2026-05-17T22:15:31 - INFO: Slick 0.0.8a11

🟢 Starting Calibration Pipeline

=== Processing MDC036_W018(6)_2025-10-31 ===
2026-05-17T22:15:31 - INFO: Camera ID: 14302216
2026-05-17T22:15:31 - INFO: Wand ID: 
2026-05-17T22:15:31 - INFO: Recorded At: 2025-10-31T11:53:43Z

-------------------------------------------------------------------
                        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 1214 stationary frames, 239 remain

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→ 2000L Phase 2: corners:  93%|█████████▎| 222/239 [00:01<00:00, 178.81it/s][A
                                                                            [A[PASS2] Summary: 0 frames fixed, 1 untrusted, 239 total

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                                                                            [A
[TIMING] 2000L — 239 frames
  Phase 1  radial detect   (parallel)  :   3.80s  (15.9 ms/frame)
  Phase 2a corner detect   (parallel)  :   1.82s  (7.6 ms/frame)
  Phase 2b corner fix      (sequential):   0.05s
  Phase 3  finalize        (sequential):   4.37s  (18.3 ms/frame)
    decode + undistort                 :   2.24s  (9.4 ms/frame)
    corner apply + refinement          :   0.97s  (4.1 ms/frame)
    segment                            :   0.95s  (4.0 ms/frame)
    smooth                             :   0.13s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  10.04s

Processing Rigs:  25%|██▌       | 1/4 [00:16<00:49, 16.36s/it][INFO] Filtered 1383 stationary frames, 202 remain

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→ 2000R Phase 2: corners: 100%|██████████| 202/202 [00:01<00:00, 186.92it/s][A
                                                                            [A[PASS2] Frame 0000614: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000615: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000616: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000617: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000619: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000620: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000621: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000622: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000623: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000624: fixed corners {2} (was_fixed=False, trusted=False)
[PASS2] Frame 0000625: fixed corners {2} (was_fixed=True, trusted=False)
[PASS2] Frame 0000626: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000823: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000824: fixed corners {3} (was_fixed=False, trusted=False)
[PASS2] Frame 0000825: fixed corners {3} (was_fixed=True, trusted=False)
[PASS2] Frame 0000826: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0001135: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0001138: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000616: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Frame 0000621: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000625: fixed corners {2} (was_fixed=True, trusted=True)
[PASS2] Frame 0000825: fixed corners {3} (was_fixed=True, trusted=True)
[PASS2] Summary: 10 frames fixed, 8 untrusted, 202 total

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                                                                            [A
[TIMING] 2000R — 202 frames
  Phase 1  radial detect   (parallel)  :   3.22s  (15.9 ms/frame)
  Phase 2a corner detect   (parallel)  :   1.70s  (8.4 ms/frame)
  Phase 2b corner fix      (sequential):   0.44s
  Phase 3  finalize        (sequential):   3.64s  (18.0 ms/frame)
    decode + undistort                 :   1.83s  (9.0 ms/frame)
    corner apply + refinement          :   0.83s  (4.1 ms/frame)
    segment                            :   0.81s  (4.0 ms/frame)
    smooth                             :   0.11s  (0.6 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :   9.01s

Processing Rigs:  50%|█████     | 2/4 [00:30<00:29, 14.83s/it][INFO] Filtered 1434 stationary frames, 252 remain

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                                                                           [A[PASS2] Summary: 0 frames fixed, 1 untrusted, 252 total

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                                                                           [A
[TIMING] 1500 — 252 frames
  Phase 1  radial detect   (parallel)  :   3.85s  (15.3 ms/frame)
  Phase 2a corner detect   (parallel)  :   2.13s  (8.5 ms/frame)
  Phase 2b corner fix      (sequential):   0.05s
  Phase 3  finalize        (sequential):   4.47s  (17.8 ms/frame)
    decode + undistort                 :   2.34s  (9.3 ms/frame)
    corner apply + refinement          :   0.92s  (3.7 ms/frame)
    segment                            :   0.99s  (3.9 ms/frame)
    smooth                             :   0.14s  (0.5 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :  10.51s

Processing Rigs:  75%|███████▌  | 3/4 [00:45<00:15, 15.20s/it][INFO] Filtered 1318 stationary frames, 173 remain

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                                                                           [A[PASS2] Summary: 0 frames fixed, 1 untrusted, 173 total

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                                                                           [A
[TIMING] 1000 — 173 frames
  Phase 1  radial detect   (parallel)  :   2.98s  (17.2 ms/frame)
  Phase 2a corner detect   (parallel)  :   1.63s  (9.4 ms/frame)
  Phase 2b corner fix      (sequential):   0.04s
  Phase 3  finalize        (sequential):   2.93s  (16.9 ms/frame)
    decode + undistort                 :   1.54s  (8.9 ms/frame)
    corner apply + refinement          :   0.57s  (3.3 ms/frame)
    segment                            :   0.67s  (3.9 ms/frame)
    smooth                             :   0.09s  (0.5 ms/frame)
    distort back                       :   0.00s  (0.0 ms/frame)
  Total                                :   7.57s

Processing Rigs: 100%|██████████| 4/4 [00:57<00:00, 13.95s/it]Processing Rigs: 100%|██████████| 4/4 [00:57<00:00, 14.45s/it]
[💾] Saved RigFrameDataset to /working/MDC036_W018(6)_2025-10-31/calibration/debug/1_digitized_full/rig_frames_full.json
[✅] Saved full dataset: 866 frames from 4 rigs to /working/MDC036_W018(6)_2025-10-31/calibration/debug/1_digitized_full/rig_frames_full.json
[💾] Saved RigFrameDataset to /working/MDC036_W018(6)_2025-10-31/calibration/debug/1_digitized_full/rig_frames_full.json
[📋] Creating calibration subset (100 frames/rig) with visualizations...
[📋] 2000L: 100 frames selected from 239
[📋] 2000R: 100 frames selected from 202
[📋] 1500: 100 frames selected from 252
[📋] 1000: 100 frames selected from 173
[💾] Saved RigFrameDataset to /working/MDC036_W018(6)_2025-10-31/calibration/debug/1_digitized/rig_frames.json
[INFO] Reloading dataset from disk to ensure clean state for multiprocessing...
[📂] Loaded RigFrameDataset from /working/MDC036_W018(6)_2025-10-31/calibration/debug/1_digitized/rig_frames.json

