%|█████████▏| 73/80 [03:32<00:18,  2.71s/it]Computing max image from bright frames:  92%|█████████▎| 74/80 [03:35<00:16,  2.70s/it]Computing max image from bright frames:  94%|█████████▍| 75/80 [03:38<00:13,  2.70s/it]Computing max image from bright frames:  95%|█████████▌| 76/80 [03:40<00:10,  2.68s/it]Computing max image from bright frames:  96%|█████████▋| 77/80 [03:43<00:08,  2.68s/it]Computing max image from bright frames:  98%|█████████▊| 78/80 [03:46<00:05,  2.69s/it]Computing max image from bright frames:  99%|█████████▉| 79/80 [03:49<00:02,  2.69s/it]Computing max image from bright frames: 100%|██████████| 80/80 [03:51<00:00,  2.77s/it]                                                                                       [✅] Casing detection complete: cx=877.0, cy=964.0

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

  0%|          | 0/100 [00:00<?, ?it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   0%|          | 0/100 [00:00<?, ?it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   1%|          | 1/100 [00:00<00:25,  3.89it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   1%|          | 1/100 [00:00<00:25,  3.89it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 314.141} (0.000):   2%|▏         | 2/100 [00:00<00:25,  3.89it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 321.212} (0.000):   3%|▎         | 3/100 [00:00<00:24,  3.89it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 321.212} (0.000):   4%|▍         | 4/100 [00:00<00:07, 12.05it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 328.283} (0.000):   4%|▍         | 4/100 [00:00<00:07, 12.05it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 335.354} (0.000):   5%|▌         | 5/100 [00:00<00:07, 12.05it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 342.424} (0.000):   6%|▌         | 6/100 [00:00<00:07, 12.05it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.000 | Best: {'fx': 342.424} (0.000):   7%|▋         | 7/100 [00:00<00:05, 16.21it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.001 | Best: {'fx': 349.495} (0.001):   7%|▋         | 7/100 [00:00<00:05, 16.21it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.001 | Best: {'fx': 356.566} (0.001):   8%|▊         | 8/100 [00:00<00:05, 16.21it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.001 | Best: {'fx': 356.566} (0.001):   9%|▉         | 9/100 [00:00<00:05, 16.88it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.001 | Best: {'fx': 363.636} (0.001):   9%|▉         | 9/100 [00:00<00:05, 16.88it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.002 | Best: {'fx': 370.707} (0.002):  10%|█         | 10/100 [00:00<00:05, 16.88it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.002 | Best: {'fx': 370.707} (0.002):  11%|█         | 11/100 [00:00<00:06, 14.42it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.003 | Best: {'fx': 384.848} (0.003):  11%|█         | 11/100 [00:00<00:06, 14.42it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.002 | Best: {'fx': 384.848} (0.003):  12%|█▏        | 12/100 [00:00<00:06, 14.42it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.004 | Best: {'fx': 391.919} (0.004):  13%|█▎        | 13/100 [00:00<00:06, 14.42it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.004 | Best: {'fx': 398.99} (0.004):  14%|█▍        | 14/100 [00:00<00:05, 14.42it/s] Brute | Start: {'fx': 500.0} (0.039) | Current: 0.004 | Best: {'fx': 398.99} (0.004):  15%|█▌        | 15/100 [00:00<00:04, 19.37it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.004 | Best: {'fx': 406.061} (0.004):  15%|█▌        | 15/100 [00:00<00:04, 19.37it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.005 | Best: {'fx': 413.131} (0.005):  16%|█▌        | 16/100 [00:00<00:04, 19.37it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.005 | Best: {'fx': 420.202} (0.005):  17%|█▋        | 17/100 [00:01<00:04, 19.37it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.005 | Best: {'fx': 420.202} (0.005):  18%|█▊        | 18/100 [00:01<00:03, 20.82it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.006 | Best: {'fx': 427.273} (0.006):  18%|█▊        | 18/100 [00:01<00:03, 20.82it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.007 | Best: {'fx': 434.343} (0.007):  19%|█▉        | 19/100 [00:01<00:03, 20.82it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.008 | Best: {'fx': 441.414} (0.008):  20%|██        | 20/100 [00:01<00:03, 20.82it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.008 | Best: {'fx': 441.414} (0.008):  21%|██        | 21/100 [00:01<00:03, 21.49it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.010 | Best: {'fx': 448.485} (0.010):  21%|██        | 21/100 [00:01<00:03, 21.49it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.012 | Best: {'fx': 455.556} (0.012):  22%|██▏       | 22/100 [00:01<00:03, 21.49it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.014 | Best: {'fx': 462.626} (0.014):  23%|██▎       | 23/100 [00:01<00:03, 21.49it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.014 | Best: {'fx': 462.626} (0.014):  24%|██▍       | 24/100 [00:01<00:03, 21.82it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.017 | Best: {'fx': 469.697} (0.017):  24%|██▍       | 24/100 [00:01<00:03, 21.82it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 476.768} (0.020):  25%|██▌       | 25/100 [00:01<00:03, 21.82it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.024 | Best: {'fx': 483.838} (0.024):  26%|██▌       | 26/100 [00:01<00:03, 21.82it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.024 | Best: {'fx': 483.838} (0.024):  27%|██▋       | 27/100 [00:01<00:03, 21.26it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.031 | Best: {'fx': 490.909} (0.031):  27%|██▋       | 27/100 [00:01<00:03, 21.26it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.044 | Best: {'fx': 505.051} (0.044):  28%|██▊       | 28/100 [00:01<00:03, 21.26it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.037 | Best: {'fx': 505.051} (0.044):  29%|██▉       | 29/100 [00:01<00:03, 21.26it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.037 | Best: {'fx': 505.051} (0.044):  30%|███       | 30/100 [00:01<00:03, 22.66it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.054 | Best: {'fx': 512.121} (0.054):  30%|███       | 30/100 [00:01<00:03, 22.66it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.071 | Best: {'fx': 519.192} (0.071):  31%|███       | 31/100 [00:01<00:03, 22.66it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.114 | Best: {'fx': 533.333} (0.114):  32%|███▏      | 32/100 [00:01<00:03, 22.66it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.114 | Best: {'fx': 533.333} (0.114):  33%|███▎      | 33/100 [00:01<00:04, 15.56it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.087 | Best: {'fx': 533.333} (0.114):  33%|███▎      | 33/100 [00:01<00:04, 15.56it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.068 | Best: {'fx': 533.333} (0.114):  34%|███▍      | 34/100 [00:02<00:04, 15.56it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.097 | Best: {'fx': 533.333} (0.114):  35%|███▌      | 35/100 [00:02<00:04, 15.56it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.058 | Best: {'fx': 533.333} (0.114):  36%|███▌      | 36/100 [00:02<00:04, 15.56it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.058 | Best: {'fx': 533.333} (0.114):  37%|███▋      | 37/100 [00:02<00:03, 18.60it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.045 | Best: {'fx': 533.333} (0.114):  37%|███▋      | 37/100 [00:02<00:03, 18.60it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.042 | Best: {'fx': 533.333} (0.114):  38%|███▊      | 38/100 [00:02<00:03, 18.60it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.036 | Best: {'fx': 533.333} (0.114):  39%|███▉      | 39/100 [00:02<00:03, 18.60it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.036 | Best: {'fx': 533.333} (0.114):  40%|████      | 40/100 [00:02<00:03, 19.03it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.038 | Best: {'fx': 533.333} (0.114):  40%|████      | 40/100 [00:02<00:03, 19.03it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.051 | Best: {'fx': 533.333} (0.114):  41%|████      | 41/100 [00:02<00:03, 19.03it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.033 | Best: {'fx': 533.333} (0.114):  42%|████▏     | 42/100 [00:02<00:03, 19.03it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.031 | Best: {'fx': 533.333} (0.114):  43%|████▎     | 43/100 [00:02<00:02, 19.03it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.031 | Best: {'fx': 533.333} (0.114):  44%|████▍     | 44/100 [00:02<00:02, 19.41it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.034 | Best: {'fx': 533.333} (0.114):  44%|████▍     | 44/100 [00:02<00:02, 19.41it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.029 | Best: {'fx': 533.333} (0.114):  45%|████▌     | 45/100 [00:02<00:02, 19.41it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.031 | Best: {'fx': 533.333} (0.114):  46%|████▌     | 46/100 [00:02<00:02, 19.41it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.031 | Best: {'fx': 533.333} (0.114):  47%|████▋     | 47/100 [00:02<00:02, 20.85it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.027 | Best: {'fx': 533.333} (0.114):  47%|████▋     | 47/100 [00:02<00:02, 20.85it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.028 | Best: {'fx': 533.333} (0.114):  48%|████▊     | 48/100 [00:02<00:02, 20.85it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.027 | Best: {'fx': 533.333} (0.114):  49%|████▉     | 49/100 [00:02<00:02, 20.85it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.026 | Best: {'fx': 533.333} (0.114):  50%|█████     | 50/100 [00:02<00:02, 20.85it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.026 | Best: {'fx': 533.333} (0.114):  51%|█████     | 51/100 [00:02<00:02, 23.85it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.026 | Best: {'fx': 533.333} (0.114):  51%|█████     | 51/100 [00:02<00:02, 23.85it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.025 | Best: {'fx': 533.333} (0.114):  52%|█████▏    | 52/100 [00:02<00:02, 23.85it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.024 | Best: {'fx': 533.333} (0.114):  53%|█████▎    | 53/100 [00:02<00:01, 23.85it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.024 | Best: {'fx': 533.333} (0.114):  54%|█████▍    | 54/100 [00:02<00:02, 20.57it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.024 | Best: {'fx': 533.333} (0.114):  54%|█████▍    | 54/100 [00:02<00:02, 20.57it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.023 | Best: {'fx': 533.333} (0.114):  55%|█████▌    | 55/100 [00:02<00:02, 20.57it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.023 | Best: {'fx': 533.333} (0.114):  56%|█████▌    | 56/100 [00:02<00:02, 20.57it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.023 | Best: {'fx': 533.333} (0.114):  57%|█████▋    | 57/100 [00:02<00:01, 22.18it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.022 | Best: {'fx': 533.333} (0.114):  57%|█████▋    | 57/100 [00:02<00:01, 22.18it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.114):  58%|█████▊    | 58/100 [00:02<00:01, 22.18it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.022 | Best: {'fx': 533.333} (0.114):  59%|█████▉    | 59/100 [00:03<00:01, 22.18it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.114):  60%|██████    | 60/100 [00:03<00:01, 22.18it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.114):  61%|██████    | 61/100 [00:03<00:01, 25.56it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.114):  61%|██████    | 61/100 [00:03<00:01, 25.56it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.114):  62%|██████▏   | 62/100 [00:03<00:01, 25.56it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.114):  63%|██████▎   | 63/100 [00:03<00:01, 25.56it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.021 | Best: {'fx': 533.333} (0.114):  64%|██████▍   | 64/100 [00:03<00:01, 25.56it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.114):  65%|██████▌   | 65/100 [00:03<00:01, 25.56it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.022 | Best: {'fx': 533.333} (0.114):  66%|██████▌   | 66/100 [00:03<00:01, 25.56it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.022 | Best: {'fx': 533.333} (0.114):  67%|██████▋   | 67/100 [00:03<00:01, 28.98it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.114):  67%|██████▋   | 67/100 [00:03<00:01, 28.98it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.114):  68%|██████▊   | 68/100 [00:03<00:01, 28.98it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.114):  69%|██████▉   | 69/100 [00:03<00:01, 28.98it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.022 | Best: {'fx': 533.333} (0.114):  70%|███████   | 70/100 [00:03<00:01, 28.98it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.114):  71%|███████   | 71/100 [00:03<00:01, 28.98it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.114):  72%|███████▏  | 72/100 [00:03<00:00, 33.27it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.020 | Best: {'fx': 533.333} (0.114):  72%|███████▏  | 72/100 [00:03<00:00, 33.27it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.114):  73%|███████▎  | 73/100 [00:03<00:00, 33.27it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.114):  74%|███████▍  | 74/100 [00:03<00:00, 33.27it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.114):  75%|███████▌  | 75/100 [00:03<00:00, 33.27it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.114):  76%|███████▌  | 76/100 [00:03<00:00, 33.97it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.114):  76%|███████▌  | 76/100 [00:03<00:00, 33.97it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.114):  77%|███████▋  | 77/100 [00:03<00:00, 33.97it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.114):  78%|███████▊  | 78/100 [00:03<00:00, 33.97it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.114):  79%|███████▉  | 79/100 [00:03<00:00, 33.97it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.114):  80%|████████  | 80/100 [00:03<00:00, 31.88it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.114):  80%|████████  | 80/100 [00:03<00:00, 31.88it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.114):  81%|████████  | 81/100 [00:03<00:00, 31.88it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.114):  82%|████████▏ | 82/100 [00:03<00:00, 31.88it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.114):  83%|████████▎ | 83/100 [00:03<00:00, 31.88it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.114):  84%|████████▍ | 84/100 [00:03<00:00, 30.17it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.114):  84%|████████▍ | 84/100 [00:03<00:00, 30.17it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.019 | Best: {'fx': 533.333} (0.114):  85%|████████▌ | 85/100 [00:03<00:00, 30.17it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.114):  86%|████████▌ | 86/100 [00:03<00:00, 30.17it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.114):  87%|████████▋ | 87/100 [00:03<00:00, 30.17it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.114):  88%|████████▊ | 88/100 [00:03<00:00, 29.34it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.114):  88%|████████▊ | 88/100 [00:03<00:00, 29.34it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.114):  89%|████████▉ | 89/100 [00:04<00:00, 29.34it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.114):  90%|█████████ | 90/100 [00:04<00:00, 29.34it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.114):  91%|█████████ | 91/100 [00:04<00:00, 29.34it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.114):  