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

-> Calculating the casing center ...
[INFO] Using 80 total sampled bright frames
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from bright frames:  42%|████▎     | 34/80 [01:46<02:32,  3.32s/it]Computing max image from bright frames:  44%|████▍     | 35/80 [01:49<02:25,  3.24s/it]Computing max image from bright frames:  45%|████▌     | 36/80 [01:52<02:20,  3.20s/it]Computing max image from bright frames:  46%|████▋     | 37/80 [01:55<02:15,  3.15s/it]Computing max image from bright frames:  48%|████▊     | 38/80 [01:58<02:11,  3.13s/it]Computing max image from bright frames:  49%|████▉     | 39/80 [02:01<02:07,  3.12s/it]Computing max image from bright frames:  50%|█████     | 40/80 [02:03<01:45,  2.63s/it]Computing max image from bright frames:  51%|█████▏    | 41/80 [02:06<01:48,  2.77s/it]Computing max image from bright frames:  52%|█████▎    | 42/80 [02:09<01:48,  2.86s/it]Computing max image from bright frames:  54%|█████▍    | 43/80 [02:12<01:47,  2.92s/it]Computing max image from bright frames:  55%|█████▌    | 44/80 [02:15<01:46,  2.96s/it]Computing max image from bright frames:  56%|█████▋    | 45/80 [02:18<01:44,  2.99s/it]Computing max image from bright frames:  57%|█████▊    | 46/80 [02:21<01:42,  3.01s/it]Computing max image from bright frames:  59%|█████▉    | 47/80 [02:24<01:39,  3.03s/it]Computing max image from bright frames:  60%|██████    | 48/80 [02:27<01:37,  3.04s/it]Computing max image from bright frames:  61%|██████▏   | 49/80 [02:30<01:34,  3.05s/it]Computing max image from bright frames:  62%|██████▎   | 50/80 [02:33<01:32,  3.08s/it]Computing max image from bright frames:  64%|██████▍   | 51/80 [02:36<01:29,  3.10s/it]Computing max image from bright frames:  65%|██████▌   | 52/80 [02:40<01:27,  3.11s/it]Computing max image from bright frames:  66%|██████▋   | 53/80 [02:43<01:24,  3.14s/it]Computing max image from bright frames:  68%|██████▊   | 54/80 [02:46<01:22,  3.16s/it]Computing max image from bright frames:  69%|██████▉   | 55/80 [02:49<01:18,  3.16s/it]Computing max image from bright frames:  70%|███████   | 56/80 [02:52<01:15,  3.13s/it]Computing max image from bright frames:  71%|███████▏  | 57/80 [02:55<01:11,  3.11s/it]Computing max image from bright frames:  72%|███████▎  | 58/80 [02:58<01:08,  3.09s/it]Computing max image from bright frames:  74%|███████▍  | 59/80 [03:01<01:04,  3.08s/it]Computing max image from bright frames:  75%|███████▌  | 60/80 [03:04<01:01,  3.05s/it]Computing max image from bright frames:  76%|███████▋  | 61/80 [03:07<00:58,  3.07s/it]Computing max image from bright frames:  78%|███████▊  | 62/80 [03:11<00:55,  3.07s/it]Computing max image from bright frames:  79%|███████▉  | 63/80 [03:14<00:52,  3.07s/it]Computing max image from bright frames:  80%|████████  | 64/80 [03:17<00:49,  3.07s/it]Computing max image from bright frames:  81%|████████▏ | 65/80 [03:20<00:46,  3.07s/it]Computing max image from bright frames:  82%|████████▎ | 66/80 [03:23<00:43,  3.12s/it]Computing max image from bright frames:  84%|████████▍ | 67/80 [03:26<00:40,  3.10s/it]Computing max image from bright frames:  85%|████████▌ | 68/80 [03:29<00:37,  3.09s/it]Computing max image from bright frames:  86%|████████▋ | 69/80 [03:32<00:33,  3.09s/it]Computing max image from bright frames:  88%|████████▊ | 70/80 [03:35<00:30,  3.09s/it]Computing max image from bright frames:  89%|████████▉ | 71/80 [03:38<00:27,  3.11s/it]Computing max image from bright frames:  90%|█████████ | 72/80 [03:42<00:25,  3.13s/it]Computing max image from bright frames:  91%|█████████▏| 73/80 [03:45<00:21,  3.14s/it]Computing max image from bright frames:  92%|█████████▎| 74/80 [03:48<00:18,  3.11s/it]Computing max image from bright frames:  94%|█████████▍| 75/80 [03:51<00:15,  3.10s/it]Computing max image from bright frames:  95%|█████████▌| 76/80 [03:54<00:12,  3.09s/it]Computing max image from bright frames:  96%|█████████▋| 77/80 [03:57<00:09,  3.08s/it]Computing max image from bright frames:  98%|█████████▊| 78/80 [04:00<00:06,  3.07s/it]Computing max image from bright frames:  99%|█████████▉| 79/80 [04:03<00:03,  3.07s/it]Computing max image from bright frames: 100%|██████████| 80/80 [04:06<00:00,  3.07s/it]                                                                                       [✅] Casing detection complete: cx=991.0, cy=757.0

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

  0%|          | 0/100 [00:00<?, ?it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   0%|          | 0/100 [00:00<?, ?it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   1%|          | 1/100 [00:00<00:27,  3.58it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   1%|          | 1/100 [00:00<00:27,  3.58it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 300.0} (0.000):   2%|▏         | 2/100 [00:00<00:27,  3.58it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 321.212} (0.000):   3%|▎         | 3/100 [00:00<00:27,  3.58it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 328.283} (0.000):   4%|▍         | 4/100 [00:00<00:26,  3.58it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 328.283} (0.000):   5%|▌         | 5/100 [00:00<00:06, 15.22it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 342.424} (0.000):   5%|▌         | 5/100 [00:00<00:06, 15.22it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 349.495} (0.000):   6%|▌         | 6/100 [00:00<00:06, 15.22it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 349.495} (0.000):   7%|▋         | 7/100 [00:00<00:06, 15.22it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.000 | Best: {'fx': 349.495} (0.000):   8%|▊         | 8/100 [00:00<00:04, 18.85it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.001 | Best: {'fx': 363.636} (0.001):   8%|▊         | 8/100 [00:00<00:04, 18.85it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.001 | Best: {'fx': 363.636} (0.001):   9%|▉         | 9/100 [00:00<00:04, 18.85it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.002 | Best: {'fx': 370.707} (0.002):  10%|█         | 10/100 [00:00<00:04, 18.85it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.003 | Best: {'fx': 377.778} (0.003):  11%|█         | 11/100 [00:00<00:04, 18.85it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.003 | Best: {'fx': 377.778} (0.003):  12%|█▏        | 12/100 [00:00<00:04, 17.68it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.004 | Best: {'fx': 384.848} (0.004):  12%|█▏        | 12/100 [00:00<00:04, 17.68it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.004 | Best: {'fx': 391.919} (0.004):  13%|█▎        | 13/100 [00:00<00:04, 17.68it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.004 | Best: {'fx': 398.99} (0.004):  14%|█▍        | 14/100 [00:00<00:04, 17.68it/s] Brute | Start: {'fx': 500.0} (0.042) | Current: 0.006 | Best: {'fx': 427.273} (0.006):  15%|█▌        | 15/100 [00:00<00:04, 17.68it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.005 | Best: {'fx': 427.273} (0.006):  16%|█▌        | 16/100 [00:00<00:04, 17.68it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.005 | Best: {'fx': 427.273} (0.006):  17%|█▋        | 17/100 [00:00<00:03, 24.20it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.005 | Best: {'fx': 427.273} (0.006):  17%|█▋        | 17/100 [00:00<00:03, 24.20it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.008 | Best: {'fx': 441.414} (0.008):  18%|█▊        | 18/100 [00:00<00:03, 24.20it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.007 | Best: {'fx': 441.414} (0.008):  19%|█▉        | 19/100 [00:00<00:03, 24.20it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.010 | Best: {'fx': 448.485} (0.010):  20%|██        | 20/100 [00:00<00:03, 24.20it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.010 | Best: {'fx': 448.485} (0.010):  21%|██        | 21/100 [00:00<00:02, 27.95it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.006 | Best: {'fx': 448.485} (0.010):  21%|██        | 21/100 [00:00<00:02, 27.95it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.013 | Best: {'fx': 455.556} (0.013):  22%|██▏       | 22/100 [00:00<00:02, 27.95it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.017 | Best: {'fx': 469.697} (0.017):  23%|██▎       | 23/100 [00:01<00:02, 27.95it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.015 | Best: {'fx': 469.697} (0.017):  24%|██▍       | 24/100 [00:01<00:02, 27.95it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.015 | Best: {'fx': 469.697} (0.017):  25%|██▌       | 25/100 [00:01<00:02, 29.05it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 476.768} (0.020):  25%|██▌       | 25/100 [00:01<00:02, 29.05it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.030 | Best: {'fx': 490.909} (0.030):  26%|██▌       | 26/100 [00:01<00:02, 29.05it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.048 | Best: {'fx': 505.051} (0.048):  27%|██▋       | 27/100 [00:01<00:02, 29.05it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.024 | Best: {'fx': 505.051} (0.048):  28%|██▊       | 28/100 [00:01<00:02, 29.05it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.024 | Best: {'fx': 505.051} (0.048):  29%|██▉       | 29/100 [00:01<00:02, 25.96it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.058 | Best: {'fx': 512.121} (0.058):  29%|██▉       | 29/100 [00:01<00:02, 25.96it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.040 | Best: {'fx': 512.121} (0.058):  30%|███       | 30/100 [00:01<00:02, 25.96it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.079 | Best: {'fx': 519.192} (0.079):  31%|███       | 31/100 [00:01<00:02, 25.96it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.079 | Best: {'fx': 519.192} (0.079):  32%|███▏      | 32/100 [00:01<00:03, 21.86it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.105 | Best: {'fx': 526.263} (0.105):  32%|███▏      | 32/100 [00:01<00:03, 21.86it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.112 | Best: {'fx': 533.333} (0.112):  33%|███▎      | 33/100 [00:01<00:03, 21.86it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.087 | Best: {'fx': 533.333} (0.112):  34%|███▍      | 34/100 [00:01<00:03, 21.86it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.087 | Best: {'fx': 533.333} (0.112):  35%|███▌      | 35/100 [00:01<00:02, 21.94it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.062 | Best: {'fx': 533.333} (0.112):  35%|███▌      | 35/100 [00:01<00:02, 21.94it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.073 | Best: {'fx': 533.333} (0.112):  36%|███▌      | 36/100 [00:01<00:02, 