92%|█████████▏| 92/100 [00:04<00:00, 21.61it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.114):  92%|█████████▏| 92/100 [00:04<00:00, 21.61it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.114):  93%|█████████▎| 93/100 [00:04<00:00, 21.61it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.114):  94%|█████████▍| 94/100 [00:04<00:00, 21.61it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.114):  95%|█████████▌| 95/100 [00:04<00:00, 21.61it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.114):  96%|█████████▌| 96/100 [00:04<00:00, 21.61it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.114):  97%|█████████▋| 97/100 [00:04<00:00, 26.20it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.114):  97%|█████████▋| 97/100 [00:04<00:00, 26.20it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.114):  98%|█████████▊| 98/100 [00:04<00:00, 26.20it/s]Brute | Start: {'fx': 500.0} (0.039) | Current: 0.018 | Best: {'fx': 533.333} (0.114):  99%|█████████▉| 99/100 [00:04<00:00, 26.20it/s]                                                                                                                                         0%|          | 0/50 [00:00<?, ?it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.047 | Best: {'fx': 508.333} (0.047):   0%|          | 0/50 [00:00<?, ?it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.047 | Best: {'fx': 508.333} (0.047):   2%|▏         | 1/50 [00:00<00:25,  1.89it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.049 | Best: {'fx': 509.354} (0.049):   2%|▏         | 1/50 [00:00<00:25,  1.89it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.051 | Best: {'fx': 510.374} (0.051):   4%|▍         | 2/50 [00:00<00:25,  1.89it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.051 | Best: {'fx': 510.374} (0.051):   6%|▌         | 3/50 [00:00<00:08,  5.67it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.053 | Best: {'fx': 511.395} (0.053):   6%|▌         | 3/50 [00:00<00:08,  5.67it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.057 | Best: {'fx': 513.435} (0.057):   8%|▊         | 4/50 [00:00<00:08,  5.67it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.057 | Best: {'fx': 513.435} (0.057):  10%|█         | 5/50 [00:00<00:05,  8.15it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.055 | Best: {'fx': 513.435} (0.057):  10%|█         | 5/50 [00:00<00:05,  8.15it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.059 | Best: {'fx': 514.456} (0.059):  12%|█▏        | 6/50 [00:00<00:05,  8.15it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.061 | Best: {'fx': 515.476} (0.061):  14%|█▍        | 7/50 [00:00<00:05,  8.15it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.064 | Best: {'fx': 516.497} (0.064):  16%|█▌        | 8/50 [00:00<00:05,  8.15it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.064 | Best: {'fx': 516.497} (0.064):  18%|█▊        | 9/50 [00:00<00:02, 14.23it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.067 | Best: {'fx': 517.517} (0.067):  18%|█▊        | 9/50 [00:00<00:02, 14.23it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.069 | Best: {'fx': 518.537} (0.069):  20%|██        | 10/50 [00:01<00:02, 14.23it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.073 | Best: {'fx': 519.558} (0.073):  22%|██▏       | 11/50 [00:01<00:02, 14.23it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.073 | Best: {'fx': 519.558} (0.073):  24%|██▍       | 12/50 [00:01<00:02, 15.86it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.076 | Best: {'fx': 520.578} (0.076):  24%|██▍       | 12/50 [00:01<00:02, 15.86it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.079 | Best: {'fx': 521.599} (0.079):  26%|██▌       | 13/50 [00:01<00:02, 15.86it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.083 | Best: {'fx': 522.619} (0.083):  28%|██▊       | 14/50 [00:01<00:02, 15.86it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.083 | Best: {'fx': 522.619} (0.083):  30%|███       | 15/50 [00:01<00:01, 17.82it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.085 | Best: {'fx': 523.639} (0.085):  30%|███       | 15/50 [00:01<00:01, 17.82it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.089 | Best: {'fx': 524.66} (0.089):  32%|███▏      | 16/50 [00:01<00:01, 17.82it/s] Brute | Start: {'fx': 533.333} (0.114) | Current: 0.095 | Best: {'fx': 525.68} (0.095):  34%|███▍      | 17/50 [00:01<00:01, 17.82it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.095 | Best: {'fx': 525.68} (0.095):  36%|███▌      | 18/50 [00:01<00:01, 16.85it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.100 | Best: {'fx': 526.701} (0.100):  36%|███▌      | 18/50 [00:01<00:01, 16.85it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.106 | Best: {'fx': 527.721} (0.106):  38%|███▊      | 19/50 [00:01<00:01, 16.85it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.112 | Best: {'fx': 528.741} (0.112):  40%|████      | 20/50 [00:01<00:01, 16.85it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.112 | Best: {'fx': 528.741} (0.112):  42%|████▏     | 21/50 [00:01<00:01, 18.39it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.115 | Best: {'fx': 529.762} (0.115):  42%|████▏     | 21/50 [00:01<00:01, 18.39it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.116 | Best: {'fx': 530.782} (0.116):  44%|████▍     | 22/50 [00:01<00:01, 18.39it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.114 | Best: {'fx': 530.782} (0.116):  46%|████▌     | 23/50 [00:01<00:01, 18.39it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.114 | Best: {'fx': 530.782} (0.116):  48%|████▊     | 24/50 [00:01<00:01, 18.28it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.110 | Best: {'fx': 530.782} (0.116):  48%|████▊     | 24/50 [00:01<00:01, 18.28it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.088 | Best: {'fx': 530.782} (0.116):  50%|█████     | 25/50 [00:01<00:01, 18.28it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.107 | Best: {'fx': 530.782} (0.116):  52%|█████▏    | 26/50 [00:01<00:01, 18.28it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.085 | Best: {'fx': 530.782} (0.116):  54%|█████▍    | 27/50 [00:01<00:01, 18.28it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.085 | Best: {'fx': 530.782} (0.116):  56%|█████▌    | 28/50 [00:01<00:00, 22.25it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.115 | Best: {'fx': 530.782} (0.116):  56%|█████▌    | 28/50 [00:01<00:00, 22.25it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.083 | Best: {'fx': 530.782} (0.116):  58%|█████▊    | 29/50 [00:01<00:00, 22.25it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.101 | Best: {'fx': 530.782} (0.116):  60%|██████    | 30/50 [00:01<00:00, 22.25it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.076 | Best: {'fx': 530.782} (0.116):  62%|██████▏   | 31/50 [00:01<00:00, 22.25it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.074 | Best: {'fx': 530.782} (0.116):  64%|██████▍   | 32/50 [00:01<00:00, 22.25it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.074 | Best: {'fx': 530.782} (0.116):  66%|██████▌   | 33/50 [00:01<00:00, 26.02it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.072 | Best: {'fx': 530.782} (0.116):  66%|██████▌   | 33/50 [00:02<00:00, 26.02it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.080 | Best: {'fx': 530.782} (0.116):  68%|██████▊   | 34/50 [00:02<00:00, 26.02it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.093 | Best: {'fx': 530.782} (0.116):  70%|███████   | 35/50 [00:02<00:00, 26.02it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.097 | Best: {'fx': 530.782} (0.116):  72%|███████▏  | 36/50 [00:02<00:00, 26.02it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.067 | Best: {'fx': 530.782} (0.116):  74%|███████▍  | 37/50 [00:02<00:00, 26.02it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.067 | Best: {'fx': 530.782} (0.116):  76%|███████▌  | 38/50 [00:02<00:00, 29.36it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.066 | Best: {'fx': 530.782} (0.116):  76%|███████▌  | 38/50 [00:02<00:00, 29.36it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.090 | Best: {'fx': 530.782} (0.116):  78%|███████▊  | 39/50 [00:02<00:00, 29.36it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.069 | Best: {'fx': 530.782} (0.116):  80%|████████  | 40/50 [00:02<00:00, 29.36it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.065 | Best: {'fx': 530.782} (0.116):  82%|████████▏ | 41/50 [00:02<00:00, 29.36it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.064 | Best: {'fx': 530.782} (0.116):  84%|████████▍ | 42/50 [00:02<00:00, 29.36it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.064 | Best: {'fx': 530.782} (0.116):  86%|████████▌ | 43/50 [00:02<00:00, 32.23it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.063 | Best: {'fx': 530.782} (0.116):  86%|████████▌ | 43/50 [00:02<00:00, 32.23it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.061 | Best: {'fx': 530.782} (0.116):  88%|████████▊ | 44/50 [00:02<00:00, 32.23it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.059 | Best: {'fx': 530.782} (0.116):  90%|█████████ | 45/50 [00:02<00:00, 32.23it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.057 | Best: {'fx': 530.782} (0.116):  92%|█████████▏| 46/50 [00:02<00:00, 32.23it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.057 | Best: {'fx': 530.782} (0.116):  94%|█████████▍| 47/50 [00:02<00:00, 28.87it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.056 | Best: {'fx': 530.782} (0.116):  94%|█████████▍| 47/50 [00:02<00:00, 28.87it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.054 | Best: {'fx': 530.782} (0.116):  96%|█████████▌| 48/50 [00:02<00:00, 28.87it/s]Brute | Start: {'fx': 533.333} (0.114) | Current: 0.053 | Best: {'fx': 530.782} (0.116):  98%|█████████▊| 49/50 [00:02<00:00, 28.87it/s]                                                                                                                                        
[DEBUG] Parameters after Step 5 (before square optimization):
    fx: 530.7823129251701
    px: 877.0
    py: 964.0
    k1: 0.0
    k2: 0.0
    k3: 0.0
    k4: 0.0
    p1: 0.0
    p2: 0.0
    p3: 0.0
    p4: 0.0
    scale: 3.0
    rotation: 0.0


[🔲] Square Reference Optimization
    Including tangential distortion parameters (p1, p2, p3, p4) in joint optimization
  Selecting up to 20 frames per rig (excluded 0 incomplete frames): 80 frames will be used for optimization
  Rigs: 1500(1500mm):20/20, 2000L(2000mm):20/20, 1000(1000mm):20/20, 2000R(2000mm):20/20
  Total: 80/80 frames used for optimization
Initial score: 6.3520: 0iter [00:00, ?iter/s][DEBUG] objective(x0) = 6.3520, picklable_objective(x0) = 6.3518
Best score: 6.3518: : 0iter [00:02, ?iter/s] Best score: 6.3518: : 1iter [00:02,  2.00s/iter]Best score: 6.3518: : 1iter [00:02,  2.00s/iter]Best score: 6.3518: : 2iter [00:02,  2.00s/iter]Best score: 6.3518: : 3iter [00:02,  1.71iter/s]Best score: 6.3518: : 3iter [00:02,  1.71iter/s]Best score: 6.3518: : 4iter [00:02,  1.71iter/s]Best score: 6.3518: : 5iter [00:02,  3.03iter/s]Best score: 6.3518: : 5iter [00:02,  3.03iter/s]Best score: 6.3518: : 6iter [00:02,  3.03iter/s]Best score: 6.3518: : 7iter [00:02,  4.40iter/s]Best score: 6.3518: : 7iter [00:02,  4.40iter/s]Best score: 6.3518: : 8iter [00:02,  4.40iter/s]Best score: 6.3518: : 9iter [00:02,  5.72iter/s]Best score: 6.3518: : 9iter [00:02,  5.72iter/s]Best score: 6.3518: : 10iter [00:02,  5.72iter/s]Best score: 6.3518: : 11iter [00:02,  6.84iter/s]Best score: 6.3518: : 11iter [00:02,  6.84iter/s]Best score: 6.3518: : 12iter [00:03,  6.84iter/s]Best score: 6.3518: : 13iter [00:03,  7.90iter/s]Best score: 6.3518: : 13iter [00:03,  7.90iter/s]Best score: 6.3518: : 14iter [00:03,  7.90iter/s]Best score: 6.3518: : 15iter [00:03,  8.77iter/s]Best score: 6.3518: : 15iter [00:03,  8.77iter/s]Best score: 6.3518: : 16iter [00:03,  8.77iter/s]Best score: 6.3518: : 17iter [00:03,  9.48iter/s]Best score: 6.3518: : 17iter [00:03,  9.48iter/s]Best score: 6.3518: : 18iter [00:03,  9.48iter/s]Best score: 6.3518: : 19iter [00:03, 10.02iter/s]Best score: 6.3518: : 19iter [00:03, 10.02iter/s]Best score: 6.3518: : 20iter [00:03, 10.02iter/s]Best score: 6.3518: : 21iter [00:03, 10.28iter/s]Best score: 6.3518: : 21iter [00:03, 10.28iter/s]Best score: 6.3518: : 22iter [00:03, 10.28iter/s]Best score: 6.3518: : 23iter [00:03, 10.62iter/s]Best score: 6.3518: : 23iter [00:04, 10.62iter/s]Best score: 6.3518: : 24iter [00:04, 10.62iter/s]Best score: 6.3518: : 25iter [00:04, 10.86iter/s]Best score: 6.3518: : 25iter [00:04, 10.86iter/s]Best score: 6.3518: : 26iter [00:04, 10.86iter/s]Best score: 6.3518: : 27iter [00:04, 11.02iter/s]Best score: 6.3518: : 27iter [00:04, 11.02iter/s]Best score: 6.3518: : 28iter [00:04, 11.02iter/s]Best score: 6.3518: : 29iter [00:04, 11.16iter/s]Best score: 6.3518: : 29iter [00:04, 11.16iter/s]Best score: 6.3518: : 30iter [00:04, 11.16iter/s]Best score: 6.3518: : 31iter [00:04, 11.07iter/s]Best score: 6.3518: : 31iter [00:04, 11.07iter/s]Best score: 6.3518: : 32iter [00:04, 11.07iter/s]Best score: 6.3518: : 33iter [00:04, 11.17iter/s]Best score: 6.3518: : 33iter [00:04, 11.17iter/s]Best score: 6.3518: : 34iter [00:05, 11.17iter/s]Best score: 6.3518: : 35iter [00:05, 11.28iter/s]Best score: 6.3518: : 35iter [00:05, 11.28iter/s]Best score: 6.3518: : 36iter [00:05, 11.28iter/s]Best score: 6.3518: : 37iter [00:05, 11.27iter/s]Best score: 6.3518: : 37iter [00:05, 11.27iter/s]Best score: 6.3518: : 38iter [00:05, 11.27iter/s]Best score: 6.3518: : 39iter [00:05, 11.30iter/s]Best score: 6.3518: : 39iter [00:05, 11.30iter/s]Best score: 6.3518: : 40iter [00:05, 11.30iter/s]Best score: 6.3518: : 41iter [00:05, 11.20iter/s]Best score: 6.3518: : 41iter [00:05, 11.20iter/s]Best score: 6.3518: : 42iter [00:05, 11.20iter/s]Best score: 6.3518: : 43iter [00:05, 11.34iter/s]Best score: 6.3518: : 43iter [00:05, 11.34iter/s]Best score: 6.3518: : 44iter [00:05, 11.34iter/s]Best score: 6.3518: : 45iter [00:05, 11.41iter/s]Best score: 6.3518: : 45iter [00:05, 11.41iter/s]Best score: 6.3518: : 46iter [00:06, 11.41iter/s]Best score: 6.3518: : 47iter [00:06, 11.41iter/s]Best score: 6.3518: : 47iter [00:06, 11.41iter/s]Best score: 6.3518: : 48iter [00:06, 11.41iter/s]Best score: 6.3518: : 49iter [00:06, 11.46iter/s]
[ITER 50] Best: 6.3518
[PARAMS] Current best parameters:
  fx: 530.7823
  fy: 530.7823
  px: 877.0000
  py: 964.0000
  k1: 0.00000000
  k2: -0.00000000
  k3: 0.00000000
  k4: 0.00000000
  p1: 0.00000000
  p2: 0.00000000
  p3: 0.00000000
  p4: 0.00000000
  s1: 0.0000
  s2: 0.0000
  s3: 0.0000
  s4: 0.0000
  tilt_x: 0.0000
  tilt_y: 0.0000
  scale: 3.0000
  rotation: 0.0000