21.94it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.045 | Best: {'fx': 533.333} (0.112):  37%|███▋      | 37/100 [00:01<00:02, 21.94it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.045 | Best: {'fx': 533.333} (0.112):  38%|███▊      | 38/100 [00:01<00:02, 23.30it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.049 | Best: {'fx': 533.333} (0.112):  38%|███▊      | 38/100 [00:01<00:02, 23.30it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.054 | Best: {'fx': 533.333} (0.112):  39%|███▉      | 39/100 [00:01<00:02, 23.30it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.042 | Best: {'fx': 533.333} (0.112):  40%|████      | 40/100 [00:01<00:02, 23.30it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.036 | Best: {'fx': 533.333} (0.112):  41%|████      | 41/100 [00:01<00:02, 23.30it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.036 | Best: {'fx': 533.333} (0.112):  42%|████▏     | 42/100 [00:01<00:02, 25.56it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.039 | Best: {'fx': 533.333} (0.112):  42%|████▏     | 42/100 [00:01<00:02, 25.56it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.034 | Best: {'fx': 533.333} (0.112):  43%|████▎     | 43/100 [00:01<00:02, 25.56it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.030 | Best: {'fx': 533.333} (0.112):  44%|████▍     | 44/100 [00:01<00:02, 25.56it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.030 | Best: {'fx': 533.333} (0.112):  45%|████▌     | 45/100 [00:01<00:02, 24.93it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.033 | Best: {'fx': 533.333} (0.112):  45%|████▌     | 45/100 [00:02<00:02, 24.93it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.031 | Best: {'fx': 533.333} (0.112):  46%|████▌     | 46/100 [00:02<00:02, 24.93it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.032 | Best: {'fx': 533.333} (0.112):  47%|████▋     | 47/100 [00:02<00:02, 24.93it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.032 | Best: {'fx': 533.333} (0.112):  48%|████▊     | 48/100 [00:02<00:01, 26.03it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.029 | Best: {'fx': 533.333} (0.112):  48%|████▊     | 48/100 [00:02<00:01, 26.03it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.028 | Best: {'fx': 533.333} (0.112):  49%|████▉     | 49/100 [00:02<00:01, 26.03it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.027 | Best: {'fx': 533.333} (0.112):  50%|█████     | 50/100 [00:02<00:01, 26.03it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.027 | Best: {'fx': 533.333} (0.112):  51%|█████     | 51/100 [00:02<00:01, 26.74it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.028 | Best: {'fx': 533.333} (0.112):  51%|█████     | 51/100 [00:02<00:01, 26.74it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.026 | Best: {'fx': 533.333} (0.112):  52%|█████▏    | 52/100 [00:02<00:01, 26.74it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.027 | Best: {'fx': 533.333} (0.112):  53%|█████▎    | 53/100 [00:02<00:01, 26.74it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.023 | Best: {'fx': 533.333} (0.112):  54%|█████▍    | 54/100 [00:02<00:01, 26.74it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.026 | Best: {'fx': 533.333} (0.112):  55%|█████▌    | 55/100 [00:02<00:01, 26.74it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.023 | Best: {'fx': 533.333} (0.112):  56%|█████▌    | 56/100 [00:02<00:01, 26.74it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.023 | Best: {'fx': 533.333} (0.112):  57%|█████▋    | 57/100 [00:02<00:01, 30.53it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.022 | Best: {'fx': 533.333} (0.112):  57%|█████▋    | 57/100 [00:02<00:01, 30.53it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.022 | Best: {'fx': 533.333} (0.112):  58%|█████▊    | 58/100 [00:02<00:01, 30.53it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.022 | Best: {'fx': 533.333} (0.112):  59%|█████▉    | 59/100 [00:02<00:01, 30.53it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.025 | Best: {'fx': 533.333} (0.112):  60%|██████    | 60/100 [00:02<00:01, 30.53it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.025 | Best: {'fx': 533.333} (0.112):  61%|██████    | 61/100 [00:02<00:01, 32.04it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.025 | Best: {'fx': 533.333} (0.112):  61%|██████    | 61/100 [00:02<00:01, 32.04it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.024 | Best: {'fx': 533.333} (0.112):  62%|██████▏   | 62/100 [00:02<00:01, 32.04it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.024 | Best: {'fx': 533.333} (0.112):  63%|██████▎   | 63/100 [00:02<00:01, 32.04it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.022 | Best: {'fx': 533.333} (0.112):  64%|██████▍   | 64/100 [00:02<00:01, 32.04it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.022 | Best: {'fx': 533.333} (0.112):  65%|██████▌   | 65/100 [00:02<00:01, 34.02it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.021 | Best: {'fx': 533.333} (0.112):  65%|██████▌   | 65/100 [00:02<00:01, 34.02it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.023 | Best: {'fx': 533.333} (0.112):  66%|██████▌   | 66/100 [00:02<00:00, 34.02it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.024 | Best: {'fx': 533.333} (0.112):  67%|██████▋   | 67/100 [00:02<00:00, 34.02it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.023 | Best: {'fx': 533.333} (0.112):  68%|██████▊   | 68/100 [00:02<00:00, 34.02it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.021 | Best: {'fx': 533.333} (0.112):  69%|██████▉   | 69/100 [00:02<00:00, 34.02it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.021 | Best: {'fx': 533.333} (0.112):  70%|███████   | 70/100 [00:02<00:00, 34.02it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.021 | Best: {'fx': 533.333} (0.112):  71%|███████   | 71/100 [00:02<00:00, 38.70it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.021 | Best: {'fx': 533.333} (0.112):  71%|███████   | 71/100 [00:02<00:00, 38.70it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.021 | Best: {'fx': 533.333} (0.112):  72%|███████▏  | 72/100 [00:02<00:00, 38.70it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.021 | Best: {'fx': 533.333} (0.112):  73%|███████▎  | 73/100 [00:02<00:00, 38.70it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.021 | Best: {'fx': 533.333} (0.112):  74%|███████▍  | 74/100 [00:02<00:00, 38.70it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.112):  75%|███████▌  | 75/100 [00:02<00:00, 38.70it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.112):  76%|███████▌  | 76/100 [00:02<00:00, 38.70it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.112):  77%|███████▋  | 77/100 [00:02<00:00, 42.64it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.112):  77%|███████▋  | 77/100 [00:02<00:00, 42.64it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.112):  78%|███████▊  | 78/100 [00:02<00:00, 42.64it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.112):  79%|███████▉  | 79/100 [00:02<00:00, 42.64it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.112):  80%|████████  | 80/100 [00:02<00:00, 42.64it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.112):  81%|████████  | 81/100 [00:02<00:00, 42.64it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.112):  82%|████████▏ | 82/100 [00:02<00:00, 41.41it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.112):  82%|████████▏ | 82/100 [00:02<00:00, 41.41it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.020 | Best: {'fx': 533.333} (0.112):  83%|████████▎ | 83/100 [00:02<00:00, 41.41it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.112):  84%|████████▍ | 84/100 [00:02<00:00, 41.41it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.112):  85%|████████▌ | 85/100 [00:03<00:00, 41.41it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.112):  86%|████████▌ | 86/100 [00:03<00:00, 41.41it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.112):  87%|████████▋ | 87/100 [00:03<00:00, 34.16it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.112):  87%|████████▋ | 87/100 [00:03<00:00, 34.16it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.112):  88%|████████▊ | 88/100 [00:03<00:00, 34.16it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.112):  89%|████████▉ | 89/100 [00:03<00:00, 34.16it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.112):  90%|█████████ | 90/100 [00:03<00:00, 34.16it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.112):  91%|█████████ | 91/100 [00:03<00:00, 34.16it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.112):  92%|█████████▏| 92/100 [00:03<00:00, 37.14it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.112):  92%|█████████▏| 92/100 [00:03<00:00, 37.14it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.018 | Best: {'fx': 533.333} (0.112):  93%|█████████▎| 93/100 [00:03<00:00, 37.14it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.112):  94%|█████████▍| 94/100 [00:03<00:00, 37.14it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.112):  95%|█████████▌| 95/100 [00:03<00:00, 37.14it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.018 | Best: {'fx': 533.333} (0.112):  96%|█████████▌| 96/100 [00:03<00:00, 37.14it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.112):  97%|█████████▋| 97/100 [00:03<00:00, 37.14it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.112):  98%|█████████▊| 98/100 [00:03<00:00, 37.14it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.112):  99%|█████████▉| 99/100 [00:03<00:00, 37.24it/s]Brute | Start: {'fx': 500.0} (0.042) | Current: 0.019 | Best: {'fx': 533.333} (0.112):  99%|█████████▉| 99/100 [00:03<00:00, 37.24it/s]                                                                                                                                         0%|          | 0/50 [00:00<?, ?it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.052 | Best: {'fx': 508.333} (0.052):   0%|          | 0/50 [00:00<?, ?it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.052 | Best: {'fx': 508.333} (0.052):   2%|▏         | 1/50 [00:00<00:24,  2.03it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.054 | Best: {'fx': 509.354} (0.054):   2%|▏         | 1/50 [00:00<00:24,  2.03it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.056 | Best: {'fx': 510.374} (0.056):   4%|▍         | 2/50 [00:00<00:23,  2.03it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.057 | Best: {'fx': 511.395} (0.057):   6%|▌         | 3/50 [00:00<00:23,  2.03it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.057 | Best: {'fx': 511.395} (0.057):   8%|▊         | 4/50 [00:00<00:05,  7.88it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.059 | Best: {'fx': 512.415} (0.059):   8%|▊         | 4/50 [00:00<00:05,  7.88it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.061 | Best: {'fx': 513.435} (0.061):  10%|█         | 5/50 [00:00<00:05,  7.88it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.070 | Best: {'fx': 516.497} (0.070):  12%|█▏        | 6/50 [00:00<00:05,  7.88it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.070 | Best: {'fx': 516.497} (0.070):  14%|█▍        | 7/50 [00:00<00:03, 11.32it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.067 | Best: {'fx': 516.497} (0.070):  14%|█▍        | 7/50 [00:00<00:03, 11.32it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.064 | Best: {'fx': 516.497} (0.070):  16%|█▌        | 8/50 [00:00<00:03, 11.32it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.080 | Best: {'fx': 519.558} (0.080):  18%|█▊        | 9/50 [00:00<00:03, 11.32it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.074 | Best: {'fx': 519.558} (0.080):  20%|██        | 10/50 [00:00<00:03, 11.32it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.074 | Best: {'fx': 519.558} (0.080):  22%|██▏       | 11/50 [00:00<00:02, 16.99it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.076 | Best: {'fx': 519.558} (0.080):  22%|██▏       | 11/50 [00:00<00:02, 16.99it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.083 | Best: {'fx': 520.578} (0.083):  24%|██▍       | 12/50 [00:00<00:02, 16.99it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.089 | Best: {'fx': 521.599} (0.089):  26%|██▌       | 13/50 [00:00<00:02, 16.99it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.093 | Best: {'fx': 522.619} (0.093):  28%|██▊       | 14/50 [00:01<00:02, 