Best score: 6.3518: : 49iter [00:06, 11.46iter/s]Best score: 6.3518: : 50iter [00:06, 11.46iter/s]Best score: 6.3518: : 51iter [00:06, 11.31iter/s]Best score: 6.3518: : 51iter [00:06, 11.31iter/s]Best score: 6.3518: : 52iter [00:06, 11.31iter/s]Best score: 6.3518: : 53iter [00:06, 11.35iter/s]Best score: 6.3518: : 53iter [00:06, 11.35iter/s]Best score: 6.3518: : 54iter [00:06, 11.35iter/s]Best score: 6.3518: : 55iter [00:06, 11.42iter/s]Best score: 6.3518: : 55iter [00:06, 11.42iter/s]Best score: 6.3518: : 56iter [00:06, 11.42iter/s]Best score: 6.3518: : 57iter [00:06, 11.50iter/s]Best score: 6.3518: : 57iter [00:07, 11.50iter/s]Best score: 6.3518: : 58iter [00:07, 11.50iter/s]Best score: 6.3518: : 59iter [00:07, 11.49iter/s]Best score: 6.3518: : 59iter [00:07, 11.49iter/s]Best score: 6.3518: : 60iter [00:07, 11.49iter/s]Best score: 6.3518: : 61iter [00:07, 11.34iter/s]Best score: 6.3518: : 61iter [00:07, 11.34iter/s]Best score: 6.3518: : 62iter [00:07, 11.34iter/s]Best score: 6.3518: : 63iter [00:07, 11.44iter/s]Best score: 6.3518: : 63iter [00:07, 11.44iter/s]Best score: 6.3518: : 64iter [00:07, 11.44iter/s]Best score: 6.3518: : 65iter [00:07, 11.52iter/s]Best score: 6.3518: : 65iter [00:07, 11.52iter/s]Best score: 6.3518: : 66iter [00:07, 11.52iter/s]Best score: 6.3518: : 67iter [00:07, 11.56iter/s]Best score: 6.3518: : 67iter [00:07, 11.56iter/s]Best score: 6.3518: : 68iter [00:07, 11.56iter/s]Best score: 6.3518: : 69iter [00:07, 11.55iter/s]Best score: 6.3518: : 69iter [00:08, 11.55iter/s]Best score: 6.3518: : 70iter [00:08, 11.55iter/s]Best score: 6.3518: : 71iter [00:08, 11.42iter/s]Best score: 6.3518: : 71iter [00:08, 11.42iter/s]Best score: 6.3518: : 72iter [00:08, 11.42iter/s]Best score: 6.3518: : 73iter [00:08, 11.49iter/s]Best score: 6.3518: : 73iter [00:08, 11.49iter/s]Best score: 6.3518: : 74iter [00:08, 11.49iter/s]Best score: 6.3518: : 75iter [00:08, 11.55iter/s]Best score: 6.3518: : 75iter [00:08, 11.55iter/s]Best score: 6.3518: : 76iter [00:08, 11.55iter/s]Best score: 6.3518: : 77iter [00:08, 11.63iter/s]Best score: 6.3518: : 77iter [00:08, 11.63iter/s]Best score: 6.3518: : 78iter [00:08, 11.63iter/s]Best score: 6.3518: : 79iter [00:08, 11.67iter/s]Best score: 6.3518: : 79iter [00:08, 11.67iter/s]Best score: 6.3518: : 80iter [00:09, 11.67iter/s]Best score: 6.3518: : 81iter [00:09, 11.53iter/s]Best score: 6.3518: : 81iter [00:09, 11.53iter/s]Best score: 6.3518: : 82iter [00:09, 11.53iter/s]Best score: 6.3518: : 83iter [00:09, 11.55iter/s]Best score: 6.3518: : 83iter [00:09, 11.55iter/s]Best score: 6.3518: : 84iter [00:09, 11.55iter/s]Best score: 6.3518: : 85iter [00:09, 11.58iter/s]Best score: 6.3518: : 85iter [00:09, 11.58iter/s]Best score: 6.3518: : 86iter [00:09, 11.58iter/s]Best score: 6.3518: : 87iter [00:09, 11.64iter/s]Best score: 6.3518: : 87iter [00:09, 11.64iter/s]Best score: 6.3518: : 88iter [00:09, 11.64iter/s]Best score: 6.3518: : 89iter [00:09, 11.60iter/s]Best score: 4.8638: : 89iter [00:09, 11.60iter/s]Best score: 4.8638: : 90iter [00:09, 11.60iter/s]Best score: 4.8638: : 91iter [00:09, 11.43iter/s]Best score: 4.8638: : 91iter [00:09, 11.43iter/s]Best score: 4.8638: : 92iter [00:10, 11.43iter/s]Best score: 4.8638: : 93iter [00:10, 11.51iter/s]Best score: 4.8638: : 93iter [00:10, 11.51iter/s]Best score: 4.8638: : 94iter [00:10, 11.51iter/s]Best score: 4.8638: : 95iter [00:10, 11.57iter/s]Best score: 4.8638: : 95iter [00:10, 11.57iter/s]Best score: 4.8638: : 96iter [00:10, 11.57iter/s]Best score: 4.8638: : 97iter [00:10, 11.58iter/s]Best score: 4.8638: : 97iter [00:10, 11.58iter/s]Best score: 4.8638: : 98iter [00:10, 11.58iter/s]Best score: 4.8638: : 99iter [00:10, 11.62iter/s]
[ITER 100] Best: 4.8237
[PARAMS] Current best parameters:
  fx: 547.8318
  fy: 549.8927
  px: 875.3988
  py: 966.3168
  k1: -0.03319707
  k2: 0.00691568
  k3: 0.00884049
  k4: -0.00469065
  p1: 0.01019957
  p2: 0.00125451
  p3: -0.00326765
  p4: 0.00725942
  s1: 0.0011
  s2: -0.0092
  s3: -0.0045
  s4: -0.0143
  tilt_x: 0.0039
  tilt_y: -0.0135
  scale: 3.0425
  rotation: 0.3449
Best score: 4.8237: : 99iter [00:10, 11.62iter/s]Best score: 4.8237: : 100iter [00:10, 11.62iter/s]Best score: 4.8237: : 101iter [00:10,  9.90iter/s]Best score: 4.8237: : 101iter [00:10,  9.90iter/s]Best score: 4.8237: : 102iter [00:11,  9.90iter/s]Best score: 4.8237: : 103iter [00:11, 10.28iter/s]Best score: 4.8237: : 103iter [00:11, 10.28iter/s]Best score: 4.8237: : 104iter [00:11, 10.28iter/s]Best score: 4.8237: : 105iter [00:11, 10.60iter/s]Best score: 4.8237: : 105iter [00:11, 10.60iter/s]Best score: 4.8237: : 106iter [00:11, 10.60iter/s]Best score: 4.8237: : 107iter [00:11, 10.82iter/s]Best score: 4.8237: : 107iter [00:11, 10.82iter/s]Best score: 4.8237: : 108iter [00:11, 10.82iter/s]Best score: 4.8237: : 109iter [00:11, 10.98iter/s]Best score: 4.8237: : 109iter [00:11, 10.98iter/s]Best score: 4.8237: : 110iter [00:11, 10.98iter/s]Best score: 4.8237: : 111iter [00:11, 10.87iter/s]Best score: 4.8237: : 111iter [00:11, 10.87iter/s]Best score: 4.8237: : 112iter [00:11, 10.87iter/s]Best score: 4.8237: : 113iter [00:11, 11.06iter/s]Best score: 4.8237: : 113iter [00:11, 11.06iter/s]Best score: 4.8237: : 114iter [00:12, 11.06iter/s]Best score: 4.8237: : 115iter [00:12, 11.14iter/s]Best score: 4.8237: : 115iter [00:12, 11.14iter/s]Best score: 4.8237: : 116iter [00:12, 11.14iter/s]Best score: 4.8237: : 117iter [00:12, 11.24iter/s]Best score: 4.8237: : 117iter [00:12, 11.24iter/s]Best score: 4.8237: : 118iter [00:12, 11.24iter/s]Best score: 4.8237: : 119iter [00:12, 11.29iter/s]Best score: 4.8237: : 119iter [00:12, 11.29iter/s]Best score: 4.8237: : 120iter [00:12, 11.29iter/s]Best score: 4.8237: : 121iter [00:12, 11.18iter/s]Best score: 4.8237: : 121iter [00:12, 11.18iter/s]Best score: 4.8237: : 122iter [00:12, 11.18iter/s]Best score: 4.8237: : 123iter [00:12, 11.29iter/s]Best score: 4.8237: : 123iter [00:12, 11.29iter/s]Best score: 4.8237: : 124iter [00:12, 11.29iter/s]Best score: 4.8237: : 125iter [00:12, 11.37iter/s]Best score: 4.8237: : 125iter [00:13, 11.37iter/s]Best score: 4.8237: : 126iter [00:13, 11.37iter/s]Best score: 4.8237: : 127iter [00:13, 11.39iter/s]Best score: 4.8237: : 127iter [00:13, 11.39iter/s]Best score: 4.8237: : 128iter [00:13, 11.39iter/s]Best score: 4.8237: : 129iter [00:13, 11.37iter/s]Best score: 4.8237: : 129iter [00:13, 11.37iter/s]Best score: 4.8237: : 130iter [00:13, 11.37iter/s]Best score: 4.8237: : 131iter [00:13, 11.20iter/s]Best score: 4.8237: : 131iter [00:13, 11.20iter/s]Best score: 4.8237: : 132iter [00:13, 11.20iter/s]Best score: 4.8237: : 133iter [00:13, 11.32iter/s]Best score: 4.8237: : 133iter [00:13, 11.32iter/s]Best score: 4.8237: : 134iter [00:13, 11.32iter/s]Best score: 4.8237: : 135iter [00:13, 11.36iter/s]Best score: 4.8237: : 135iter [00:13, 11.36iter/s]Best score: 4.8237: : 136iter [00:14, 11.36iter/s]Best score: 4.8237: : 137iter [00:14, 11.44iter/s]Best score: 4.8237: : 137iter [00:14, 11.44iter/s]Best score: 4.8237: : 138iter [00:14, 11.44iter/s]Best score: 4.8237: : 139iter [00:14, 11.52iter/s]Best score: 4.8237: : 139iter [00:14, 11.52iter/s]Best score: 4.8237: : 140iter [00:14, 11.52iter/s]Best score: 4.8237: : 141iter [00:14, 11.34iter/s]Best score: 4.8237: : 141iter [00:14, 11.34iter/s]Best score: 4.8237: : 142iter [00:14, 11.34iter/s]Best score: 4.8237: : 143iter [00:14, 11.45iter/s]Best score: 4.8237: : 143iter [00:14, 11.45iter/s]Best score: 4.8237: : 144iter [00:14, 11.45iter/s]Best score: 4.8237: : 145iter [00:14, 11.52iter/s]Best score: 4.8237: : 145iter [00:14, 11.52iter/s]Best score: 4.8237: : 146iter [00:14, 11.52iter/s]Best score: 4.8237: : 147iter [00:14, 11.51iter/s]Best score: 4.8237: : 147iter [00:14, 11.51iter/s]Best score: 4.8237: : 148iter [00:15, 11.51iter/s]Best score: 4.8237: : 149iter [00:15, 11.53iter/s]
[ITER 150] Best: 4.8237
[PARAMS] Current best parameters:
  fx: 547.8318
  fy: 549.8927
  px: 875.3988
  py: 966.3168
  k1: -0.03319707
  k2: 0.00691568
  k3: 0.00884049
  k4: -0.00469065
  p1: 0.01019957
  p2: 0.00125451
  p3: -0.00326765
  p4: 0.00725942
  s1: 0.0011
  s2: -0.0092
  s3: -0.0045
  s4: -0.0143
  tilt_x: 0.0039
  tilt_y: -0.0135
  scale: 3.0425
  rotation: 0.3449
Best score: 4.8237: : 149iter [00:15, 11.53iter/s]Best score: 4.8237: : 150iter [00:15, 11.53iter/s]Best score: 4.8237: : 151iter [00:15,  7.47iter/s]Best score: 4.8237: : 151iter [00:15,  7.47iter/s]Best score: 4.8237: : 152iter [00:15,  7.47iter/s]Best score: 4.8237: : 153iter [00:15,  8.38iter/s]Best score: 4.8237: : 153iter [00:15,  8.38iter/s]Best score: 4.8237: : 154iter [00:15,  8.38iter/s]Best score: 4.8237: : 155iter [00:15,  9.14iter/s]Best score: 4.8237: : 155iter [00:15,  9.14iter/s]Best score: 4.8237: : 156iter [00:16,  9.14iter/s]Best score: 4.8237: : 157iter [00:16,  9.80iter/s]Best score: 4.8237: : 157iter [00:16,  9.80iter/s]Best score: 4.8237: : 158iter [00:16,  9.80iter/s]Best score: 4.8237: : 159iter [00:16, 10.27iter/s]Best score: 4.8237: : 159iter [00:16, 10.27iter/s]Best score: 4.8237: : 160iter [00:16, 10.27iter/s]Best score: 4.8237: : 161iter [00:16, 10.47iter/s]Best score: 4.8237: : 161iter [00:16, 10.47iter/s]Best score: 4.8237: : 162iter [00:16, 10.47iter/s]Best score: 4.8237: : 163iter [00:16, 10.79iter/s]Best score: 4.8237: : 163iter [00:16, 10.79iter/s]Best score: 4.8237: : 164iter [00:16, 10.79iter/s]Best score: 4.8237: : 165iter [00:16, 11.01iter/s]Best score: 4.8237: : 165iter [00:16, 11.01iter/s]Best score: 4.8237: : 166iter [00:16, 11.01iter/s]Best score: 4.8237: : 167iter [00:16, 11.24iter/s]Best score: 4.8237: : 167iter [00:17, 11.24iter/s]Best score: 4.8237: : 168iter [00:17, 11.24iter/s]Best score: 4.8237: : 169iter [00:17, 11.39iter/s]Best score: 4.8237: : 169iter [00:17, 11.39iter/s]Best score: 4.8237: : 170iter [00:17, 11.39iter/s]Best score: 4.8237: : 171iter [00:17, 11.29iter/s]Best score: 4.8237: : 171iter [00:17, 11.29iter/s]Best score: 4.8237: : 172iter [00:17, 11.29iter/s]Best score: 4.8237: : 173iter [00:17, 11.38iter/s]Best score: 4.8237: : 173iter [00:17, 11.38iter/s]Best score: 4.8237: : 174iter [00:17, 11.38iter/s]Best score: 4.8237: : 175iter [00:17, 11.52iter/s]Best score: 4.8237: : 175iter [00:17, 11.52iter/s]Best score: 4.8237: : 176iter [00:17, 11.52iter/s]Best score: 4.8237: : 177iter [00:17, 11.55iter/s]Best score: 4.8237: : 177iter [00:17, 11.55iter/s]Best score: 4.8237: : 178iter [00:17, 11.55iter/s]Best score: 4.8237: : 179iter [00:17, 11.60iter/s]Best score: 4.8237: : 179iter [00:18, 11.60iter/s]Best score: 4.8237: : 180iter [00:18, 11.60iter/s]Best score: 4.8237: : 181iter [00:18, 11.44iter/s]Best score: 4.8237: : 181iter [00:18, 11.44iter/s]Best score: 4.8237: : 182iter [00:18, 11.44iter/s]Best score: 4.8237: : 183iter [00:18, 11.55iter/s]Best score: 4.8237: : 183iter [00:18, 11.55iter/s]Best score: 4.8237: : 184iter [00:18, 11.55iter/s]Best score: 4.8237: : 185iter [00:18, 11.57iter/s]Best score: 4.8237: : 185iter [00:18, 11.57iter/s]Best score: 4.8237: : 186iter [00:18, 11.57iter/s]Best score: 4.8237: : 187iter [00:18, 11.60iter/s]Best score: 4.8237: : 187iter [00:18, 11.60iter/s]Best score: 4.8237: : 188iter [00:18, 11.60iter/s]Best score: 4.8237: : 189iter [00:18, 11.66iter/s]Best score: 1.6214: : 189iter [00:18, 11.66iter/s]Best score: 1.6214: : 190iter [00:19, 11.66iter/s]Best score: 1.6214: : 191iter [00:19, 11.47iter/s]Best score: 1.6214: : 191iter [00:19, 11.47iter/s]Best score: 1.6214: : 192iter [00:19, 11.47iter/s]Best score: 1.6214: : 193iter [00:19, 11.54iter/s]Best score: 1.6214: : 193iter [00:19, 11.54iter/s]Best score: 1.6214: : 194iter [00:19, 11.54iter/s]Best score: 1.6214: : 195iter [00:19, 11.59iter/s]Best score: 1.6214: : 195iter [00:19, 11.59iter/s]Best score: 1.6214: : 196iter [00:19, 11.59iter/s]Best score: 1.6214: : 197iter [00:19, 11.66iter/s]Best score: 1.6214: : 197iter [00:19, 11.66iter/s]Best score: 1.6214: : 198iter [00:19, 11.66iter/s]Best score: 1.6214: : 199iter [00:19, 11.69iter/s]
[ITER 200] Best: 1.4114
[PARAMS] Current best parameters:
  fx: 572.3075
  fy: 572.0247
  px: 885.9692
  py: 964.5464
  k1: -0.03328212
  k2: -0.01651838
  k3: 0.01918386
  k4: -0.00594386
  p1: -0.00528413
  p2: 0.01842928
  p3: -0.00758895
  p4: 0.01045935
  s1: -0.0033
  s2: -0.0026
  s3: 0.0073
  s4: -0.0143
  tilt_x: 0.0060
  tilt_y: -0.0315
  scale: 2.9659
  rotation: 0.4189
Best score: 1.4114: : 199iter [00:19, 11.69iter/s]Best score: 1.4114: : 200iter [00:20, 11.69iter/s]Best score: 1.4114: : 201iter [00:20,  7.55iter/s]Best score: 1.4114: : 201iter [00:20,  7.55iter/s]Best score: 1.4114: : 202iter [00:20,  7.55iter/s]Best score: 1.4114: : 203iter [00:20,  8.47iter/s]Best score: 1.4114: : 203iter [00:20,  8.47iter/s]Best score: 1.4114: : 204iter [00:20,  8.47iter/s]Best score: 1.4114: : 205iter [00:20,  9.21iter/s]Best score: 1.4114: : 205iter [00:20,  9.21iter/s]Best score: 1.4114: : 206iter [00:20,  9.21iter/s]Best score: 1.4114: : 207iter [00:20,  9.87iter/s]Best score: 1.4114: : 207iter [00:20,  9.87iter/s]Best score: 1.4114: : 208iter [00:20,  9.87iter/s]Best score: 1.4114: : 209iter [00:20, 10.37iter/s]Best score: 0.7676: : 209iter [00:20, 10.37iter/s]Best score: 0.7676: : 210iter [00:21, 10.37iter/s]Best score: 0.7676: : 211iter [00:21, 10.58iter/s]Best score: 0.7676: : 211iter [00:21, 10.58iter/s]Best score: 0.7676: : 212iter [00:21, 10.58iter/s]Best score: 0.7676: : 213iter [00:21, 10.92iter/s]Best score: 0.7676: : 213iter [00:21, 10.92iter/s]Best score: 0.7676: : 214iter [00:21, 10.92iter/s]Best score: 0.7676: : 215iter [00:21, 11.16iter/s]Best score: 0.7676: : 215iter [00:21, 11.16iter/s]Best score: 0.7676: : 216iter [00:21, 11.16iter/s]Best score: 0.7676: : 217iter [00:21, 11.33iter/s]Best score: 0.7676: : 217iter [00:21, 11.33iter/s]Best score: 0.7676: : 218iter [00:21, 11.33iter/s]Best score: 0.7676: : 219iter [00:21, 11.42iter/s]Best score: 0.5864: : 219iter [00:21, 11.42iter/s]Best score: 0.5864: : 220iter [00:21, 11.42iter/s]Best score: 0.5864: : 221iter [00:21, 11.25iter/s]Best score: 0.5864: : 221iter [00:21, 11.25iter/s]Best score: 0.5864: : 222iter [00:22, 11.25iter/s]Best score: 0.5864: : 223iter [00:22, 11.38iter/s]Best score: 0.5864: : 223iter [00:22, 11.38iter/s]Best score: 0.5864: : 224iter [00:22, 11.38iter/s]Best score: 0.5864: : 225iter [00:22, 11.42iter/s]Best score: 0.5864: : 225iter [00:22, 11.42iter/s]Best score: 0.5864: : 226iter [00:22, 11.42iter/s]Best score: 0.5864: : 227iter [00:22, 11.53iter/s]Best score: 0.5864: : 227iter [00:22, 11.53iter/s]Best score: 0.5864: : 228iter [00:22, 11.53iter/s]Best score: 0.5864: : 229iter [00:22, 11.58iter/s]Best score: 0.5864: : 229iter [00:22, 11.58iter/s]Best score: 0.5864: : 230iter [00:22, 11.58iter/s]Best score: 0.5864: : 231iter [00:22, 11.44iter/s]Best score: 0.5864: : 231iter [00:22, 11.44iter/s]Best score: 0.5864: : 232iter [00:22, 11.44iter/s]Best score: 0.5864: : 233iter [00:22, 11.54iter/s]Best score: 0.5864: : 233iter [00:23, 11.54iter/s]Best score: 0.5864: : 234iter [00:23, 11.54iter/s]Best score: 0.5864: : 235iter [00:23, 11.62iter/s]Best score: 0.5864: : 235iter [00:23, 11.62iter/s]Best score: 0.5864: : 236iter [00:23, 11.62iter/s]Best score: 0.5864: : 237iter [00:23, 11.67iter/s]Best score: 0.5864: : 237iter [00:23, 11.67iter/s]Best score: 0.5864: : 238iter [00:23, 11.67iter/s]Best score: 0.5864: : 239iter [00:23, 11.67iter/s]Best score: 0.5260: : 239iter [00:23, 11.67iter/s]Best score: 0.5260: : 240iter [00:23, 11.67iter/s]Best score: 0.5260: : 241iter [00:23, 11.48iter/s]Best score: 0.5260: : 241iter [00:23, 11.48iter/s]Best score: 0.5260: : 242iter [00:23, 11.48iter/s]Best score: 0.5260: : 243iter [00:23, 11.58iter/s]Best score: 0.5260: : 243iter [00:23, 11.58iter/s]Best score: 0.5260: : 244iter [00:23, 11.58iter/s]Best score: 0.5260: : 245iter [00:23, 11.62iter/s]Best score: 0.5260: : 245iter [00:24, 11.62iter/s]Best score: 0.5260: : 246iter [00:24, 11.62iter/s]Best score: 0.5260: : 247iter [00:24, 11.67iter/s]Best score: 0.5260: : 247iter [00:24, 11.67iter/s]Best score: 0.5260: : 248iter [00:24, 11.67iter/s]Best score: 0.5260: : 249iter [00:24, 11.63iter/s]
[ITER 250] Best: 0.4995
[PARAMS] Current best parameters:
  fx: 556.3545
  fy: 556.4040
  px: 880.7280
  py: 965.6688
  k1: -0.00664527
  k2: -0.03555627
  k3: 0.02652649
  k4: -0.00641192
  p1: 0.00540190
  p2: 0.00698804
  p3: -0.00513400
  p4: 0.00111332
  s1: 0.0152
  s2: -0.0115
  s3: -0.0050
  s4: -0.0046
  tilt_x: 0.0002
  tilt_y: -0.0243
  scale: 2.9778
  rotation: 0.2470
Best score: 0.4995: : 249iter [00:24, 11.63iter/s]Best score: 0.4995: : 250iter [00:24, 11.63iter/s]Best score: 0.4995: : 251iter [00:24,  7.52iter/s]Best score: 0.4995: : 251iter [00:24,  7.52iter/s]Best score: 0.4995: : 252iter [00:25,  7.52iter/s]Best score: 0.4995: : 253iter [00:25,  7.00iter/s]Best score: 0.4995: : 253iter [00:25,  7.00iter/s]Best score: 0.4995: : 254iter [00:25,  7.00iter/s]Best score: 0.4995: : 255iter [00:25,  7.97iter/s]Best score: 0.4995: : 255iter [00:25,  7.97iter/s]Best score: 0.4995: : 256iter [00:25,  7.97iter/s]Best score: 0.4995: : 257iter [00:25,  8.81iter/s]Best score: 0.4995: : 257iter [00:25,  8.81iter/s]Best score: 0.4995: : 258iter [00:25,  8.81iter/s]Best score: 0.4995: : 259iter [00:25,  9.53iter/s]Best score: 0.3842: : 259iter [00:25,  9.53iter/s]Best score: 0.3842: : 260iter [00:25,  9.53iter/s]Best score: 0.3842: : 261iter [00:25,  9.97iter/s]Best score: 0.3842: : 261iter [00:25,  9.97iter/s]Best score: 0.3842: : 262iter [00:25,  9.97iter/s]Best score: 0.3842: : 263iter [00:25, 10.42iter/s]Best score: 0.3842: : 263iter [00:26, 10.42iter/s]Best score: 0.3842: : 264iter [00:26, 10.42iter/s]Best score: 0.3842: : 265iter [00:26, 10.73iter/s]Best score: 0.3842: : 265iter [00:26, 10.73iter/s]Best score: 0.3842: : 266iter [00:26, 10.73iter/s]Best score: 0.3842: : 267iter [00:26, 10.97iter/s]Best score: 0.3842: : 267iter [00:26, 10.97iter/s]Best score: 0.3842: : 268iter [00:26, 10.97iter/s]Best score: 0.3842: : 269iter [00:26, 11.20iter/s]Best score: 0.3412: : 269iter [00:26, 11.20iter/s]Best score: 0.3412: : 270iter [00:26, 11.20iter/s]Best score: 0.3412: : 271iter [00:26, 11.20iter/s]Best score: 0.3412: : 271iter [00:26, 11.20iter/s]Best score: 0.3412: : 272iter [00:26, 11.20iter/s]Best score: 0.3412: : 273iter [00:26, 11.38iter/s]Best score: 0.3412: : 273iter [00:26, 11.38iter/s]Best score: 0.3412: : 274iter [00:27, 11.38iter/s]Best score: 0.3412: : 275iter [00:27, 11.50iter/s]Best score: 0.3412: : 275iter [00:27, 11.50iter/s]Best score: 0.3412: : 276iter [00:27, 11.50iter/s]Best score: 0.3412: : 277iter [00:27, 11.58iter/s]Best score: 0.3412: : 277iter [00:27, 11.58iter/s]Best score: 0.3412: : 278iter [00:27, 11.58iter/s]Best score: 0.3412: : 279iter [00:27, 11.60iter/s]Best score: 0.2838: : 279iter [00:27, 11.60iter/s]Best score: 0.2838: : 280iter [00:27, 11.60iter/s]Best score: 0.2838: : 281iter [00:27, 11.47iter/s]Best score: 0.2838: : 281iter [00:27, 11.47iter/s]Best score: 0.2838: : 282iter [00:27, 11.47iter/s]Best score: 0.2838: : 283iter [00:27, 11.56iter/s]Best score: 0.2838: : 283iter [00:27, 11.56iter/s]Best score: 0.2838: : 284iter [00:27, 11.56iter/s]Best score: 0.2838: : 285iter [00:27, 11.62iter/s]Best score: 0.2838: : 285iter [00:27, 11.62iter/s]Best score: 0.2838: : 286iter [00:28, 11.62iter/s]Best score: 0.2838: : 287iter [00:28, 11.62iter/s]Best score: 0.2838: : 287iter [00:28, 11.62iter/s]Best score: 0.2838: : 288iter [00:28, 11.62iter/s]Best score: 0.2838: : 289iter [00:28, 11.66iter/s]Best score: 0.2838: : 289iter [00:28, 11.66iter/s]Best score: 0.2838: : 290iter [00:28, 11.66iter/s]Best score: 0.2838: : 291iter [00:28, 11.49iter/s]Best score: 0.2838: : 291iter [00:28, 11.49iter/s]Best score: 0.2838: : 292iter [00:28, 11.49iter/s]Best score: 0.2838: : 293iter [00:28, 11.57iter/s]Best score: 0.2838: : 293iter [00:28, 11.57iter/s]Best score: 0.2838: : 294iter [00:28, 11.57iter/s]Best score: 0.2838: : 295iter [00:28, 11.64iter/s]Best score: 0.2838: : 295iter [00:28, 11.64iter/s]Best score: 0.2838: : 296iter [00:28, 11.64iter/s]Best score: 0.2838: : 297iter [00:28, 11.68iter/s]Best score: 0.2838: : 297iter [00:29, 11.68iter/s]Best score: 0.2838: : 298iter [00:29, 11.68iter/s]Best score: 0.2838: : 299iter [00:29, 11.67iter/s]
[ITER 300] Best: 0.2605
[PARAMS] Current best parameters:
  fx: 560.3494
  fy: 560.9285
  px: 882.6395
  py: 962.1025
  k1: -0.00586406
  k2: -0.04136662
  k3: 0.02871548
  k4: -0.00653000
  p1: 0.00060576
  p2: 0.00937877
  p3: -0.00898240
  p4: 0.00960456
  s1: 0.0131
  s2: -0.0139
  s3: -0.0029
  s4: -0.0083
  tilt_x: -0.0105
  tilt_y: -0.0297
  scale: 2.9685
  rotation: 0.3131
Best score: 0.2605: : 299iter [00:29, 11.67iter/s]Best score: 0.2605: : 300iter [00:29, 11.67iter/s]Best score: 0.2605: : 301iter [00:29,  7.54iter/s]Best score: 0.2605: : 301iter [00:29,  7.54iter/s]Best score: 0.2605: : 302iter [00:29,  7.54iter/s]Best score: 0.2605: : 303iter [00:29,  8.45iter/s]Best score: 0.2605: : 303iter [00:29,  8.45iter/s]Best score: 0.2605: : 304iter [00:29,  8.45iter/s]Best score: 0.2605: : 305iter [00:29,  9.24iter/s]Best score: 0.2605: : 305iter [00:29,  9.24iter/s]Best score: 0.2605: : 306iter [00:30,  9.24iter/s]Best score: 0.2605: : 307iter [00:30,  9.86iter/s]Best score: 0.2605: : 307iter [00:30,  9.86iter/s]Best score: 0.2605: : 308iter [00:30,  9.86iter/s]Best score: 0.2605: : 309iter [00:30, 10.36iter/s]Best score: 0.2605: : 309iter [00:30, 10.36iter/s]Best score: 0.2605: : 310iter [00:30, 10.36iter/s]Best score: 0.2605: : 311iter [00:30, 10.52iter/s]Best score: 0.2605: : 311iter [00:30, 10.52iter/s]Best score: 0.2605: : 312iter [00:30, 10.52iter/s]Best score: 0.2605: : 313iter [00:30, 10.87iter/s]Best score: 0.2605: : 313iter [00:30, 10.87iter/s]Best score: 0.2605: : 314iter [00:30, 10.87iter/s]Best score: 0.2605: : 315iter [00:30, 11.12iter/s]Best score: 0.2605: : 315iter [00:30, 11.12iter/s]Best score: 0.2605: : 316iter [00:30, 11.12iter/s]Best score: 0.2605: : 317iter [00:30, 11.31iter/s]Best score: 0.2605: : 317iter [00:31, 11.31iter/s]Best score: 0.2605: : 318iter [00:31, 11.31iter/s]Best score: 0.2605: : 319iter [00:31, 11.44iter/s]Best score: 0.2062: : 319iter [00:31, 11.44iter/s]Best score: 0.2062: : 320iter [00:31, 11.44iter/s]Best score: 0.2062: : 321iter [00:31, 11.34iter/s]Best score: 0.2062: : 321iter [00:31, 11.34iter/s]Best score: 0.2062: : 322iter [00:31, 11.34iter/s]Best score: 0.2062: : 323iter [00:31, 11.46iter/s]Best score: 0.2062: : 323iter [00:31, 11.46iter/s]Best score: 0.2062: : 324iter [00:31, 11.46iter/s]Best score: 0.2062: : 325iter [00:31, 11.55iter/s]Best score: 0.2062: : 325iter [00:31, 11.55iter/s]Best score: 0.2062: : 326iter [00:31, 11.55iter/s]Best score: 0.2062: : 327iter [00:31, 11.61iter/s]Best score: 0.2062: : 327iter [00:31, 11.61iter/s]Best score: 0.2062: : 328iter [00:31, 11.61iter/s]Best score: 0.2062: : 329iter [00:31, 11.65iter/s]Best score: 0.2062: : 329iter [00:32, 11.65iter/s]Best score: 0.2062: : 330iter [00:32, 11.65iter/s]Best score: 0.2062: : 331iter [00:32, 11.44iter/s]Best score: 0.2062: : 331iter [00:32, 11.44iter/s]Best score: 0.2062: : 332iter [00:32, 11.44iter/s]Best score: 0.2062: : 333iter [00:32, 11.50iter/s]Best score: 0.2062: : 333iter [00:32, 11.50iter/s]Best score: 0.2062: : 334iter [00:32, 11.50iter/s]Best score: 0.2062: : 335iter [00:32, 11.58iter/s]Best score: 0.2062: : 335iter [00:32, 11.58iter/s]Best score: 0.2062: : 336iter [00:32, 11.58iter/s]Best score: 0.2062: : 337iter [00:32, 11.62iter/s]Best score: 0.2062: : 337iter [00:32, 11.62iter/s]Best score: 0.2062: : 338iter [00:32, 11.62iter/s]Best score: 0.2062: : 339iter [00:32, 11.66iter/s]Best score: 0.1749: : 339iter [00:32, 11.66iter/s]Best score: 0.1749: : 340iter [00:33, 11.66iter/s]Best score: 0.1749: : 341iter [00:33, 11.48iter/s]Best score: 0.1749: : 341iter [00:33, 11.48iter/s]Best score: 0.1749: : 342iter [00:33, 11.48iter/s]Best score: 0.1749: : 343iter [00:33, 11.57iter/s]Best score: 0.1749: : 343iter [00:33, 11.57iter/s]Best score: 0.1749: : 344iter [00:33, 11.57iter/s]Best score: 0.1749: : 345iter [00:33, 11.62iter/s]Best score: 0.1749: : 345iter [00:33, 11.62iter/s]Best score: 0.1749: : 346iter [00:33, 11.62iter/s]Best score: 0.1749: : 347iter [00:33, 11.66iter/s]Best score: 0.1749: : 347iter [00:33, 11.66iter/s]Best score: 0.1749: : 348iter [00:33, 11.66iter/s]Best score: 0.1749: : 349iter [00:33, 11.70iter/s]
[ITER 350] Best: 0.1749
[PARAMS] Current best parameters:
  fx: 552.8402
  fy: 552.9628
  px: 877.7241
  py: 962.5978
  k1: -0.00288779
  k2: -0.03759925
  k3: 0.02859494
  k4: -0.00719645
  p1: -0.00214449
  p2: 0.00186305
  p3: -0.01026092
  p4: 0.00810644
  s1: 0.0139
  s2: -0.0110
  s3: -0.0009
  s4: -0.0042
  tilt_x: -0.0028
  tilt_y: -0.0205
  scale: 2.9800
  rotation: 0.3818
Best score: 0.1749: : 349iter [00:33, 11.70iter/s]Best score: 0.1749: : 350iter [00:34, 11.70iter/s]Best score: 0.1749: : 351iter [00:34,  7.53iter/s]Best score: 0.1749: : 351iter [00:34,  7.53iter/s]Best score: 0.1749: : 352iter [00:34,  7.53iter/s]Best score: 0.1749: : 353iter [00:34,  8.43iter/s]Best score: 0.1749: : 353iter [00:34,  8.43iter/s]Best score: 0.1749: : 354iter [00:34,  8.43iter/s]Best score: 0.1749: : 355iter [00:34,  9.20iter/s]Best score: 0.1749: : 355iter [00:34,  9.20iter/s]Best score: 0.1749: : 356iter [00:34,  9.20iter/s]Best score: 0.1749: : 357iter [00:34,  9.84iter/s]Best score: 0.1749: : 357iter [00:34,  9.84iter/s]Best score: 0.1749: : 358iter [00:34,  9.84iter/s]Best score: 0.1749: : 359iter [00:34, 10.34iter/s]Best score: 0.1713: : 359iter [00:34, 10.34iter/s]Best score: 0.1713: : 360iter [00:35, 10.34iter/s]Best score: 0.1713: : 361iter [00:35, 10.52iter/s]Best score: 0.1713: : 361iter [00:35, 10.52iter/s]Best score: 0.1713: : 362iter [00:35, 10.52iter/s]Best score: 0.1713: : 363iter [00:35, 10.84iter/s]Best score: 0.1713: : 363iter [00:35, 10.84iter/s]Best score: 0.1713: : 364iter [00:35, 10.84iter/s]Best score: 0.1713: : 365iter [00:35, 11.12iter/s]Best score: 0.1713: : 365iter [00:35, 11.12iter/s]Best score: 0.1713: : 366iter [00:35, 11.12iter/s]Best score: 0.1713: : 367iter [00:35, 11.27iter/s]Best score: 0.1713: : 367iter [00:35, 11.27iter/s]Best score: 0.1713: : 368iter [00:35, 11.27iter/s]Best score: 0.1713: : 369iter [00:35, 11.37iter/s]Best score: 0.1704: : 369iter [00:35, 11.37iter/s]Best score: 0.1704: : 370iter [00:35, 11.37iter/s]Best score: 0.1704: : 371iter [00:35, 11.23iter/s]Best score: 0.1704: : 371iter [00:36, 11.23iter/s]Best score: 0.1704: : 372iter [00:36, 11.23iter/s]Best score: 0.1704: : 373iter [00:36, 11.34iter/s]Best score: 0.1704: : 373iter [00:36, 11.34iter/s]Best score: 0.1704: : 374iter [00:36, 11.34iter/s]Best score: 0.1704: : 375iter [00:36, 11.46iter/s]Best score: 0.1704: : 375iter [00:36, 11.46iter/s]Best score: 0.1704: : 376iter [00:36, 11.46iter/s]Best score: 0.1704: : 377iter [00:36, 11.54iter/s]Best score: 0.1704: : 377iter [00:36, 11.54iter/s]Best score: 0.1704: : 378iter [00:36, 11.54iter/s]Best score: 0.1704: : 379iter [00:36, 11.58iter/s]Best score: 0.1704: : 379iter [00:36, 11.58iter/s]Best score: 0.1704: : 380iter [00:36, 11.58iter/s]Best score: 0.1704: : 381iter [00:36, 11.39iter/s]Best score: 0.1704: : 381iter [00:36, 11.39iter/s]Best score: 0.1704: : 382iter [00:36, 11.39iter/s]Best score: 0.1704: : 383iter [00:36, 11.49iter/s]Best score: 0.1704: : 383iter [00:37, 11.49iter/s]Best score: 0.1704: : 384iter [00:37, 11.49iter/s]Best score: 0.1704: : 385iter [00:37, 11.54iter/s]Best score: 0.1704: : 385iter [00:37, 11.54iter/s]Best score: 0.1704: : 386iter [00:37, 11.54iter/s]Best score: 0.1704: : 387iter [00:37, 11.60iter/s]Best score: 0.1704: : 387iter [00:37, 11.60iter/s]Best score: 0.1704: : 388iter [00:37, 11.60iter/s]Best score: 0.1704: : 389iter [00:37, 11.64iter/s]Best score: 0.1704: : 389iter [00:37, 11.64iter/s]Best score: 0.1704: : 390iter [00:37, 11.64iter/s]Best score: 0.1704: : 391iter [00:37, 11.48iter/s]Best score: 0.1704: : 391iter [00:37, 11.48iter/s]Best score: 0.1704: : 392iter [00:37, 11.48iter/s]Best score: 0.1704: : 393iter [00:37, 11.52iter/s]Best score: 0.1704: : 393iter [00:37, 11.52iter/s]Best score: 0.1704: : 394iter [00:37, 11.52iter/s]Best score: 0.1704: : 395iter [00:37, 11.59iter/s]Best score: 0.1704: : 395iter [00:38, 11.59iter/s]Best score: 0.1704: : 396iter [00:38, 11.59iter/s]Best score: 0.1704: : 397iter [00:38, 11.65iter/s]Best score: 0.1704: : 397iter [00:38, 11.65iter/s]Best score: 0.1704: : 398iter [00:38, 11.65iter/s]Best score: 0.1704: : 399iter [00:38, 11.66iter/s]
[ITER 400] Best: 0.1652
[PARAMS] Current best parameters:
  fx: 555.7613
  fy: 555.7892
  px: 879.2585
  py: 960.9268
  k1: 0.00192975
  k2: -0.04902830
  k3: 0.03457307
  k4: -0.00816498
  p1: -0.00105974
  p2: 0.00123979
  p3: -0.00796231
  p4: 0.01090206
  s1: 0.0135
  s2: -0.0131
  s3: -0.0029
  s4: -0.0089
  tilt_x: -0.0141
  tilt_y: -0.0292
  scale: 2.9735
  rotation: 0.3720
Best score: 0.1652: : 399iter [00:38, 11.66iter/s]Best score: 0.1652: : 400iter [00:38, 11.66iter/s]Best score: 0.1652: : 401iter [00:38,  7.49iter/s]Best score: 0.1652: : 401iter [00:38,  7.49iter/s]Best score: 0.1652: : 402iter [00:38,  7.49iter/s]Best score: 0.1652: : 403iter [00:38,  8.41iter/s]Best score: 0.1652: : 403iter [00:39,  8.41iter/s]Best score: 0.1652: : 404iter [00:39,  8.41iter/s]Best score: 0.1652: : 405iter [00:39,  9.19iter/s]Best score: 0.1652: : 405iter [00:39,  9.19iter/s]Best score: 0.1652: : 406iter [00:39,  9.19iter/s]Best score: 0.1652: : 407iter [00:39,  9.82iter/s]Best score: 0.1652: : 407iter [00:39,  9.82iter/s]Best score: 0.1652: : 408iter [00:39,  9.82iter/s]Best score: 0.1652: : 409iter [00:39, 10.33iter/s]Best score: 0.1639: : 409iter [00:39, 10.33iter/s]Best score: 0.1639: : 410iter [00:39, 10.33iter/s]Best score: 0.1639: : 411iter [00:39, 10.55iter/s]Best score: 0.1639: : 411iter [00:39, 10.55iter/s]Best score: 0.1639: : 412iter [00:39, 10.55iter/s]Best score: 0.1639: : 413iter [00:39, 10.87iter/s]Best score: 0.1639: : 413iter [00:39, 10.87iter/s]Best score: 0.1639: : 414iter [00:40, 10.87iter/s]Best score: 0.1639: : 415iter [00:40, 11.12iter/s]Best score: 0.1639: : 415iter [00:40, 11.12iter/s]Best score: 0.1639: : 416iter [00:40, 11.12iter/s]Best score: 0.1639: : 417iter [00:40, 11.30iter/s]Best score: 0.1639: : 417iter [00:40, 11.30iter/s]Best score: 0.1639: : 418iter [00:40, 11.30iter/s]Best score: 0.1639: : 419iter [00:40, 11.40iter/s]Best score: 0.1639: : 419iter [00:40, 11.40iter/s]Best score: 0.1639: : 420iter [00:40, 11.40iter/s]Best score: 0.1639: : 421iter [00:40, 11.33iter/s]Best score: 0.1639: : 421iter [00:40, 11.33iter/s]Best score: 0.1639: : 422iter [00:40, 11.33iter/s]Best score: 0.1639: : 423iter [00:40, 11.44iter/s]Best score: 0.1639: : 423iter [00:40, 11.44iter/s]Best score: 0.1639: : 424iter [00:40, 11.44iter/s]Best score: 0.1639: : 425iter [00:40, 11.54iter/s]Best score: 0.1639: : 425iter [00:40, 11.54iter/s]Best score: 0.1639: : 426iter [00:41, 11.54iter/s]Best score: 0.1639: : 427iter [00:41, 11.59iter/s]Best score: 0.1639: : 427iter [00:41, 11.59iter/s]Best score: 0.1639: : 428iter [00:41, 11.59iter/s]Best score: 0.1639: : 429iter [00:41, 11.63iter/s]Best score: 0.1637: : 429iter [00:41, 11.63iter/s]Best score: 0.1637: : 430iter [00:41, 11.63iter/s]Best score: 0.1637: : 431iter [00:41, 11.47iter/s]Best score: 0.1637: : 431iter [00:41, 11.47iter/s]Best score: 0.1637: : 432iter [00:41, 11.47iter/s]Best score: 0.1637: : 433iter [00:41, 11.54iter/s]Best score: 0.1637: : 433iter [00:41, 11.54iter/s]Best score: 0.1637: : 434iter [00:41, 11.54iter/s]Best score: 0.1637: : 435iter [00:41, 11.61iter/s]Best score: 0.1637: : 435iter [00:41, 11.61iter/s]Best score: 0.1637: : 436iter [00:41, 11.61iter/s]Best score: 0.1637: : 437iter [00:41, 11.64iter/s]Best score: 0.1637: : 437iter [00:42, 11.64iter/s]Best score: 0.1637: : 438iter [00:42, 11.64iter/s]Best score: 0.1637: : 439iter [00:42, 11.66iter/s]Best score: 0.1637: : 439iter [00:42, 11.66iter/s]Best score: 0.1637: : 440iter [00:42, 11.66iter/s]Best score: 0.1637: : 441iter [00:42, 11.47iter/s]Best score: 0.1637: : 441iter [00:42, 11.47iter/s]Best score: 0.1637: : 442iter [00:42, 11.47iter/s]Best score: 0.1637: : 443iter [00:42, 11.55iter/s]Best score: 0.1637: : 443iter [00:42, 11.55iter/s]Best score: 0.1637: : 444iter [00:42, 11.55iter/s]Best score: 0.1637: : 445iter [00:42, 11.60iter/s]Best score: 0.1637: : 445iter [00:42, 11.60iter/s]Best score: 0.1637: : 446iter [00:42, 11.60iter/s]Best score: 0.1637: : 447iter [00:42, 11.65iter/s]Best score: 0.1637: : 447iter [00:42, 11.65iter/s]Best score: 0.1637: : 448iter [00:42, 11.65iter/s]Best score: 0.1637: : 449iter [00:42, 11.67iter/s]