16.99it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.093 | Best: {'fx': 522.619} (0.093):  30%|███       | 15/50 [00:01<00:01, 19.54it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.101 | Best: {'fx': 524.66} (0.101):  30%|███       | 15/50 [00:01<00:01, 19.54it/s] Brute | Start: {'fx': 533.333} (0.112) | Current: 0.097 | Best: {'fx': 524.66} (0.101):  32%|███▏      | 16/50 [00:01<00:01, 19.54it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.103 | Best: {'fx': 525.68} (0.103):  34%|███▍      | 17/50 [00:01<00:01, 19.54it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.106 | Best: {'fx': 526.701} (0.106):  36%|███▌      | 18/50 [00:01<00:01, 19.54it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.106 | Best: {'fx': 526.701} (0.106):  38%|███▊      | 19/50 [00:01<00:01, 21.37it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.108 | Best: {'fx': 527.721} (0.108):  38%|███▊      | 19/50 [00:01<00:01, 21.37it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.108 | Best: {'fx': 527.721} (0.108):  40%|████      | 20/50 [00:01<00:01, 21.37it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.113 | Best: {'fx': 530.782} (0.113):  42%|████▏     | 21/50 [00:01<00:01, 21.37it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.113 | Best: {'fx': 530.782} (0.113):  44%|████▍     | 22/50 [00:01<00:01, 22.33it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.111 | Best: {'fx': 530.782} (0.113):  44%|████▍     | 22/50 [00:01<00:01, 22.33it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.114 | Best: {'fx': 531.803} (0.114):  46%|████▌     | 23/50 [00:01<00:01, 22.33it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.113 | Best: {'fx': 531.803} (0.114):  48%|████▊     | 24/50 [00:01<00:01, 22.33it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.113 | Best: {'fx': 531.803} (0.114):  50%|█████     | 25/50 [00:01<00:01, 21.73it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.112 | Best: {'fx': 531.803} (0.114):  50%|█████     | 25/50 [00:01<00:01, 21.73it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.088 | Best: {'fx': 531.803} (0.114):  52%|█████▏    | 26/50 [00:01<00:01, 21.73it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.086 | Best: {'fx': 531.803} (0.114):  54%|█████▍    | 27/50 [00:01<00:01, 21.73it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.086 | Best: {'fx': 531.803} (0.114):  56%|█████▌    | 28/50 [00:01<00:01, 20.51it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.096 | Best: {'fx': 531.803} (0.114):  56%|█████▌    | 28/50 [00:01<00:01, 20.51it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.108 | Best: {'fx': 531.803} (0.114):  58%|█████▊    | 29/50 [00:01<00:01, 20.51it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.079 | Best: {'fx': 531.803} (0.114):  60%|██████    | 30/50 [00:01<00:00, 20.51it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.084 | Best: {'fx': 531.803} (0.114):  62%|██████▏   | 31/50 [00:01<00:00, 20.51it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.105 | Best: {'fx': 531.803} (0.114):  64%|██████▍   | 32/50 [00:01<00:00, 20.51it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.081 | Best: {'fx': 531.803} (0.114):  66%|██████▌   | 33/50 [00:01<00:00, 20.51it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.073 | Best: {'fx': 531.803} (0.114):  68%|██████▊   | 34/50 [00:01<00:00, 20.51it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.077 | Best: {'fx': 531.803} (0.114):  70%|███████   | 35/50 [00:01<00:00, 20.51it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.075 | Best: {'fx': 531.803} (0.114):  72%|███████▏  | 36/50 [00:01<00:00, 20.51it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.072 | Best: {'fx': 531.803} (0.114):  74%|███████▍  | 37/50 [00:01<00:00, 20.51it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.072 | Best: {'fx': 531.803} (0.114):  76%|███████▌  | 38/50 [00:01<00:00, 38.06it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.101 | Best: {'fx': 531.803} (0.114):  76%|███████▌  | 38/50 [00:01<00:00, 38.06it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.068 | Best: {'fx': 531.803} (0.114):  78%|███████▊  | 39/50 [00:01<00:00, 38.06it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.069 | Best: {'fx': 531.803} (0.114):  80%|████████  | 40/50 [00:01<00:00, 38.06it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.093 | Best: {'fx': 531.803} (0.114):  82%|████████▏ | 41/50 [00:01<00:00, 38.06it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.067 | Best: {'fx': 531.803} (0.114):  84%|████████▍ | 42/50 [00:01<00:00, 38.06it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.067 | Best: {'fx': 531.803} (0.114):  86%|████████▌ | 43/50 [00:01<00:00, 40.06it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.065 | Best: {'fx': 531.803} (0.114):  86%|████████▌ | 43/50 [00:01<00:00, 40.06it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.062 | Best: {'fx': 531.803} (0.114):  88%|████████▊ | 44/50 [00:01<00:00, 40.06it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.063 | Best: {'fx': 531.803} (0.114):  90%|█████████ | 45/50 [00:01<00:00, 40.06it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.058 | Best: {'fx': 531.803} (0.114):  92%|█████████▏| 46/50 [00:01<00:00, 40.06it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.057 | Best: {'fx': 531.803} (0.114):  94%|█████████▍| 47/50 [00:01<00:00, 40.06it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.061 | Best: {'fx': 531.803} (0.114):  96%|█████████▌| 48/50 [00:01<00:00, 40.06it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.059 | Best: {'fx': 531.803} (0.114):  98%|█████████▊| 49/50 [00:01<00:00, 40.06it/s]Brute | Start: {'fx': 533.333} (0.112) | Current: 0.059 | Best: {'fx': 531.803} (0.114): 100%|██████████| 50/50 [00:01<00:00, 44.94it/s]                                                                                                                                        
[DEBUG] Parameters after Step 5 (before square optimization):
    fx: 531.8027210884354
    px: 991.0
    py: 757.0
    k1: 0.0
    k2: 0.0
    k3: 0.0
    k4: 0.0
    p1: 0.0
    p2: 0.0
    p3: 0.0
    p4: 0.0
    scale: 3.0
    rotation: 0.0