[ITER 450] Best: 0.1628
[PARAMS] Current best parameters:
  fx: 555.4361
  fy: 555.4081
  px: 878.6783
  py: 960.6884
  k1: -0.00447860
  k2: -0.03535450
  k3: 0.02611964
  k4: -0.00658178
  p1: 0.00026737
  p2: 0.00054169
  p3: -0.01046210
  p4: 0.01471233
  s1: 0.0175
  s2: -0.0180
  s3: -0.0045
  s4: -0.0111
  tilt_x: -0.0175
  tilt_y: -0.0278
  scale: 2.9732
  rotation: 0.4008
Best score: 0.1628: : 449iter [00:43, 11.67iter/s]Best score: 0.1628: : 450iter [00:43, 11.67iter/s]Best score: 0.1628: : 451iter [00:43,  7.51iter/s]Best score: 0.1628: : 451iter [00:43,  7.51iter/s]Best score: 0.1628: : 452iter [00:43,  7.51iter/s]Best score: 0.1628: : 453iter [00:43,  8.41iter/s]Best score: 0.1628: : 453iter [00:43,  8.41iter/s]Best score: 0.1628: : 454iter [00:43,  8.41iter/s]Best score: 0.1628: : 455iter [00:43,  9.20iter/s]Best score: 0.1628: : 455iter [00:43,  9.20iter/s]Best score: 0.1628: : 456iter [00:43,  9.20iter/s]Best score: 0.1628: : 457iter [00:43,  9.83iter/s]Best score: 0.1628: : 457iter [00:44,  9.83iter/s]Best score: 0.1628: : 458iter [00:44,  9.83iter/s]Best score: 0.1628: : 459iter [00:44, 10.34iter/s]Best score: 0.1608: : 459iter [00:44, 10.34iter/s]Best score: 0.1608: : 460iter [00:44, 10.34iter/s]Best score: 0.1608: : 461iter [00:44, 10.55iter/s]Best score: 0.1608: : 461iter [00:44, 10.55iter/s]Best score: 0.1608: : 462iter [00:44, 10.55iter/s]Best score: 0.1608: : 463iter [00:44, 10.89iter/s]Best score: 0.1608: : 463iter [00:44, 10.89iter/s]Best score: 0.1608: : 464iter [00:44, 10.89iter/s]Best score: 0.1608: : 465iter [00:44, 11.13iter/s]Best score: 0.1608: : 465iter [00:44, 11.13iter/s]Best score: 0.1608: : 466iter [00:44, 11.13iter/s]Best score: 0.1608: : 467iter [00:44, 11.28iter/s]Best score: 0.1608: : 467iter [00:44, 11.28iter/s]Best score: 0.1608: : 468iter [00:44, 11.28iter/s]Best score: 0.1608: : 469iter [00:44, 11.42iter/s]Best score: 0.1581: : 469iter [00:45, 11.42iter/s]Best score: 0.1581: : 470iter [00:45, 11.42iter/s]Best score: 0.1581: : 471iter [00:45, 11.33iter/s]Best score: 0.1581: : 471iter [00:45, 11.33iter/s]Best score: 0.1581: : 472iter [00:45, 11.33iter/s]Best score: 0.1581: : 473iter [00:45, 11.45iter/s]Best score: 0.1581: : 473iter [00:45, 11.45iter/s]Best score: 0.1581: : 474iter [00:45, 11.45iter/s]Best score: 0.1581: : 475iter [00:45, 11.52iter/s]Best score: 0.1581: : 475iter [00:45, 11.52iter/s]Best score: 0.1581: : 476iter [00:45, 11.52iter/s]Best score: 0.1581: : 477iter [00:45, 11.57iter/s]Best score: 0.1581: : 477iter [00:45, 11.57iter/s]Best score: 0.1581: : 478iter [00:45, 11.57iter/s]Best score: 0.1581: : 479iter [00:45, 11.61iter/s]Best score: 0.1513: : 479iter [00:45, 11.61iter/s]Best score: 0.1513: : 480iter [00:46, 11.61iter/s]Best score: 0.1513: : 481iter [00:46, 11.45iter/s]Best score: 0.1513: : 481iter [00:46, 11.45iter/s]Best score: 0.1513: : 482iter [00:46, 11.45iter/s]Best score: 0.1513: : 483iter [00:46, 11.51iter/s]Best score: 0.1513: : 483iter [00:46, 11.51iter/s]Best score: 0.1513: : 484iter [00:46, 11.51iter/s]Best score: 0.1513: : 485iter [00:46, 11.56iter/s]Best score: 0.1513: : 485iter [00:46, 11.56iter/s]Best score: 0.1513: : 486iter [00:46, 11.56iter/s]Best score: 0.1513: : 487iter [00:46, 11.61iter/s]Best score: 0.1513: : 487iter [00:46, 11.61iter/s]Best score: 0.1513: : 488iter [00:46, 11.61iter/s]Best score: 0.1513: : 489iter [00:46, 11.65iter/s]Best score: 0.1513: : 489iter [00:46, 11.65iter/s]Best score: 0.1513: : 490iter [00:46, 11.65iter/s]Best score: 0.1513: : 491iter [00:46, 11.47iter/s]Best score: 0.1513: : 491iter [00:46, 11.47iter/s]Best score: 0.1513: : 492iter [00:47, 11.47iter/s]Best score: 0.1513: : 493iter [00:47, 11.55iter/s]Best score: 0.1513: : 493iter [00:47, 11.55iter/s]Best score: 0.1513: : 494iter [00:47, 11.55iter/s]Best score: 0.1513: : 495iter [00:47, 11.62iter/s]Best score: 0.1513: : 495iter [00:47, 11.62iter/s]Best score: 0.1513: : 496iter [00:47, 11.62iter/s]Best score: 0.1513: : 497iter [00:47, 11.61iter/s]Best score: 0.1513: : 497iter [00:47, 11.61iter/s]Best score: 0.1513: : 498iter [00:47, 11.61iter/s]Best score: 0.1513: : 499iter [00:47, 11.65iter/s]
[ITER 500] Best: 0.1497
[PARAMS] Current best parameters:
  fx: 555.2802
  fy: 555.3827
  px: 876.9266
  py: 960.7255
  k1: -0.00698559
  k2: -0.03289329
  k3: 0.02491111
  k4: -0.00623061
  p1: -0.00306391
  p2: -0.00104618
  p3: -0.00320237
  p4: 0.01055626
  s1: 0.0088
  s2: -0.0124
  s3: -0.0061
  s4: -0.0086
  tilt_x: -0.0106
  tilt_y: -0.0218
  scale: 2.9792
  rotation: 0.4034
Best score: 0.1497: : 499iter [00:47, 11.65iter/s]Best score: 0.1497: : 500iter [00:48, 11.65iter/s]Best score: 0.1497: : 501iter [00:48,  7.53iter/s]Best score: 0.1497: : 501iter [00:48,  7.53iter/s]Best score: 0.1497: : 502iter [00:48,  7.53iter/s]Best score: 0.1497: : 503iter [00:48,  8.41iter/s]Best score: 0.1497: : 503iter [00:48,  8.41iter/s]Best score: 0.1497: : 504iter [00:48,  8.41iter/s]Best score: 0.1497: : 505iter [00:48,  9.18iter/s]Best score: 0.1497: : 505iter [00:48,  9.18iter/s]Best score: 0.1497: : 506iter [00:48,  9.18iter/s]Best score: 0.1497: : 507iter [00:48,  9.81iter/s]Best score: 0.1497: : 507iter [00:48,  9.81iter/s]Best score: 0.1497: : 508iter [00:48,  9.81iter/s]Best score: 0.1497: : 509iter [00:48, 10.30iter/s]Best score: 0.1476: : 509iter [00:48, 10.30iter/s]Best score: 0.1476: : 510iter [00:48, 10.30iter/s]Best score: 0.1476: : 511iter [00:48, 10.50iter/s]Best score: 0.1476: : 511iter [00:49, 10.50iter/s]Best score: 0.1476: : 512iter [00:49, 10.50iter/s]Best score: 0.1476: : 513iter [00:49, 10.84iter/s]Best score: 0.1476: : 513iter [00:49, 10.84iter/s]Best score: 0.1476: : 514iter [00:49, 10.84iter/s]Best score: 0.1476: : 515iter [00:49, 11.09iter/s]Best score: 0.1476: : 515iter [00:49, 11.09iter/s]Best score: 0.1476: : 516iter [00:49, 11.09iter/s]Best score: 0.1476: : 517iter [00:49, 11.27iter/s]Best score: 0.1476: : 517iter [00:49, 11.27iter/s]Best score: 0.1476: : 518iter [00:49, 11.27iter/s]Best score: 0.1476: : 519iter [00:49, 11.40iter/s]Best score: 0.1476: : 519iter [00:49, 11.40iter/s]Best score: 0.1476: : 520iter [00:49, 11.40iter/s]Best score: 0.1476: : 521iter [00:49, 11.29iter/s]Best score: 0.1476: : 521iter [00:49, 11.29iter/s]Best score: 0.1476: : 522iter [00:49, 11.29iter/s]Best score: 0.1476: : 523iter [00:49, 11.41iter/s]Best score: 0.1476: : 523iter [00:50, 11.41iter/s]Best score: 0.1476: : 524iter [00:50, 11.41iter/s]Best score: 0.1476: : 525iter [00:50, 11.50iter/s]Best score: 0.1476: : 525iter [00:50, 11.50iter/s]Best score: 0.1476: : 526iter [00:50, 11.50iter/s]Best score: 0.1476: : 527iter [00:50, 11.50iter/s]Best score: 0.1476: : 527iter [00:50, 11.50iter/s]Best score: 0.1476: : 528iter [00:50, 11.50iter/s]Best score: 0.1476: : 529iter [00:50, 11.44iter/s]Best score: 0.1453: : 529iter [00:50, 11.44iter/s]Best score: 0.1453: : 530iter [00:50, 11.44iter/s]Best score: 0.1453: : 531iter [00:50, 11.22iter/s]Best score: 0.1453: : 531iter [00:50, 11.22iter/s]Best score: 0.1453: : 532iter [00:50, 11.22iter/s]Best score: 0.1453: : 533iter [00:50, 11.25iter/s]Best score: 0.1453: : 533iter [00:50, 11.25iter/s]Best score: 0.1453: : 534iter [00:51, 11.25iter/s]Best score: 0.1453: : 535iter [00:51, 11.33iter/s]Best score: 0.1453: : 535iter [00:51, 11.33iter/s]Best score: 0.1453: : 536iter [00:51, 11.33iter/s]Best score: 0.1453: : 537iter [00:51, 11.44iter/s]Best score: 0.1453: : 537iter [00:51, 11.44iter/s]Best score: 0.1453: : 538iter [00:51, 11.44iter/s]Best score: 0.1453: : 539iter [00:51, 11.51iter/s]Best score: 0.1453: : 539iter [00:51, 11.51iter/s]Best score: 0.1453: : 540iter [00:51, 11.51iter/s]Best score: 0.1453: : 541iter [00:51, 11.32iter/s]Best score: 0.1453: : 541iter [00:51, 11.32iter/s]Best score: 0.1453: : 542iter [00:51, 11.32iter/s]Best score: 0.1453: : 543iter [00:51, 11.38iter/s]Best score: 0.1453: : 543iter [00:51, 11.38iter/s]Best score: 0.1453: : 544iter [00:51, 11.38iter/s]Best score: 0.1453: : 545iter [00:51, 11.34iter/s]Best score: 0.1453: : 545iter [00:51, 11.34iter/s]Best score: 0.1453: : 546iter [00:52, 11.34iter/s]Best score: 0.1453: : 547iter [00:52, 11.44iter/s]Best score: 0.1453: : 547iter [00:52, 11.44iter/s]Best score: 0.1453: : 548iter [00:52, 11.44iter/s]Best score: 0.1453: : 549iter [00:52, 11.48iter/s]
[ITER 550] Best: 0.1453
[PARAMS] Current best parameters:
  fx: 555.0784
  fy: 555.1387
  px: 874.4233
  py: 960.4187
  k1: -0.00943102
  k2: -0.02727405
  k3: 0.02106974
  k4: -0.00539874
  p1: -0.00409196
  p2: -0.00456050
  p3: 0.00013236
  p4: 0.01382645
  s1: 0.0059
  s2: -0.0152
  s3: -0.0090
  s4: -0.0118
  tilt_x: -0.0099
  tilt_y: -0.0167
  scale: 2.9792
  rotation: 0.3958
Best score: 0.1453: : 549iter [00:52, 11.48iter/s]Best score: 0.1453: : 550iter [00:52, 11.48iter/s]Best score: 0.1453: : 551iter [00:52,  7.46iter/s]Best score: 0.1453: : 551iter [00:52,  7.46iter/s]Best score: 0.1453: : 552iter [00:52,  7.46iter/s]Best score: 0.1453: : 553iter [00:52,  8.35iter/s]Best score: 0.1453: : 553iter [00:52,  8.35iter/s]Best score: 0.1453: : 554iter [00:53,  8.35iter/s]Best score: 0.1453: : 555iter [00:53,  9.06iter/s]Best score: 0.1453: : 555iter [00:53,  9.06iter/s]Best score: 0.1453: : 556iter [00:53,  9.06iter/s]Best score: 0.1453: : 557iter [00:53,  9.69iter/s]Best score: 0.1453: : 557iter [00:53,  9.69iter/s]Best score: 0.1453: : 558iter [00:53,  9.69iter/s]Best score: 0.1453: : 559iter [00:53, 10.21iter/s]Best score: 0.1428: : 559iter [00:53, 10.21iter/s]Best score: 0.1428: : 560iter [00:53, 10.21iter/s]Best score: 0.1428: : 561iter [00:53, 10.46iter/s]Best score: 0.1428: : 561iter [00:53, 10.46iter/s]Best score: 0.1428: : 562iter [00:53, 10.46iter/s]Best score: 0.1428: : 563iter [00:53, 10.80iter/s]Best score: 0.1428: : 563iter [00:53, 10.80iter/s]Best score: 0.1428: : 564iter [00:53, 10.80iter/s]Best score: 0.1428: : 565iter [00:53, 11.07iter/s]Best score: 0.1428: : 565iter [00:54, 11.07iter/s]Best score: 0.1428: : 566iter [00:54, 11.07iter/s]Best score: 0.1428: : 567iter [00:54, 11.22iter/s]Best score: 0.1428: : 567iter [00:54, 11.22iter/s]Best score: 0.1428: : 568iter [00:54, 11.22iter/s]Best score: 0.1428: : 569iter [00:54, 11.36iter/s]Best score: 0.1421: : 569iter [00:54, 11.36iter/s]Best score: 0.1421: : 570iter [00:54, 11.36iter/s]Best score: 0.1421: : 571iter [00:54, 11.27iter/s]Best score: 0.1421: : 571iter [00:54, 11.27iter/s]Best score: 0.1421: : 572iter [00:54, 11.27iter/s]Best score: 0.1421: : 573iter [00:54, 11.41iter/s]Best score: 0.1421: : 573iter [00:54, 11.41iter/s]Best score: 0.1421: : 574iter [00:54, 11.41iter/s]Best score: 0.1421: : 575iter [00:54, 11.49iter/s]Best score: 0.1421: : 575iter [00:54, 11.49iter/s]Best score: 0.1421: : 576iter [00:54, 11.49iter/s]Best score: 0.1421: : 577iter [00:54, 11.53iter/s]Best score: 0.1421: : 577iter [00:55, 11.53iter/s]Best score: 0.1421: : 578iter [00:55, 11.53iter/s]Best score: 0.1421: : 579iter [00:55, 11.60iter/s]Best score: 0.1421: : 579iter [00:55, 11.60iter/s]Best score: 0.1421: : 580iter [00:55, 11.60iter/s]Best score: 0.1421: : 581iter [00:55, 11.45iter/s]Best score: 0.1421: : 581iter [00:55, 11.45iter/s]Best score: 0.1421: : 582iter [00:55, 11.45iter/s]Best score: 0.1421: : 583iter [00:55, 11.54iter/s]Best score: 0.1421: : 583iter [00:55, 11.54iter/s]Best score: 0.1421: : 584iter [00:55, 11.54iter/s]Best score: 0.1421: : 585iter [00:55, 11.59iter/s]Best score: 0.1421: : 585iter [00:55, 11.59iter/s]Best score: 0.1421: : 586iter [00:55, 11.59iter/s]Best score: 0.1421: : 587iter [00:55, 11.63iter/s]Best score: 0.1421: : 587iter [00:55, 11.63iter/s]Best score: 0.1421: : 588iter [00:56, 11.63iter/s]Best score: 0.1421: : 589iter [00:56, 11.65iter/s]Best score: 0.1416: : 589iter [00:56, 11.65iter/s]Best score: 0.1416: : 590iter [00:56, 11.65iter/s]Best score: 0.1416: : 591iter [00:56, 11.46iter/s]Best score: 0.1416: : 591iter [00:56, 11.46iter/s]Best score: 0.1416: : 592iter [00:56, 11.46iter/s]Best score: 0.1416: : 593iter [00:56, 11.54iter/s]Best score: 0.1416: : 593iter [00:56, 11.54iter/s]Best score: 0.1416: : 594iter [00:56, 11.54iter/s]Best score: 0.1416: : 595iter [00:56, 11.60iter/s]Best score: 0.1416: : 595iter [00:56, 11.60iter/s]Best score: 0.1416: : 596iter [00:56, 11.60iter/s]Best score: 0.1416: : 597iter [00:56, 11.64iter/s]Best score: 0.1416: : 597iter [00:56, 11.64iter/s]Best score: 0.1416: : 598iter [00:56, 11.64iter/s]Best score: 0.1416: : 599iter [00:56, 11.66iter/s]
[ITER 600] Best: 0.1412
[PARAMS] Current best parameters:
  fx: 556.3754
  fy: 556.3682
  px: 873.6985
  py: 958.9496
  k1: -0.01821371
  k2: -0.01295813
  k3: 0.01149512
  k4: -0.00315871
  p1: -0.00650826
  p2: -0.00587556
  p3: 0.00530463
  p4: 0.01008364
  s1: 0.0020
  s2: -0.0120
  s3: -0.0115
  s4: -0.0094
  tilt_x: -0.0126
  tilt_y: -0.0156
  scale: 2.9829
  rotation: 0.3830
Best score: 0.1412: : 599iter [00:56, 11.66iter/s]Best score: 0.1412: : 600iter [00:57, 11.66iter/s]Best score: 0.1412: : 601iter [00:57,  7.52iter/s]Best score: 0.1412: : 601iter [00:57,  7.52iter/s]Best score: 0.1412: : 602iter [00:57,  7.52iter/s]Best score: 0.1412: : 603iter [00:57,  8.43iter/s]Best score: 0.1412: : 603iter [00:57,  8.43iter/s]Best score: 0.1412: : 604iter [00:57,  8.43iter/s]Best score: 0.1412: : 605iter [00:57,  9.21iter/s]Best score: 0.1412: : 605iter [00:57,  9.21iter/s]Best score: 0.1412: : 606iter [00:57,  9.21iter/s]Best score: 0.1412: : 607iter [00:57,  9.84iter/s]Best score: 0.1412: : 607iter [00:57,  9.84iter/s]Best score: 0.1412: : 608iter [00:58,  9.84iter/s]Best score: 0.1412: : 609iter [00:58, 10.34iter/s]Best score: 0.1404: : 609iter [00:58, 10.34iter/s]Best score: 0.1404: : 610iter [00:58, 10.34iter/s]Best score: 0.1404: : 611iter [00:58, 10.56iter/s]Best score: 0.1404: : 611iter [00:58, 10.56iter/s]Best score: 0.1404: : 612iter [00:58, 10.56iter/s]Best score: 0.1404: : 613iter [00:58, 10.86iter/s]Best score: 0.1404: : 613iter [00:58, 10.86iter/s]Best score: 0.1404: : 614iter [00:58, 10.86iter/s]Best score: 0.1404: : 615iter [00:58, 11.11iter/s]Best score: 0.1404: : 615iter [00:58, 11.11iter/s]Best score: 0.1404: : 616iter [00:58, 11.11iter/s]Best score: 0.1404: : 617iter [00:58, 11.29iter/s]Best score: 0.1404: : 617iter [00:58, 11.29iter/s]Best score: 0.1404: : 618iter [00:58, 11.29iter/s]Best score: 0.1404: : 619iter [00:58, 11.43iter/s]Best score: 0.1400: : 619iter [00:59, 11.43iter/s]Best score: 0.1400: : 620iter [00:59, 11.43iter/s]Best score: 0.1400: : 621iter [00:59, 11.33iter/s]Best score: 0.1400: : 621iter [00:59, 11.33iter/s]Best score: 0.1400: : 622iter [00:59, 11.33iter/s]Best score: 0.1400: : 623iter [00:59, 11.45iter/s]Best score: 0.1400: : 623iter [00:59, 11.45iter/s]Best score: 0.1400: : 624iter [00:59, 11.45iter/s]Best score: 0.1400: : 625iter [00:59, 11.53iter/s]Best score: 0.1400: : 625iter [00:59, 11.53iter/s]Best score: 0.1400: : 626iter [00:59, 11.53iter/s]Best score: 0.1400: : 627iter [00:59, 11.58iter/s]Best score: 0.1400: : 627iter [00:59, 11.58iter/s]Best score: 0.1400: : 628iter [00:59, 11.58iter/s]Best score: 0.1400: : 629iter [00:59, 11.61iter/s]Best score: 0.1397: : 629iter [00:59, 11.61iter/s]Best score: 0.1397: : 630iter [00:59, 11.61iter/s]Best score: 0.1397: : 631iter [00:59, 11.43iter/s]Best score: 0.1397: : 631iter [01:00, 11.43iter/s]Best score: 0.1397: : 632iter [01:00, 11.43iter/s]Best score: 0.1397: : 633iter [01:00, 11.46iter/s]Best score: 0.1397: : 633iter [01:00, 11.46iter/s]Best score: 0.1397: : 634iter [01:00, 11.46iter/s]Best score: 0.1397: : 635iter [01:00, 11.52iter/s]Best score: 0.1397: : 635iter [01:00, 11.52iter/s]Best score: 0.1397: : 636iter [01:00, 11.52iter/s]Best score: 0.1397: : 637iter [01:00, 11.59iter/s]Best score: 0.1397: : 637iter [01:00, 11.59iter/s]Best score: 0.1397: : 638iter [01:00, 11.59iter/s]Best score: 0.1397: : 639iter [01:00, 11.63iter/s]Best score: 0.1392: : 639iter [01:00, 11.63iter/s]Best score: 0.1392: : 640iter [01:00, 11.63iter/s]Best score: 0.1392: : 641iter [01:00, 11.46iter/s]Best score: 0.1392: : 641iter [01:00, 11.46iter/s]Best score: 0.1392: : 642iter [01:00, 11.46iter/s]Best score: 0.1392: : 643iter [01:00, 11.49iter/s]Best score: 0.1392: : 643iter [01:01, 11.49iter/s]Best score: 0.1392: : 644iter [01:01, 11.49iter/s]Best score: 0.1392: : 645iter [01:01, 11.50iter/s]Best score: 0.1392: : 645iter [01:01, 11.50iter/s]Best score: 0.1392: : 646iter [01:01, 11.50iter/s]Best score: 0.1392: : 647iter [01:01, 11.49iter/s]Best score: 0.1392: : 647iter [01:01, 11.49iter/s]Best score: 0.1392: : 648iter [01:01, 11.49iter/s]Best score: 0.1392: : 649iter [01:01, 11.49iter/s]
[ITER 650] Best: 0.1392
[PARAMS] Current best parameters:
  fx: 554.1376
  fy: 554.1304
  px: 875.4459
  py: 957.9290
  k1: -0.02101722
  k2: -0.00370489
  k3: 0.00506538
  k4: -0.00163642
  p1: -0.00726238
  p2: -0.00517620
  p3: 0.00714062
  p4: 0.00603394
  s1: 0.0015
  s2: -0.0083
  s3: -0.0141
  s4: -0.0046
  tilt_x: -0.0160
  tilt_y: -0.0227
  scale: 2.9881
  rotation: 0.3934
Best score: 0.1392: : 649iter [01:01, 11.49iter/s]Best score: 0.1392: : 650iter [01:02, 11.49iter/s]Best score: 0.1392: : 651iter [01:02,  7.48iter/s]Best score: 0.1392: : 651iter [01:02,  7.48iter/s]Best score: 0.1392: : 652iter [01:02,  7.48iter/s]Best score: 0.1392: : 653iter [01:02,  8.38iter/s]Best score: 0.1392: : 653iter [01:02,  8.38iter/s]Best score: 0.1392: : 654iter [01:02,  8.38iter/s]Best score: 0.1392: : 655iter [01:02,  9.16iter/s]Best score: 0.1392: : 655iter [01:02,  9.16iter/s]Best score: 0.1392: : 656iter [01:02,  9.16iter/s]Best score: 0.1392: : 657iter [01:02,  9.78iter/s]Best score: 0.1392: : 657iter [01:02,  9.78iter/s]Best score: 0.1392: : 658iter [01:02,  9.78iter/s]Best score: 0.1392: : 659iter [01:02, 10.25iter/s]Best score: 0.1392: : 659iter [01:02, 10.25iter/s]Best score: 0.1392: : 660iter [01:02, 10.25iter/s]Best score: 0.1392: : 661iter [01:02, 10.48iter/s]Best score: 0.1392: : 661iter [01:02, 10.48iter/s]Best score: 0.1392: : 662iter [01:03, 10.48iter/s]Best score: 0.1392: : 663iter [01:03, 10.81iter/s]Best score: 0.1392: : 663iter [01:03, 10.81iter/s]Best score: 0.1392: : 664iter [01:03, 10.81iter/s]Best score: 0.1392: : 665iter [01:03, 11.07iter/s]Best score: 0.1392: : 665iter [01:03, 11.07iter/s]Best score: 0.1392: : 666iter [01:03, 11.07iter/s]Best score: 0.1392: : 667iter [01:03, 11.22iter/s]Best score: 0.1392: : 667iter [01:03, 11.22iter/s]Best score: 0.1392: : 668iter [01:03, 11.22iter/s]Best score: 0.1392: : 669iter [01:03, 11.37iter/s]Best score: 0.1392: : 669iter [01:03, 11.37iter/s]Best score: 0.1392: : 670iter [01:03, 11.37iter/s]Best score: 0.1392: : 671iter [01:03, 11.28iter/s]Best score: 0.1392: : 671iter [01:03, 11.28iter/s]Best score: 0.1392: : 672iter [01:03, 11.28iter/s]Best score: 0.1392: : 673iter [01:03, 11.40iter/s]Best score: 0.1392: : 673iter [01:03, 11.40iter/s]Best score: 0.1392: : 674iter [01:04, 11.40iter/s]Best score: 0.1392: : 675iter [01:04, 11.49iter/s]Best score: 0.1392: : 675iter [01:04, 11.49iter/s]Best score: 0.1392: : 676iter [01:04, 11.49iter/s]Best score: 0.1392: : 677iter [01:04, 11.55iter/s]Best score: 0.1392: : 677iter [01:04, 11.55iter/s]Best score: 0.1392: : 678iter [01:04, 11.55iter/s]Best score: 0.1392: : 679iter [01:04, 11.59iter/s]Best score: 0.1387: : 679iter [01:04, 11.59iter/s]Best score: 0.1387: : 680iter [01:04, 11.59iter/s]Best score: 0.1387: : 681iter [01:04, 11.36iter/s]Best score: 0.1387: : 681iter [01:04, 11.36iter/s]Best score: 0.1387: : 682iter [01:04, 11.36iter/s]Best score: 0.1387: : 683iter [01:04, 11.46iter/s]Best score: 0.1387: : 683iter [01:04, 11.46iter/s]Best score: 0.1387: : 684iter [01:04, 11.46iter/s]Best score: 0.1387: : 685iter [01:04, 11.53iter/s]Best score: 0.1387: : 685iter [01:05, 11.53iter/s]Best score: 0.1387: : 686iter [01:05, 11.53iter/s]Best score: 0.1387: : 687iter [01:05, 11.56iter/s]Best score: 0.1387: : 687iter [01:05, 11.56iter/s]Best score: 0.1387: : 688iter [01:05, 11.56iter/s]Best score: 0.1387: : 689iter [01:05, 11.51iter/s]Best score: 0.1382: : 689iter [01:05, 11.51iter/s]Best score: 0.1382: : 690iter [01:05, 11.51iter/s]Best score: 0.1382: : 691iter [01:05, 11.36iter/s]Best score: 0.1382: : 691iter [01:05, 11.36iter/s]Best score: 0.1382: : 692iter [01:05, 11.36iter/s]Best score: 0.1382: : 693iter [01:05, 11.46iter/s]Best score: 0.1382: : 693iter [01:05, 11.46iter/s]Best score: 0.1382: : 694iter [01:05, 11.46iter/s]Best score: 0.1382: : 695iter [01:05, 11.55iter/s]Best score: 0.1382: : 695iter [01:05, 11.55iter/s]Best score: 0.1382: : 696iter [01:05, 11.55iter/s]Best score: 0.1382: : 697iter [01:05, 11.60iter/s]Best score: 0.1382: : 697iter [01:06, 11.60iter/s]Best score: 0.1382: : 698iter [01:06, 11.60iter/s]Best score: 0.1382: : 699iter [01:06, 11.63iter/s]
[ITER 700] Best: 0.1382
[PARAMS] Current best parameters:
  fx: 553.6667
  fy: 553.6754
  px: 875.1998
  py: 957.9751
  k1: -0.02228538
  k2: -0.00118899
  k3: 0.00376553
  k4: -0.00142970
  p1: -0.00717386
  p2: -0.00587608
  p3: 0.00843713
  p4: 0.00580421
  s1: 0.0006
  s2: -0.0081
  s3: -0.0154
  s4: -0.0045
  tilt_x: -0.0161
  tilt_y: -0.0231
  scale: 2.9904
  rotation: 0.3921
Best score: 0.1382: : 699iter [01:06, 11.63iter/s]Best score: 0.1382: : 700iter [01:06, 11.63iter/s]Best score: 0.1382: : 701iter [01:06,  6.45iter/s]Best score: 0.1382: : 701iter [01:06,  6.45iter/s]Best score: 0.1382: : 702iter [01:06,  6.45iter/s]Best score: 0.1382: : 703iter [01:06,  7.45iter/s]Best score: 0.1382: : 703iter [01:07,  7.45iter/s]Best score: 0.1382: : 704iter [01:07,  7.45iter/s]Best score: 0.1382: : 705iter [01:07,  8.37iter/s]Best score: 0.1382: : 705iter [01:07,  8.37iter/s]Best score: 0.1382: : 706iter [01:07,  8.37iter/s]Best score: 0.1382: : 707iter [01:07,  9.16iter/s]Best score: 0.1382: : 707iter [01:07,  9.16iter/s]Best score: 0.1382: : 708iter [01:07,  9.16iter/s]Best score: 0.1382: : 709iter [01:07,  9.80iter/s]Best score: 0.1382: : 709iter [01:07,  9.80iter/s]Best score: 0.1382: : 710iter [01:07,  9.80iter/s]Best score: 0.1382: : 711iter [01:07, 10.15iter/s]Best score: 0.1382: : 711iter [01:07, 10.15iter/s]Best score: 0.1382: : 712iter [01:07, 10.15iter/s]Best score: 0.1382: : 713iter [01:07, 10.57iter/s]Best score: 0.1382: : 713iter [01:07, 10.57iter/s]Best score: 0.1382: : 714iter [01:07, 10.57iter/s]Best score: 0.1382: : 715iter [01:07, 10.90iter/s]Best score: 0.1382: : 715iter [01:08, 10.90iter/s]Best score: 0.1382: : 716iter [01:08, 10.90iter/s]Best score: 0.1382: : 717iter [01:08, 11.13iter/s]Best score: 0.1382: : 717iter [01:08, 11.13iter/s]Best score: 0.1382: : 718iter [01:08, 11.13iter/s]Best score: 0.1382: : 719iter [01:08, 11.31iter/s]Best score: 0.1382: : 719iter [01:08, 11.31iter/s]Best score: 0.1382: : 720iter [01:08, 11.31iter/s]Best score: 0.1382: : 721iter [01:08, 11.22iter/s]Best score: 0.1382: : 721iter [01:08, 11.22iter/s]Best score: 0.1382: : 722iter [01:08, 11.22iter/s]Best score: 0.1382: : 723iter [01:08, 11.36iter/s]Best score: 0.1382: : 723iter [01:08, 11.36iter/s]Best score: 0.1382: : 724iter [01:08, 11.36iter/s]Best score: 0.1382: : 725iter [01:08, 11.48iter/s]Best score: 0.1382: : 725iter [01:08, 11.48iter/s]Best score: 0.1382: : 726iter [01:09, 11.48iter/s]Best score: 0.1382: : 727iter [01:09, 11.56iter/s]Best score: 0.1382: : 727iter [01:09, 11.56iter/s]Best score: 0.1382: : 728iter [01:09, 11.56iter/s]Best score: 0.1382: : 729iter [01:09, 11.61iter/s]Best score: 0.1381: : 729iter [01:09, 11.61iter/s]Best score: 0.1381: : 730iter [01:09, 11.61iter/s]Best score: 0.1381: : 731iter [01:09, 11.45iter/s]Best score: 0.1381: : 731iter [01:09, 11.45iter/s]Best score: 0.1381: : 732iter [01:09, 11.45iter/s]Best score: 0.1381: : 733iter [01:09, 11.53iter/s]Best score: 0.1381: : 733iter [01:09, 11.53iter/s]Best score: 0.1381: : 734iter [01:09, 11.53iter/s]Best score: 0.1381: : 735iter [01:09, 11.60iter/s]Best score: 0.1381: : 735iter [01:09, 11.60iter/s]Best score: 0.1381: : 736iter [01:09, 11.60iter/s]Best score: 0.1381: : 737iter [01:09, 11.64iter/s]Best score: 0.1381: : 737iter [01:09, 11.64iter/s]Best score: 0.1381: : 738iter [01:10, 11.64iter/s]Best score: 0.1381: : 739iter [01:10, 11.68iter/s]Best score: 0.1380: : 739iter [01:10, 11.68iter/s]Best score: 0.1380: : 740iter [01:10, 11.68iter/s]Best score: 0.1380: : 741iter [01:10, 11.44iter/s]Best score: 0.1380: : 741iter [01:10, 11.44iter/s]Best score: 0.1380: : 742iter [01:10, 11.44iter/s]Best score: 0.1380: : 743iter [01:10, 11.52iter/s]Best score: 0.1380: : 743iter [01:10, 11.52iter/s]Best score: 0.1380: : 744iter [01:10, 11.52iter/s]Best score: 0.1380: : 745iter [01:10, 11.60iter/s]Best score: 0.1380: : 745iter [01:10, 11.60iter/s]Best score: 0.1380: : 746iter [01:10, 11.60iter/s]Best score: 0.1380: : 747iter [01:10, 11.63iter/s]Best score: 0.1380: : 747iter [01:10, 11.63iter/s]Best score: 0.1380: : 748iter [01:10, 11.63iter/s]Best score: 0.1380: : 749iter [01:10, 11.66iter/s]
[ITER 750] Best: 0.1378
[PARAMS] Current best parameters:
  fx: 549.9487
  fy: 549.9542
  px: 874.7483
  py: 957.7793
  k1: -0.02176645
  k2: 0.00497569
  k3: -0.00085396
  k4: -0.00033819
  p1: -0.00921402
  p2: -0.00763680
  p3: 0.01134428
  p4: 0.00393797
  s1: -0.0013
  s2: -0.0059
  s3: -0.0164
  s4: -0.0026
  tilt_x: -0.0128
  tilt_y: -0.0243
  scale: 2.9942
  rotation: 0.3888
Best score: 0.1378: : 749iter [01:11, 11.66iter/s]Best score: 0.1378: : 750iter [01:11, 11.66iter/s]Best score: 0.1378: : 751iter [01:11,  7.54iter/s]Best score: 0.1378: : 751iter [01:11,  7.54iter/s]Best score: 0.1378: : 752iter [01:11,  7.54iter/s]Best score: 0.1378: : 753iter [01:11,  8.41iter/s]Best score: 0.1378: : 753iter [01:11,  8.41iter/s]Best score: 0.1378: : 754iter [01:11,  8.41iter/s]Best score: 0.1378: : 755iter [01:11,  9.19iter/s]Best score: 0.1378: : 755iter [01:11,  9.19iter/s]Best score: 0.1378: : 756iter [01:11,  9.19iter/s]Best score: 0.1378: : 757iter [01:11,  9.83iter/s]Best score: 0.1378: : 757iter [01:12,  9.83iter/s]Best score: 0.1378: : 758iter [01:12,  9.83iter/s]Best score: 0.1378: : 759iter [01:12, 10.33iter/s]Best score: 0.1377: : 759iter [01:12, 10.33iter/s]Best score: 0.1377: : 760iter [01:12, 10.33iter/s]Best score: 0.1377: : 761iter [01:12, 10.51iter/s]Best score: 0.1377: : 761iter [01:12, 10.51iter/s]Best score: 0.1377: : 762iter [01:12, 10.51iter/s]Best score: 0.1377: : 763iter [01:12, 10.82iter/s]Best score: 0.1377: : 763iter [01:12, 10.82iter/s]Best score: 0.1377: : 764iter [01:12, 10.82iter/s]Best score: 0.1377: : 765iter [01:12, 11.06iter/s]Best score: 0.1377: : 765iter [01:12, 11.06iter/s]Best score: 0.1377: : 766iter [01:12, 11.06iter/s]Best score: 0.1377: : 767iter [01:12, 11.21iter/s]Best score: 0.1377: : 767iter [01:12, 11.21iter/s]Best score: 0.1377: : 768iter [01:12, 11.21iter/s]Best score: 0.1377: : 769iter [01:12, 11.27iter/s]Best score: 0.1377: : 769iter [01:13, 11.27iter/s]Best score: 0.1377: : 770iter [01:13, 11.27iter/s]Best score: 0.1377: : 771iter [01:13, 11.15iter/s]Best score: 0.1377: : 771iter [01:13, 11.15iter/s]Best score: 0.1377: : 772iter [01:13, 11.15iter/s]Best score: 0.1377: : 773iter [01:13, 11.22iter/s]Best score: 0.1377: : 773iter [01:13, 11.22iter/s]Best score: 0.1377: : 774iter [01:13, 11.22iter/s]Best score: 0.1377: : 775iter [01:13, 11.28iter/s]Best score: 0.1377: : 775iter [01:13, 11.28iter/s]Best score: 0.1377: : 776iter [01:13, 11.28iter/s]Best score: 0.1377: : 777iter [01:13, 11.31iter/s]Best score: 0.1377: : 777iter [01:13, 11.31iter/s]Best score: 0.1377: : 778iter [01:13, 11.31iter/s]Best score: 0.1377: : 779iter [01:13, 11.44iter/s]Best score: 0.1377: : 779iter [01:13, 11.44iter/s]Best score: 0.1377: : 780iter [01:14, 11.44iter/s]Best score: 0.1377: : 781iter [01:14, 11.33iter/s]Best score: 0.1377: : 781iter [01:14, 11.33iter/s]Best score: 0.1377: : 782iter [01:14, 11.33iter/s]Best score: 0.1377: : 783iter [01:14, 11.43iter/s]Best score: 0.1377: : 783iter [01:14, 11.43iter/s]Best score: 0.1377: : 784iter [01:14, 11.43iter/s]Best score: 0.1377: : 785iter [01:14, 11.50iter/s]Best score: 0.1377: : 785iter [01:14, 11.50iter/s]Best score: 0.1377: : 786iter [01:14, 11.50iter/s]Best score: 0.1377: : 787iter [01:14, 11.57iter/s]Best score: 0.1377: : 787iter [01:14, 11.57iter/s]Best score: 0.1377: : 788iter [01:14, 11.57iter/s]Best score: 0.1377: : 789iter [01:14, 11.61iter/s]Best score: 0.1377: : 789iter [01:14, 11.61iter/s]Best score: 0.1377: : 790iter [01:14, 11.61iter/s]Best score: 0.1377: : 791iter [01:14, 11.44iter/s]Best score: 0.1377: : 791iter [01:14, 11.44iter/s]Best score: 0.1377: : 792iter [01:15, 11.44iter/s]Best score: 0.1377: : 793iter [01:15, 11.54iter/s]Best score: 0.1377: : 793iter [01:15, 11.54iter/s]Best score: 0.1377: : 794iter [01:15, 11.54iter/s]Best score: 0.1377: : 795iter [01:15, 11.60iter/s]Best score: 0.1377: : 795iter [01:15, 11.60iter/s]Best score: 0.1377: : 796iter [01:15, 11.60iter/s]Best score: 0.1377: : 797iter [01:15, 11.63iter/s]Best score: 0.1377: : 797iter [01:15, 11.63iter/s]Best score: 0.1377: : 798iter [01:15, 11.63iter/s]Best score: 0.1377: : 799iter [01:15, 11.66iter/s]
[ITER 800] Best: 0.1376
[PARAMS] Current best parameters:
  fx: 549.0789
  fy: 549.0663
  px: 875.3556
  py: 957.6853
  k1: -0.01923473
  k2: 0.00242485
  k3: 0.00055503
  k4: -0.00063735
  p1: -0.00874113
  p2: -0.00732029
  p3: 0.01022629
  p4: 0.00338269
  s1: 0.0000
  s2: -0.0053
  s3: -0.0159
  s4: -0.0020
  tilt_x: -0.0143
  tilt_y: -0.0267
  scale: 2.9931
  rotation: 0.3940