[🔲] Square Reference Optimization
    Including tangential distortion parameters (p1, p2, p3, p4) in joint optimization
  Selecting up to 20 frames per rig (excluded 1 incomplete frames): 79 frames will be used for optimization
  Rigs: 2000L(2000mm):20/20, 2000R(2000mm):20/20, 1500(1500mm):19/20, 1000(1000mm):20/20
  Total: 79/80 frames used for optimization
Initial score: 7.5584: 0iter [00:00, ?iter/s][DEBUG] objective(x0) = 7.5584, picklable_objective(x0) = 7.5271
Best score: 7.5271: : 0iter [00:02, ?iter/s] Best score: 7.5271: : 1iter [00:02,  2.00s/iter]Best score: 7.5271: : 1iter [00:02,  2.00s/iter]Best score: 7.5271: : 2iter [00:02,  2.00s/iter]Best score: 7.5271: : 3iter [00:02,  1.72iter/s]Best score: 7.5271: : 3iter [00:02,  1.72iter/s]Best score: 7.5271: : 4iter [00:02,  1.72iter/s]Best score: 7.5271: : 5iter [00:02,  3.05iter/s]Best score: 7.5271: : 5iter [00:02,  3.05iter/s]Best score: 7.5271: : 6iter [00:02,  3.05iter/s]Best score: 7.5271: : 7iter [00:02,  4.44iter/s]Best score: 7.5271: : 7iter [00:02,  4.44iter/s]Best score: 7.5271: : 8iter [00:02,  4.44iter/s]Best score: 7.5271: : 9iter [00:02,  5.78iter/s]Best score: 7.5271: : 9iter [00:02,  5.78iter/s]Best score: 7.5271: : 10iter [00:02,  5.78iter/s]Best score: 7.5271: : 11iter [00:02,  6.93iter/s]Best score: 7.5271: : 11iter [00:02,  6.93iter/s]Best score: 7.5271: : 12iter [00:03,  6.93iter/s]Best score: 7.5271: : 13iter [00:03,  7.98iter/s]Best score: 7.5271: : 13iter [00:03,  7.98iter/s]Best score: 7.5271: : 14iter [00:03,  7.98iter/s]Best score: 7.5271: : 15iter [00:03,  8.87iter/s]Best score: 7.5271: : 15iter [00:03,  8.87iter/s]Best score: 7.5271: : 16iter [00:03,  8.87iter/s]Best score: 7.5271: : 17iter [00:03,  9.59iter/s]Best score: 7.5271: : 17iter [00:03,  9.59iter/s]Best score: 7.5271: : 18iter [00:03,  9.59iter/s]Best score: 7.5271: : 19iter [00:03, 10.18iter/s]Best score: 7.5271: : 19iter [00:03, 10.18iter/s]Best score: 7.5271: : 20iter [00:03, 10.18iter/s]Best score: 7.5271: : 21iter [00:03, 10.47iter/s]Best score: 7.5271: : 21iter [00:03, 10.47iter/s]Best score: 7.5271: : 22iter [00:03, 10.47iter/s]Best score: 7.5271: : 23iter [00:03, 10.76iter/s]Best score: 7.5271: : 23iter [00:04, 10.76iter/s]Best score: 7.5271: : 24iter [00:04, 10.76iter/s]Best score: 7.5271: : 25iter [00:04, 10.98iter/s]Best score: 7.5271: : 25iter [00:04, 10.98iter/s]Best score: 7.5271: : 26iter [00:04, 10.98iter/s]Best score: 7.5271: : 27iter [00:04, 11.19iter/s]Best score: 7.5271: : 27iter [00:04, 11.19iter/s]Best score: 7.5271: : 28iter [00:04, 11.19iter/s]Best score: 7.5271: : 29iter [00:04, 11.32iter/s]Best score: 7.5271: : 29iter [00:04, 11.32iter/s]Best score: 7.5271: : 30iter [00:04, 11.32iter/s]Best score: 7.5271: : 31iter [00:04, 11.24iter/s]Best score: 7.5271: : 31iter [00:04, 11.24iter/s]Best score: 7.5271: : 32iter [00:04, 11.24iter/s]Best score: 7.5271: : 33iter [00:04, 11.38iter/s]Best score: 7.5271: : 33iter [00:04, 11.38iter/s]Best score: 7.5271: : 34iter [00:04, 11.38iter/s]Best score: 7.5271: : 35iter [00:04, 11.49iter/s]Best score: 7.5271: : 35iter [00:05, 11.49iter/s]Best score: 7.5271: : 36iter [00:05, 11.49iter/s]Best score: 7.5271: : 37iter [00:05, 11.54iter/s]Best score: 7.5271: : 37iter [00:05, 11.54iter/s]Best score: 7.5271: : 38iter [00:05, 11.54iter/s]Best score: 7.5271: : 39iter [00:05, 11.58iter/s]Best score: 7.5271: : 39iter [00:05, 11.58iter/s]Best score: 7.5271: : 40iter [00:05, 11.58iter/s]Best score: 7.5271: : 41iter [00:05, 11.50iter/s]Best score: 7.5271: : 41iter [00:05, 11.50iter/s]Best score: 7.5271: : 42iter [00:05, 11.50iter/s]Best score: 7.5271: : 43iter [00:05, 11.60iter/s]Best score: 7.5271: : 43iter [00:05, 11.60iter/s]Best score: 7.5271: : 44iter [00:05, 11.60iter/s]Best score: 7.5271: : 45iter [00:05, 11.71iter/s]Best score: 7.5271: : 45iter [00:05, 11.71iter/s]Best score: 7.5271: : 46iter [00:05, 11.71iter/s]Best score: 7.5271: : 47iter [00:05, 11.78iter/s]Best score: 7.5271: : 47iter [00:06, 11.78iter/s]Best score: 7.5271: : 48iter [00:06, 11.78iter/s]Best score: 7.5271: : 49iter [00:06, 11.81iter/s]
[ITER 50] Best: 7.5271
[PARAMS] Current best parameters:
  fx: 531.8027
  fy: 531.8027
  px: 991.0000
  py: 757.0000
  k1: 0.00000000
  k2: -0.00000000
  k3: 0.00000000
  k4: 0.00000000
  p1: 0.00000000
  p2: 0.00000000
  p3: 0.00000000
  p4: 0.00000000
  s1: 0.0000
  s2: 0.0000
  s3: 0.0000
  s4: 0.0000
  tilt_x: 0.0000