Best score: 0.1376: : 799iter [01:15, 11.66iter/s]Best score: 0.1376: : 800iter [01:16, 11.66iter/s]Best score: 0.1376: : 801iter [01:16,  7.50iter/s]Best score: 0.1376: : 801iter [01:16,  7.50iter/s]Best score: 0.1376: : 802iter [01:16,  7.50iter/s]Best score: 0.1376: : 803iter [01:16,  8.41iter/s]Best score: 0.1376: : 803iter [01:16,  8.41iter/s]Best score: 0.1376: : 804iter [01:16,  8.41iter/s]Best score: 0.1376: : 805iter [01:16,  9.20iter/s]Best score: 0.1376: : 805iter [01:16,  9.20iter/s]Best score: 0.1376: : 806iter [01:16,  9.20iter/s]Best score: 0.1376: : 807iter [01:16,  9.83iter/s]Best score: 0.1376: : 807iter [01:16,  9.83iter/s]Best score: 0.1376: : 808iter [01:16,  9.83iter/s]Best score: 0.1376: : 809iter [01:16, 10.32iter/s]Best score: 0.1376: : 809iter [01:16, 10.32iter/s]Best score: 0.1376: : 810iter [01:16, 10.32iter/s]Best score: 0.1376: : 811iter [01:16, 10.52iter/s]Best score: 0.1376: : 811iter [01:17, 10.52iter/s]Best score: 0.1376: : 812iter [01:17, 10.52iter/s]Best score: 0.1376: : 813iter [01:17, 10.85iter/s]Best score: 0.1376: : 813iter [01:17, 10.85iter/s]Best score: 0.1376: : 814iter [01:17, 10.85iter/s]Best score: 0.1376: : 815iter [01:17, 11.09iter/s]Best score: 0.1376: : 815iter [01:17, 11.09iter/s]Best score: 0.1376: : 816iter [01:17, 11.09iter/s]Best score: 0.1376: : 817iter [01:17, 11.22iter/s]Best score: 0.1376: : 817iter [01:17, 11.22iter/s]Best score: 0.1376: : 818iter [01:17, 11.22iter/s]Best score: 0.1376: : 819iter [01:17, 11.34iter/s]Best score: 0.1374: : 819iter [01:17, 11.34iter/s]Best score: 0.1374: : 820iter [01:17, 11.34iter/s]Best score: 0.1374: : 821iter [01:17, 11.26iter/s]Best score: 0.1374: : 821iter [01:17, 11.26iter/s]Best score: 0.1374: : 822iter [01:17, 11.26iter/s]Best score: 0.1374: : 823iter [01:17, 11.39iter/s]Best score: 0.1374: : 823iter [01:18, 11.39iter/s]Best score: 0.1374: : 824iter [01:18, 11.39iter/s]Best score: 0.1374: : 825iter [01:18, 11.48iter/s]Best score: 0.1374: : 825iter [01:18, 11.48iter/s]Best score: 0.1374: : 826iter [01:18, 11.48iter/s]Best score: 0.1374: : 827iter [01:18, 11.50iter/s]Best score: 0.1374: : 827iter [01:18, 11.50iter/s]Best score: 0.1374: : 828iter [01:18, 11.50iter/s]Best score: 0.1374: : 829iter [01:18, 11.57iter/s]Best score: 0.1374: : 829iter [01:18, 11.57iter/s]Best score: 0.1374: : 830iter [01:18, 11.57iter/s]Best score: 0.1374: : 831iter [01:18, 11.42iter/s]Best score: 0.1374: : 831iter [01:18, 11.42iter/s]Best score: 0.1374: : 832iter [01:18, 11.42iter/s]Best score: 0.1374: : 833iter [01:18, 11.52iter/s]Best score: 0.1374: : 833iter [01:18, 11.52iter/s]Best score: 0.1374: : 834iter [01:19, 11.52iter/s]Best score: 0.1374: : 835iter [01:19, 11.49iter/s]Best score: 0.1374: : 835iter [01:19, 11.49iter/s]Best score: 0.1374: : 836iter [01:19, 11.49iter/s]Best score: 0.1374: : 837iter [01:19, 11.55iter/s]Best score: 0.1374: : 837iter [01:19, 11.55iter/s]Best score: 0.1374: : 838iter [01:19, 11.55iter/s]Best score: 0.1374: : 839iter [01:19, 11.60iter/s]Best score: 0.1374: : 839iter [01:19, 11.60iter/s]Best score: 0.1374: : 840iter [01:19, 11.60iter/s]Best score: 0.1374: : 841iter [01:19, 11.44iter/s]Best score: 0.1374: : 841iter [01:19, 11.44iter/s]Best score: 0.1374: : 842iter [01:19, 11.44iter/s]Best score: 0.1374: : 843iter [01:19, 11.53iter/s]Best score: 0.1374: : 843iter [01:19, 11.53iter/s]Best score: 0.1374: : 844iter [01:19, 11.53iter/s]Best score: 0.1374: : 845iter [01:19, 11.58iter/s]Best score: 0.1374: : 845iter [01:19, 11.58iter/s]Best score: 0.1374: : 846iter [01:20, 11.58iter/s]Best score: 0.1374: : 847iter [01:20, 11.63iter/s]Best score: 0.1374: : 847iter [01:20, 11.63iter/s]Best score: 0.1374: : 848iter [01:20, 11.63iter/s]Best score: 0.1374: : 849iter [01:20, 11.66iter/s]
[ITER 850] Best: 0.1374
[PARAMS] Current best parameters:
  fx: 546.7680
  fy: 546.7271
  px: 875.3000
  py: 957.7567
  k1: -0.01896321
  k2: 0.00620590
  k3: -0.00208002
  k4: -0.00006336
  p1: -0.00931429
  p2: -0.00783873
  p3: 0.01093711
  p4: 0.00216874
  s1: -0.0003
  s2: -0.0040
  s3: -0.0160
  s4: -0.0007
  tilt_x: -0.0125
  tilt_y: -0.0272
  scale: 2.9953
  rotation: 0.3918
Best score: 0.1374: : 849iter [01:20, 11.66iter/s]Best score: 0.1374: : 850iter [01:20, 11.66iter/s]Best score: 0.1374: : 851iter [01:20,  7.49iter/s]Best score: 0.1374: : 851iter [01:20,  7.49iter/s]Best score: 0.1374: : 852iter [01:20,  7.49iter/s]Best score: 0.1374: : 853iter [01:20,  8.40iter/s]Best score: 0.1374: : 853iter [01:20,  8.40iter/s]Best score: 0.1374: : 854iter [01:21,  8.40iter/s]Best score: 0.1374: : 855iter [01:21,  9.17iter/s]Best score: 0.1374: : 855iter [01:21,  9.17iter/s]Best score: 0.1374: : 856iter [01:21,  9.17iter/s]Best score: 0.1374: : 857iter [01:21,  9.81iter/s]Best score: 0.1374: : 857iter [01:21,  9.81iter/s]Best score: 0.1374: : 858iter [01:21,  9.81iter/s]Best score: 0.1374: : 859iter [01:21, 10.32iter/s]Best score: 0.1373: : 859iter [01:21, 10.32iter/s]Best score: 0.1373: : 860iter [01:21, 10.32iter/s]Best score: 0.1373: : 861iter [01:21, 10.54iter/s]Best score: 0.1373: : 861iter [01:21, 10.54iter/s]Best score: 0.1373: : 862iter [01:21, 10.54iter/s]Best score: 0.1373: : 863iter [01:21, 10.87iter/s]Best score: 0.1373: : 863iter [01:21, 10.87iter/s]Best score: 0.1373: : 864iter [01:21, 10.87iter/s]Best score: 0.1373: : 865iter [01:21, 11.09iter/s]Best score: 0.1373: : 865iter [01:21, 11.09iter/s]Best score: 0.1373: : 866iter [01:22, 11.09iter/s]Best score: 0.1373: : 867iter [01:22, 11.25iter/s]Best score: 0.1373: : 867iter [01:22, 11.25iter/s]Best score: 0.1373: : 868iter [01:22, 11.25iter/s]Best score: 0.1373: : 869iter [01:22, 11.37iter/s]Best score: 0.1373: : 869iter [01:22, 11.37iter/s]Best score: 0.1373: : 870iter [01:22, 11.37iter/s]Best score: 0.1373: : 871iter [01:22, 11.25iter/s]Best score: 0.1373: : 871iter [01:22, 11.25iter/s]Best score: 0.1373: : 872iter [01:22, 11.25iter/s]Best score: 0.1373: : 873iter [01:22, 11.33iter/s]Best score: 0.1373: : 873iter [01:22, 11.33iter/s]Best score: 0.1373: : 874iter [01:22, 11.33iter/s]Best score: 0.1373: : 875iter [01:22, 11.44iter/s]Best score: 0.1373: : 875iter [01:22, 11.44iter/s]Best score: 0.1373: : 876iter [01:22, 11.44iter/s]Best score: 0.1373: : 877iter [01:22, 11.52iter/s]Best score: 0.1373: : 877iter [01:23, 11.52iter/s]Best score: 0.1373: : 878iter [01:23, 11.52iter/s]Best score: 0.1373: : 879iter [01:23, 11.58iter/s]Best score: 0.1372: : 879iter [01:23, 11.58iter/s]Best score: 0.1372: : 880iter [01:23, 11.58iter/s]Best score: 0.1372: : 881iter [01:23, 11.42iter/s]Best score: 0.1372: : 881iter [01:23, 11.42iter/s]Best score: 0.1372: : 882iter [01:23, 11.42iter/s]Best score: 0.1372: : 883iter [01:23, 11.51iter/s]Best score: 0.1372: : 883iter [01:23, 11.51iter/s]Best score: 0.1372: : 884iter [01:23, 11.51iter/s]Best score: 0.1372: : 885iter [01:23, 11.58iter/s]Best score: 0.1372: : 885iter [01:23, 11.58iter/s]Best score: 0.1372: : 886iter [01:23, 11.58iter/s]Best score: 0.1372: : 887iter [01:23, 11.63iter/s]Best score: 0.1372: : 887iter [01:23, 11.63iter/s]Best score: 0.1372: : 888iter [01:23, 11.63iter/s]Best score: 0.1372: : 889iter [01:23, 11.66iter/s]Best score: 0.1371: : 889iter [01:24, 11.66iter/s]Best score: 0.1371: : 890iter [01:24, 11.66iter/s]Best score: 0.1371: : 891iter [01:24, 11.48iter/s]Best score: 0.1371: : 891iter [01:24, 11.48iter/s]Best score: 0.1371: : 892iter [01:24, 11.48iter/s]Best score: 0.1371: : 893iter [01:24, 11.53iter/s]Best score: 0.1371: : 893iter [01:24, 11.53iter/s]Best score: 0.1371: : 894iter [01:24, 11.53iter/s]Best score: 0.1371: : 895iter [01:24, 11.58iter/s]Best score: 0.1371: : 895iter [01:24, 11.58iter/s]Best score: 0.1371: : 896iter [01:24, 11.58iter/s]Best score: 0.1371: : 897iter [01:24, 11.59iter/s]Best score: 0.1371: : 897iter [01:24, 11.59iter/s]Best score: 0.1371: : 898iter [01:24, 11.59iter/s]Best score: 0.1371: : 899iter [01:24, 11.55iter/s]
[ITER 900] Best: 0.1371
[PARAMS] Current best parameters:
  fx: 544.2040
  fy: 544.1639
  px: 875.7251
  py: 957.9811
  k1: -0.01545721
  k2: 0.00484167
  k3: -0.00150425
  k4: -0.00019855
  p1: -0.00741807
  p2: -0.00801346
  p3: 0.00865439
  p4: 0.00030539
  s1: 0.0028
  s2: -0.0022
  s3: -0.0152
  s4: 0.0010
  tilt_x: -0.0152
  tilt_y: -0.0296
  scale: 2.9958
  rotation: 0.4004
Best score: 0.1371: : 899iter [01:24, 11.55iter/s]Best score: 0.1371: : 900iter [01:25, 11.55iter/s]Best score: 0.1371: : 901iter [01:25,  7.47iter/s]Best score: 0.1371: : 901iter [01:25,  7.47iter/s]Best score: 0.1371: : 902iter [01:25,  7.47iter/s]Best score: 0.1371: : 903iter [01:25,  8.37iter/s]Best score: 0.1371: : 903iter [01:25,  8.37iter/s]Best score: 0.1371: : 904iter [01:25,  8.37iter/s]Best score: 0.1371: : 905iter [01:25,  9.16iter/s]Best score: 0.1371: : 905iter [01:25,  9.16iter/s]Best score: 0.1371: : 906iter [01:25,  9.16iter/s]Best score: 0.1371: : 907iter [01:25,  9.80iter/s]Best score: 0.1371: : 907iter [01:25,  9.80iter/s]Best score: 0.1371: : 908iter [01:26,  9.80iter/s]Best score: 0.1371: : 909iter [01:26, 10.30iter/s]Best score: 0.1370: : 909iter [01:26, 10.30iter/s]Best score: 0.1370: : 910iter [01:26, 10.30iter/s]Best score: 0.1370: : 911iter [01:26, 10.51iter/s]Best score: 0.1370: : 911iter [01:26, 10.51iter/s]Best score: 0.1370: : 912iter [01:26, 10.51iter/s]Best score: 0.1370: : 913iter [01:26, 10.85iter/s]Best score: 0.1370: : 913iter [01:26, 10.85iter/s]Best score: 0.1370: : 914iter [01:26, 10.85iter/s]Best score: 0.1370: : 915iter [01:26, 11.00iter/s]Best score: 0.1370: : 915iter [01:26, 11.00iter/s]Best score: 0.1370: : 916iter [01:26, 11.00iter/s]Best score: 0.1370: : 917iter [01:26, 11.20iter/s]Best score: 0.1370: : 917iter [01:26, 11.20iter/s]Best score: 0.1370: : 918iter [01:26, 11.20iter/s]Best score: 0.1370: : 919iter [01:26, 11.34iter/s]Best score: 0.1370: : 919iter [01:26, 11.34iter/s]Best score: 0.1370: : 920iter [01:27, 11.34iter/s]Best score: 0.1370: : 921iter [01:27, 11.20iter/s]Best score: 0.1370: : 921iter [01:27, 11.20iter/s]Best score: 0.1370: : 922iter [01:27, 11.20iter/s]Best score: 0.1370: : 923iter [01:27, 11.34iter/s]Best score: 0.1370: : 923iter [01:27, 11.34iter/s]Best score: 0.1370: : 924iter [01:27, 11.34iter/s]Best score: 0.1370: : 925iter [01:27, 11.46iter/s]Best score: 0.1370: : 925iter [01:27, 11.46iter/s]Best score: 0.1370: : 926iter [01:27, 11.46iter/s]Best score: 0.1370: : 927iter [01:27, 11.54iter/s]Best score: 0.1370: : 927iter [01:27, 11.54iter/s]Best score: 0.1370: : 928iter [01:27, 11.54iter/s]Best score: 0.1370: : 929iter [01:27, 11.59iter/s]Best score: 0.1370: : 929iter [01:27, 11.59iter/s]Best score: 0.1370: : 930iter [01:27, 11.59iter/s]Best score: 0.1370: : 931iter [01:27, 11.43iter/s]Best score: 0.1370: : 931iter [01:28, 11.43iter/s]Best score: 0.1370: : 932iter [01:28, 11.43iter/s]Best score: 0.1370: : 933iter [01:28, 11.50iter/s]Best score: 0.1370: : 933iter [01:28, 11.50iter/s]Best score: 0.1370: : 934iter [01:28, 11.50iter/s]Best score: 0.1370: : 935iter [01:28, 11.53iter/s]Best score: 0.1370: : 935iter [01:28, 11.53iter/s]Best score: 0.1370: : 936iter [01:28, 11.53iter/s]Best score: 0.1370: : 937iter [01:28, 11.57iter/s]Best score: 0.1370: : 937iter [01:28, 11.57iter/s]Best score: 0.1370: : 938iter [01:28, 11.57iter/s]Best score: 0.1370: : 939iter [01:28, 11.60iter/s]Best score: 0.1370: : 939iter [01:28, 11.60iter/s]Best score: 0.1370: : 940iter [01:28, 11.60iter/s]Best score: 0.1370: : 941iter [01:28, 11.43iter/s]Best score: 0.1370: : 941iter [01:28, 11.43iter/s]Best score: 0.1370: : 942iter [01:28, 11.43iter/s]Best score: 0.1370: : 943iter [01:28, 11.52iter/s]Best score: 0.1370: : 943iter [01:29, 11.52iter/s]Best score: 0.1370: : 944iter [01:29, 11.52iter/s]Best score: 0.1370: : 945iter [01:29, 11.58iter/s]Best score: 0.1370: : 945iter [01:29, 11.58iter/s]Best score: 0.1370: : 946iter [01:29, 11.58iter/s]Best score: 0.1370: : 947iter [01:29, 11.61iter/s]Best score: 0.1370: : 947iter [01:29, 11.61iter/s]Best score: 0.1370: : 948iter [01:29, 11.61iter/s]Best score: 0.1370: : 949iter [01:29, 11.65iter/s]
[ITER 950] Best: 0.1369
[PARAMS] Current best parameters:
  fx: 542.9188
  fy: 542.8834
  px: 875.8391
  py: 957.9469
  k1: -0.01347287
  k2: 0.00394938
  k3: -0.00120410
  k4: -0.00024322
  p1: -0.00635821
  p2: -0.00858687
  p3: 0.00548921
  p4: 0.00018644
  s1: 0.0068
  s2: -0.0023
  s3: -0.0132
  s4: 0.0011
  tilt_x: -0.0173
  tilt_y: -0.0313
  scale: 2.9959
  rotation: 0.4048
Best score: 0.1369: : 949iter [01:29, 11.65iter/s]Best score: 0.1369: : 950iter [01:29, 11.65iter/s]Best score: 0.1369: : 951iter [01:29,  7.50iter/s]Best score: 0.1369: : 951iter [01:30,  7.50iter/s]Best score: 0.1369: : 952iter [01:30,  7.50iter/s]Best score: 0.1369: : 953iter [01:30,  8.40iter/s]Best score: 0.1369: : 953iter [01:30,  8.40iter/s]Best score: 0.1369: : 954iter [01:30,  8.40iter/s]Best score: 0.1369: : 955iter [01:30,  9.17iter/s]Best score: 0.1369: : 955iter [01:30,  9.17iter/s]Best score: 0.1369: : 956iter [01:30,  9.17iter/s]Best score: 0.1369: : 957iter [01:30,  9.76iter/s]Best score: 0.1369: : 957iter [01:30,  9.76iter/s]Best score: 0.1369: : 958iter [01:30,  9.76iter/s]Best score: 0.1369: : 959iter [01:30, 10.28iter/s]Best score: 0.1367: : 959iter [01:30, 10.28iter/s]Best score: 0.1367: : 960iter [01:30, 10.28iter/s]Best score: 0.1367: : 961iter [01:30, 10.50iter/s]Best score: 0.1367: : 961iter [01:30, 10.50iter/s]Best score: 0.1367: : 962iter [01:31, 10.50iter/s]Best score: 0.1367: : 963iter [01:31, 10.86iter/s]Best score: 0.1367: : 963iter [01:31, 10.86iter/s]Best score: 0.1367: : 964iter [01:31, 10.86iter/s]Best score: 0.1367: : 965iter [01:31, 11.10iter/s]Best score: 0.1367: : 965iter [01:31, 11.10iter/s]Best score: 0.1367: : 966iter [01:31, 11.10iter/s]Best score: 0.1367: : 967iter [01:31, 11.29iter/s]Best score: 0.1367: : 967iter [01:31, 11.29iter/s]Best score: 0.1367: : 968iter [01:31, 11.29iter/s]Best score: 0.1367: : 969iter [01:31, 11.43iter/s]Best score: 0.1365: : 969iter [01:31, 11.43iter/s]Best score: 0.1365: : 970iter [01:31, 11.43iter/s]Best score: 0.1365: : 971iter [01:31, 11.33iter/s]Best score: 0.1365: : 971iter [01:31, 11.33iter/s]Best score: 0.1365: : 972iter [01:31, 11.33iter/s]Best score: 0.1365: : 973iter [01:31, 11.44iter/s]Best score: 0.1365: : 973iter [01:31, 11.44iter/s]Best score: 0.1365: : 974iter [01:32, 11.44iter/s]Best score: 0.1365: : 975iter [01:32, 11.53iter/s]Best score: 0.1365: : 975iter [01:32, 11.53iter/s]Best score: 0.1365: : 976iter [01:32, 11.53iter/s]Best score: 0.1365: : 977iter [01:32, 11.58iter/s]Best score: 0.1365: : 977iter [01:32, 11.58iter/s]Best score: 0.1365: : 978iter [01:32, 11.58iter/s]Best score: 0.1365: : 979iter [01:32, 11.53iter/s]Best score: 0.1365: : 979iter [01:32, 11.53iter/s]Best score: 0.1365: : 980iter [01:32, 11.53iter/s]Best score: 0.1365: : 981iter [01:32, 11.31iter/s]Best score: 0.1365: : 981iter [01:32, 11.31iter/s]Best score: 0.1365: : 982iter [01:32, 11.31iter/s]Best score: 0.1365: : 983iter [01:32, 11.43iter/s]Best score: 0.1365: : 983iter [01:32, 11.43iter/s]Best score: 0.1365: : 984iter [01:32, 11.43iter/s]Best score: 0.1365: : 985iter [01:32, 11.51iter/s]Best score: 0.1365: : 985iter [01:33, 11.51iter/s]Best score: 0.1365: : 986iter [01:33, 11.51iter/s]Best score: 0.1365: : 987iter [01:33, 11.57iter/s]Best score: 0.1365: : 987iter [01:33, 11.57iter/s]Best score: 0.1365: : 988iter [01:33, 11.57iter/s]Best score: 0.1365: : 989iter [01:33, 11.62iter/s]Best score: 0.1364: : 989iter [01:33, 11.62iter/s]Best score: 0.1364: : 990iter [01:33, 11.62iter/s]Best score: 0.1364: : 991iter [01:33, 11.44iter/s]Best score: 0.1364: : 991iter [01:33, 11.44iter/s]Best score: 0.1364: : 992iter [01:33, 11.44iter/s]Best score: 0.1364: : 993iter [01:33, 11.53iter/s]Best score: 0.1364: : 993iter [01:33, 11.53iter/s]Best score: 0.1364: : 994iter [01:33, 11.53iter/s]Best score: 0.1364: : 995iter [01:33, 11.59iter/s]Best score: 0.1364: : 995iter [01:33, 11.59iter/s]Best score: 0.1364: : 996iter [01:33, 11.59iter/s]Best score: 0.1364: : 997iter [01:33, 11.63iter/s]Best score: 0.1364: : 997iter [01:34, 11.63iter/s]Best score: 0.1364: : 998iter [01:34, 11.63iter/s]Best score: 0.1364: : 999iter [01:34, 11.65iter/s]
[ITER 1000] Best: 0.1364
[PARAMS] Current best parameters:
  fx: 542.1978
  fy: 542.2042
  px: 875.8903
  py: 958.1770
  k1: -0.01132961
  k2: 0.00193892
  k3: -0.00033771
  k4: -0.00035491
  p1: -0.00519975
  p2: -0.01020362
  p3: 0.00173815
  p4: 0.00244248
  s1: 0.0120
  s2: -0.0043
  s3: -0.0103
  s4: -0.0012
  tilt_x: -0.0185
  tilt_y: -0.0347
  scale: 2.9952
  rotation: 0.4098
Best score: 0.1364: : 999iter [01:34, 11.65iter/s]Best score: 0.1364: : 1000iter [01:34, 11.65iter/s]Best score: 0.1364: : 1001iter [01:34,  7.49iter/s]Best score: 0.1364: : 1001iter [01:34,  7.49iter/s]Best score: 0.1364: : 1002iter [01:34,  7.49iter/s]Best score: 0.1364: : 1003iter [01:34,  8.40iter/s]Best score: 0.1364: : 1003iter [01:34,  8.40iter/s]Best score: 0.1364: : 1004iter [01:34,  8.40iter/s]Best score: 0.1364: : 1005iter [01:34,  9.15iter/s]Best score: 0.1364: : 1005iter [01:35,  9.15iter/s]Best score: 0.1364: : 1006iter [01:35,  9.15iter/s]Best score: 0.1364: : 1007iter [01:35,  9.80iter/s]Best score: 0.1364: : 1007iter [01:35,  9.80iter/s]Best score: 0.1364: : 1008iter [01:35,  9.80iter/s]Best score: 0.1364: : 1009iter [01:35, 10.30iter/s]Best score: 0.1364: : 1009iter [01:35, 10.30iter/s]Best score: 0.1364: : 1010iter [01:35, 10.30iter/s]Best score: 0.1364: : 1011iter [01:35, 10.51iter/s]Best score: 0.1364: : 1011iter [01:35, 10.51iter/s]Best score: 0.1364: : 1012iter [01:35, 10.51iter/s]Best score: 0.1364: : 1013iter [01:35, 10.83iter/s]Best score: 0.1364: : 1013iter [01:35, 10.83iter/s]Best score: 0.1364: : 1014iter [01:35, 10.83iter/s]Best score: 0.1364: : 1015iter [01:35, 11.08iter/s]Best score: 0.1364: : 1015iter [01:35, 11.08iter/s]Best score: 0.1364: : 1016iter [01:35, 11.08iter/s]Best score: 0.1364: : 1017iter [01:35, 11.25iter/s]Best score: 0.1364: : 1017iter [01:36, 11.25iter/s]Best score: 0.1364: : 1018iter [01:36, 11.25iter/s]Best score: 0.1364: : 1019iter [01:36, 11.37iter/s]Best score: 0.1364: : 1019iter [01:36, 11.37iter/s]Best score: 0.1364: : 1020iter [01:36, 11.37iter/s]Best score: 0.1364: : 1021iter [01:36, 11.27iter/s]Best score: 0.1364: : 1021iter [01:36, 11.27iter/s]Best score: 0.1364: : 1022iter [01:36, 11.27iter/s]Best score: 0.1364: : 1023iter [01:36, 11.38iter/s]Best score: 0.1364: : 1023iter [01:36, 11.38iter/s]Best score: 0.1364: : 1024iter [01:36, 11.38iter/s]Best score: 0.1364: : 1025iter [01:36, 11.49iter/s]Best score: 0.1364: : 1025iter [01:36, 11.49iter/s]Best score: 0.1364: : 1026iter [01:36, 11.49iter/s]Best score: 0.1364: : 1027iter [01:36, 11.57iter/s]Best score: 0.1364: : 1027iter [01:36, 11.57iter/s]Best score: 0.1364: : 1028iter [01:37, 11.57iter/s]Best score: 0.1364: : 1029iter [01:37, 11.62iter/s]Best score: 0.1363: : 1029iter [01:37, 11.62iter/s]Best score: 0.1363: : 1030iter [01:37, 11.62iter/s]Best score: 0.1363: : 1031iter [01:37, 11.42iter/s]Best score: 0.1363: : 1031iter [01:37, 11.42iter/s]Best score: 0.1363: : 1032iter [01:37, 11.42iter/s]Best score: 0.1363: : 1033iter [01:37, 11.47iter/s]Best score: 0.1363: : 1033iter [01:37, 11.47iter/s]Best score: 0.1363: : 1034iter [01:37, 11.47iter/s]Best score: 0.1363: : 1035iter [01:37, 11.48iter/s]Best score: 0.1363: : 1035iter [01:37, 11.48iter/s]Best score: 0.1363: : 1036iter [01:37, 11.48iter/s]Best score: 0.1363: : 1037iter [01:37, 11.55iter/s]Best score: 0.1363: : 1037iter [01:37, 11.55iter/s]Best score: 0.1363: : 1038iter [01:37, 11.55iter/s]Best score: 0.1363: : 1039iter [01:37, 11.59iter/s]Best score: 0.1363: : 1039iter [01:37, 11.59iter/s]Best score: 0.1363: : 1040iter [01:38, 11.59iter/s]Best score: 0.1363: : 1041iter [01:38, 11.43iter/s]Best score: 0.1363: : 1041iter [01:38, 11.43iter/s]Best score: 0.1363: : 1042iter [01:38, 11.43iter/s]Best score: 0.1363: : 1043iter [01:38, 11.51iter/s]Best score: 0.1363: : 1043iter [01:38, 11.51iter/s]Best score: 0.1363: : 1044iter [01:38, 11.51iter/s]Best score: 0.1363: : 1045iter [01:38, 11.59iter/s]Best score: 0.1363: : 1045iter [01:38, 11.59iter/s]Best score: 0.1363: : 1046iter [01:38, 11.59iter/s]Best score: 0.1363: : 1047iter [01:38, 11.63iter/s]Best score: 0.1363: : 1047iter [01:38, 11.63iter/s]Best score: 0.1363: : 1048iter [01:38, 11.63iter/s]Best score: 0.1363: : 1049iter [01:38, 11.65iter/s]
[ITER 1050] Best: 0.1362
[PARAMS] Current best parameters:
  fx: 541.2454
  fy: 541.2647
  px: 875.8417
  py: 958.3181
  k1: -0.01153988
  k2: 0.00469259
  k3: -0.00257604
  k4: 0.00021694
  p1: -0.00514116
  p2: -0.01140179
  p3: 0.00023565
  p4: 0.00323286
  s1: 0.0144
  s2: -0.0049
  s3: -0.0088
  s4: -0.0019
  tilt_x: -0.0177
  tilt_y: -0.0370
  scale: 2.9960
  rotation: 0.4115
Best score: 0.1362: : 1049iter [01:38, 11.65iter/s]Best score: 0.1362: : 1050iter [01:39, 11.65iter/s]Best score: 0.1362: : 1051iter [01:39,  7.49iter/s]Best score: 0.1362: : 1051iter [01:39,  7.49iter/s]Best score: 0.1362: : 1052iter [01:39,  7.49iter/s]Best score: 0.1362: : 1053iter [01:39,  8.39iter/s]Best score: 0.1362: : 1053iter [01:39,  8.39iter/s]Best score: 0.1362: : 1054iter [01:39,  8.39iter/s]Best score: 0.1362: : 1055iter [01:39,  9.18iter/s]Best score: 0.1362: : 1055iter [01:39,  9.18iter/s]Best score: 0.1362: : 1056iter [01:39,  9.18iter/s]Best score: 0.1362: : 1057iter [01:39,  9.81iter/s]Best score: 0.1362: : 1057iter [01:39,  9.81iter/s]Best score: 0.1362: : 1058iter [01:39,  9.81iter/s]Best score: 0.1362: : 1059iter [01:39, 10.31iter/s]Best score: 0.1362: : 1059iter [01:40, 10.31iter/s]Best score: 0.1362: : 1060iter [01:40, 10.31iter/s]Best score: 0.1362: : 1061iter [01:40, 10.52iter/s]Best score: 0.1362: : 1061iter [01:40, 10.52iter/s]Best score: 0.1362: : 1062iter [01:40, 10.52iter/s]Best score: 0.1362: : 1063iter [01:40, 10.83iter/s]Best score: 0.1362: : 1063iter [01:40, 10.83iter/s]Best score: 0.1362: : 1064iter [01:40, 10.83iter/s]Best score: 0.1362: : 1065iter [01:40, 11.09iter/s]Best score: 0.1362: : 1065iter [01:40, 11.09iter/s]Best score: 0.1362: : 1066iter [01:40, 11.09iter/s]Best score: 0.1362: : 1067iter [01:40, 11.24iter/s]Best score: 0.1362: : 1067iter [01:40, 11.24iter/s]Best score: 0.1362: : 1068iter [01:40, 11.24iter/s]Best score: 0.1362: : 1069iter [01:40, 11.39iter/s]Best score: 0.1362: : 1069iter [01:40, 11.39iter/s]Best score: 0.1362: : 1070iter [01:40, 11.39iter/s]Best score: 0.1362: : 1071iter [01:40, 11.30iter/s]Best score: 0.1362: : 1071iter [01:41, 11.30iter/s]Best score: 0.1362: : 1072iter [01:41, 11.30iter/s]Best score: 0.1362: : 1073iter [01:41, 11.42iter/s]Best score: 0.1362: : 1073iter [01:41, 11.42iter/s]Best score: 0.1362: : 1074iter [01:41, 11.42iter/s]Best score: 0.1362: : 1075iter [01:41, 11.52iter/s]Best score: 0.1362: : 1075iter [01:41, 11.52iter/s]Best score: 0.1362: : 1076iter [01:41, 11.52iter/s]Best score: 0.1362: : 1077iter [01:41, 11.58iter/s]Best score: 0.1362: : 1077iter [01:41, 11.58iter/s]Best score: 0.1362: : 1078iter [01:41, 11.58iter/s]Best score: 0.1362: : 1079iter [01:41, 11.62iter/s]Best score: 0.1362: : 1079iter [01:41, 11.62iter/s]Best score: 0.1362: : 1080iter [01:41, 11.62iter/s]Best score: 0.1362: : 1081iter [01:41, 11.45iter/s]Best score: 0.1362: : 1081iter [01:41, 11.45iter/s]Best score: 0.1362: : 1082iter [01:42, 11.45iter/s]Best score: 0.1362: : 1083iter [01:42, 11.53iter/s]Best score: 0.1362: : 1083iter [01:42, 11.53iter/s]Best score: 0.1362: : 1084iter [01:42, 11.53iter/s]Best score: 0.1362: : 1085iter [01:42, 11.58iter/s]Best score: 0.1362: : 1085iter [01:42, 11.58iter/s]Best score: 0.1362: : 1086iter [01:42, 11.58iter/s]Best score: 0.1362: : 1087iter [01:42, 11.59iter/s]Best score: 0.1362: : 1087iter [01:42, 11.59iter/s]Best score: 0.1362: : 1088iter [01:42, 11.59iter/s]Best score: 0.1362: : 1089iter [01:42, 11.60iter/s]Best score: 0.1362: : 1089iter [01:42, 11.60iter/s]Best score: 0.1362: : 1090iter [01:42, 11.60iter/s]Best score: 0.1362: : 1091iter [01:42, 11.44iter/s]Best score: 0.1362: : 1091iter [01:42, 11.44iter/s]Best score: 0.1362: : 1092iter [01:42, 11.44iter/s]Best score: 0.1362: : 1093iter [01:42, 11.51iter/s]Best score: 0.1362: : 1093iter [01:42, 11.51iter/s]Best score: 0.1362: : 1094iter [01:43, 11.51iter/s]Best score: 0.1362: : 1095iter [01:43, 11.58iter/s]Best score: 0.1362: : 1095iter [01:43, 11.58iter/s]Best score: 0.1362: : 1096iter [01:43, 11.58iter/s]Best score: 0.1362: : 1097iter [01:43, 11.62iter/s]Best score: 0.1362: : 1097iter [01:43, 11.62iter/s]Best score: 0.1362: : 1098iter [01:43, 11.62iter/s]Best score: 0.1362: : 1099iter [01:43, 11.65iter/s]
[ITER 1100] Best: 0.1362
[PARAMS] Current best parameters:
  fx: 541.1743
  fy: 541.2037
  px: 875.8976
  py: 958.3313
  k1: -0.01120283
  k2: 0.00409536
  k3: -0.00215761
  k4: 0.00011624
  p1: -0.00541197
  p2: -0.01140131
  p3: 0.00140295
  p4: 0.00251459
  s1: 0.0133
  s2: -0.0041
  s3: -0.0096
  s4: -0.0013
  tilt_x: -0.0172
  tilt_y: -0.0372
  scale: 2.9962
  rotation: 0.4115
Best score: 0.1362: : 1099iter [01:43, 11.65iter/s]Best score: 0.1362: : 1100iter [01:43, 10.60iter/s]

[📈] Running L-BFGS-B polish after 1100 DE iterations...
  Polish improved score: 0.136164 -> 0.136092

[⭕] Ring refinement pass (3500mm diameter)...
  Points: 102,177 → 95,988 within 3500mm ring
  Ring polish did not improve score: 0.136092
  Success: True
  Tangential distortion: p1=-0.005417, p2=-0.011407, p3=0.001398, p4=0.002499
  ✓ Tangential correction is significant for corner improvement
[✅] Square reference optimization complete. Score: 0.1361
[✅] Parameters copied to: /working/STLC-083WF_W028(6)_2026-02-04/calibration/params.json
[📌] Selecting best parameters...
[✅] Saved final refined parameters.


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


[DEBUG] Parameters being applied to PTD conversion:
    fx: 541.174332690813
    fy: 541.2036928832557
    px: 875.8976025382478
    py: 958.3312715295921
    k1: -0.011286649571859063
    k2: 0.004161224540472867
    k3: -0.002090134851070103
    k4: 7.170775732697808e-05
    p1: -0.005416845133934382
    p2: -0.011407327723678059
    p3: 0.001397822545251012
    p4: 0.0024990307023158268
    scale: 2.9960365315383535
    rotation: 0.411450216059609
    mmpp: 3.417977027987935
    nmpp: 3417977.027987935

[🔄] Converting 1495 frames to PTD, creating debug images for 400 calibration frames...
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                                                                 [A📁 Rigs:  75%|███████▌  | 3/4 [00:09<00:02,  2.82s/rig]
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                                                                  [A📁 Rigs: 100%|██████████| 4/4 [00:15<00:00,  4.10s/rig]📁 Rigs: 100%|██████████| 4/4 [00:15<00:00,  3.78s/rig]
[✅] Saved PTDs: /working/STLC-083WF_W028(6)_2026-02-04/calibration/debug/4_undistorted/output/ptd
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                                                                [A📁 Rigs:  25%|██▌       | 1/4 [00:00<00:02,  1.08rig/s]
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                                                                [A📁 Rigs:  75%|███████▌  | 3/4 [00:02<00:00,  1.04rig/s]
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                                                                 [A📁 Rigs: 100%|██████████| 4/4 [00:03<00:00,  1.00s/rig]📁 Rigs: 100%|██████████| 4/4 [00:03<00:00,  1.01rig/s]
[✅] Saved PTDs: /working/STLC-083WF_W028(6)_2026-02-04/calibration/debug/4_undistorted/temp_ptd
[WARN] No .tfd files found for serial extraction
[WARN] Failed to extract serial number from .tfd file. Check that .tfd files exist and contain 'LASERbidh' or 'LASERbidg' pattern. Using 'unknown' as fallback.
📤 Writing LUT:   0%|          | 0/3240000 [00:00<?, ?px/s]📤 Writing LUT:   2%|▏         | 77157/3240000 [00:00<00:04, 771563.38px/s]📤 Writing LUT:   5%|▌         | 163920/3240000 [00:00<00:03, 828069.94px/s]📤 Writing LUT:   8%|▊         | 249332/3240000 [00:00<00:03, 839964.35px/s]📤 Writing LUT:  10%|█         | 335195/3240000 [00:00<00:03, 847329.65px/s]📤 Writing LUT:  13%|█▎        | 420534/3240000 [00:00<00:03, 849514.61px/s]📤 Writing LUT:  16%|█▌        | 505656/3240000 [00:00<00:03, 850094.03px/s]📤 Writing LUT:  18%|█▊        | 591310/3240000 [00:00<00:03, 852199.63px/s]📤 Writing LUT:  21%|██        | 678777/3240000 [00:00<00:02, 859350.76px/s]📤 Writing LUT:  24%|██▎       | 764713/3240000 [00:00<00:02, 859207.89px/s]📤 Writing LUT:  26%|██▋       | 850634/3240000 [00:01<00:02, 854751.89px/s]📤 Writing LUT:  29%|██▉       | 936115/3240000 [00:01<00:02, 850922.69px/s]📤 Writing LUT:  32%|███▏      | 1022308/3240000 [00:01<00:02, 854251.16px/s]📤 Writing LUT:  34%|███▍      | 1107899/3240000 [00:01<00:02, 854748.24px/s]📤 Writing LUT:  37%|███▋      | 1194817/3240000 [00:01<00:02, 859091.74px/s]📤 Writing LUT:  40%|███▉      | 1280990/3240000 [00:01<00:02, 859884.45px/s]📤 Writing LUT:  42%|████▏     | 1366982/3240000 [00:01<00:02, 858806.61px/s]📤 Writing LUT:  45%|████▍     | 1452866/3240000 [00:01<00:02, 858752.97px/s]📤 Writing LUT:  48%|████▊     | 1541866/3240000 [00:01<00:01, 868128.80px/s]📤 Writing LUT:  50%|█████     | 1630015/3240000 [00:01<00:01, 872136.97px/s]📤 Writing LUT:  53%|█████▎    | 1717900/3240000 [00:02<00:01, 874149.54px/s]📤 Writing LUT:  56%|█████▌    | 1807473/3240000 [00:02<00:01, 880623.92px/s]📤 Writing LUT:  59%|█████▊    | 1897515/3240000 [00:02<00:01, 886562.13px/s]📤 Writing LUT:  61%|██████▏   | 1986173/3240000 [00:02<00:01, 883844.84px/s]📤 Writing LUT:  64%|██████▍   | 2074978/3240000 [00:02<00:01, 885087.54px/s]📤 Writing LUT:  67%|██████▋   | 2163489/3240000 [00:02<00:01, 880910.16px/s]📤 Writing LUT:  69%|██████▉   | 2251586/3240000 [00:02<00:01, 876120.99px/s]📤 Writing LUT:  72%|███████▏  | 2339206/3240000 [00:02<00:01, 875374.36px/s]📤 Writing LUT:  75%|███████▍  | 2428735/3240000 [00:02<00:00, 881314.94px/s]📤 Writing LUT:  78%|███████▊  | 2516874/3240000 [00:02<00:00, 877762.04px/s]📤 Writing LUT:  80%|████████  | 2606665/3240000 [00:03<00:00, 883772.11px/s]📤 Writing LUT:  83%|████████▎ | 2696949/3240000 [00:03<00:00, 889467.45px/s]📤 Writing LUT:  86%|████████▌ | 2785904/3240000 [00:03<00:00, 888959.12px/s]📤 Writing LUT:  89%|████████▊ | 2874806/3240000 [00:03<00:00, 886282.10px/s]📤 Writing LUT:  91%|█████████▏| 2963440/3240000 [00:03<00:00, 884484.50px/s]📤 Writing LUT:  94%|█████████▍| 3051893/3240000 [00:03<00:00, 881821.09px/s]📤 Writing LUT:  97%|█████████▋| 3140079/3240000 [00:03<00:00, 881580.73px/s]📤 Writing LUT: 100%|█████████▉| 3228815/3240000 [00:03<00:00, 883307.13px/s]📤 Writing LUT: 100%|██████████| 3240000/3240000 [00:03<00:00, 869652.12px/s]
[✅] LUT written to: /working/STLC-083WF_W028(6)_2026-02-04/calibration/debug/4_undistorted/output/LUT.lut
[WARN] Folder name 'STLC-083WF_W028(6)_2026-02-04' does not match expected pattern MDC042_W007_5_28_2025. Using simple naming convention.
[✅] LUT copied to: /working/STLC-083WF_W028(6)_2026-02-04/calibration/STLC-083WF_W028(6)_2026-02-04_unknown.lut

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

[ℹ️] Detected device type: SMD_P3D (rigs: [1000, 1500, 2000]mm)
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                                                                [A[✅] 1500: /working/STLC-083WF_W028(6)_2026-02-04/calibration/debug/5_heatmap/1500_heatmap.png
[✅] 1500 (fitted): /working/STLC-083WF_W028(6)_2026-02-04/calibration/debug/5_heatmap/1500_heatmap_fitted.png
📁 Rigs (heatmap):  25%|██▌       | 1/4 [00:05<00:16,  5.34s/rig]
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                                                                 [A[✅] 2000L: /working/STLC-083WF_W028(6)_2026-02-04/calibration/debug/5_heatmap/2000L_heatmap.png
[✅] 2000L (fitted): /working/STLC-083WF_W028(6)_2026-02-04/calibration/debug/5_heatmap/2000L_heatmap_fitted.png
📁 Rigs (heatmap):  50%|█████     | 2/4 [00:11<00:11,  5.71s/rig]
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                                                                [A[✅] 1000: /working/STLC-083WF_W028(6)_2026-02-04/calibration/debug/5_heatmap/1000_heatmap.png
[✅] 1000 (fitted): /working/STLC-083WF_W028(6)_2026-02-04/calibration/debug/5_heatmap/1000_heatmap_fitted.png
📁 Rigs (heatmap):  75%|███████▌  | 3/4 [00:14<00:04,  4.42s/rig]
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                                                                 [A[✅] 2000R: /working/STLC-083WF_W028(6)_2026-02-04/calibration/debug/5_heatmap/2000R_heatmap.png
[✅] 2000R (fitted): /working/STLC-083WF_W028(6)_2026-02-04/calibration/debug/5_heatmap/2000R_heatmap_fitted.png
📁 Rigs (heatmap): 100%|██████████| 4/4 [00:22<00:00,  5.91s/rig]📁 Rigs (heatmap): 100%|██████████| 4/4 [00:22<00:00,  5.60s/rig]
[✅] all_rigs_average.png
[✅] all_rigs_best.png
[✅] all_rigs_average_fitted.png
[✅] all_rigs_best_fitted.png
[✅] Heatmaps saved to: /working/STLC-083WF_W028(6)_2026-02-04/calibration/debug/5_heatmap
[🏁] Finished processing STLC-083WF_W028(6)_2026-02-04


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