  tilt_y: 0.0000
  scale: 3.0000
  rotation: 0.0000
Best score: 7.5271: : 49iter [00:06, 11.81iter/s]Best score: 7.5271: : 50iter [00:06, 11.81iter/s]Best score: 7.5271: : 51iter [00:06, 11.73iter/s]Best score: 7.5271: : 51iter [00:06, 11.73iter/s]Best score: 7.5271: : 52iter [00:06, 11.73iter/s]Best score: 7.5271: : 53iter [00:06, 11.76iter/s]Best score: 7.5271: : 53iter [00:06, 11.76iter/s]Best score: 7.5271: : 54iter [00:06, 11.76iter/s]Best score: 7.5271: : 55iter [00:06, 11.77iter/s]Best score: 7.5271: : 55iter [00:06, 11.77iter/s]Best score: 7.5271: : 56iter [00:06, 11.77iter/s]Best score: 7.5271: : 57iter [00:06, 11.86iter/s]Best score: 7.5271: : 57iter [00:06, 11.86iter/s]Best score: 7.5271: : 58iter [00:06, 11.86iter/s]Best score: 7.5271: : 59iter [00:06, 11.85iter/s]Best score: 7.5271: : 59iter [00:07, 11.85iter/s]Best score: 7.5271: : 60iter [00:07, 11.85iter/s]Best score: 7.5271: : 61iter [00:07, 11.62iter/s]Best score: 7.5271: : 61iter [00:07, 11.62iter/s]Best score: 7.5271: : 62iter [00:07, 11.62iter/s]Best score: 7.5271: : 63iter [00:07, 11.67iter/s]Best score: 7.5271: : 63iter [00:07, 11.67iter/s]Best score: 7.5271: : 64iter [00:07, 11.67iter/s]Best score: 7.5271: : 65iter [00:07, 11.72iter/s]Best score: 7.5271: : 65iter [00:07, 11.72iter/s]Best score: 7.5271: : 66iter [00:07, 11.72iter/s]Best score: 7.5271: : 67iter [00:07, 11.79iter/s]Best score: 7.5271: : 67iter [00:07, 11.79iter/s]Best score: 7.5271: : 68iter [00:07, 11.79iter/s]Best score: 7.5271: : 69iter [00:07, 11.82iter/s]Best score: 7.5271: : 69iter [00:07, 11.82iter/s]Best score: 7.5271: : 70iter [00:08, 11.82iter/s]Best score: 7.5271: : 71iter [00:08, 11.70iter/s]Best score: 7.5271: : 71iter [00:08, 11.70iter/s]Best score: 7.5271: : 72iter [00:08, 11.70iter/s]Best score: 7.5271: : 73iter [00:08, 11.75iter/s]Best score: 7.5271: : 73iter [00:08, 11.75iter/s]Best score: 7.5271: : 74iter [00:08, 11.75iter/s]Best score: 7.5271: : 75iter [00:08, 11.80iter/s]Best score: 7.5271: : 75iter [00:08, 11.80iter/s]Best score: 7.5271: : 76iter [00:08, 11.80iter/s]Best score: 7.5271: : 77iter [00:08, 11.87iter/s]Best score: 7.5271: : 77iter [00:08, 11.87iter/s]Best score: 7.5271: : 78iter [00:08, 11.87iter/s]Best score: 7.5271: : 79iter [00:08, 11.93iter/s]Best score: 7.5271: : 79iter [00:08, 11.93iter/s]Best score: 7.5271: : 80iter [00:08, 11.93iter/s]Best score: 7.5271: : 81iter [00:08, 11.81iter/s]Best score: 7.5271: : 81iter [00:08, 11.81iter/s]Best score: 7.5271: : 82iter [00:09, 11.81iter/s]Best score: 7.5271: : 83iter [00:09, 11.89iter/s]Best score: 7.5271: : 83iter [00:09, 11.89iter/s]Best score: 7.5271: : 84iter [00:09, 11.89iter/s]Best score: 7.5271: : 85iter [00:09, 11.88iter/s]Best score: 7.5271: : 85iter [00:09, 11.88iter/s]Best score: 7.5271: : 86iter [00:09, 11.88iter/s]Best score: 7.5271: : 87iter [00:09, 11.90iter/s]Best score: 7.5271: : 87iter [00:09, 11.90iter/s]Best score: 7.5271: : 88iter [00:09, 11.90iter/s]Best score: 7.5271: : 89iter [00:09, 11.92iter/s]Best score: 6.4542: : 89iter [00:09, 11.92iter/s]Best score: 6.4542: : 90iter [00:09, 11.92iter/s]Best score: 6.4542: : 91iter [00:09, 11.68iter/s]Best score: 6.4542: : 91iter [00:09, 11.68iter/s]Best score: 6.4542: : 92iter [00:09, 11.68iter/s]Best score: 6.4542: : 93iter [00:09, 11.74iter/s]Best score: 6.4542: : 93iter [00:09, 11.74iter/s]Best score: 6.4542: : 94iter [00:10, 11.74iter/s]Best score: 6.4542: : 95iter [00:10, 11.77iter/s]Best score: 6.4542: : 95iter [00:10, 11.77iter/s]Best score: 6.4542: : 96iter [00:10, 11.77iter/s]Best score: 6.4542: : 97iter [00:10, 11.85iter/s]Best score: 6.4542: : 97iter [00:10, 11.85iter/s]Best score: 6.4542: : 98iter [00:10, 11.85iter/s]Best score: 6.4542: : 99iter [00:10, 11.84iter/s]
[ITER 100] Best: 3.7448
[PARAMS] Current best parameters:
  fx: 551.3117
  fy: 549.2025
  px: 996.0331
  py: 765.9423
  k1: -0.00483679
  k2: -0.01965450
  k3: 0.00608361
  k4: 0.00084159
  p1: 0.00340576
  p2: 0.01363824
  p3: -0.01901772
  p4: 0.00456068
  s1: -0.0023
  s2: 0.0072
  s3: 0.0012
  s4: 0.0165
  tilt_x: 0.0238
  tilt_y: -0.0141
  scale: 2.9895
  rotation: 0.6441
Best score: 3.7448: : 99iter [00:10, 11.84iter/s]Best score: 3.7448: : 100iter [00:10, 11.84iter/s]Best score: 3.7448: : 101iter [00:10, 10.14iter/s]Best score: 3.7448: : 101iter [00:10, 10.14iter/s]Best score: 3.7448: : 102iter [00:10, 10.14iter/s]Best score: 3.7448: : 103iter [00:10, 10.56iter/s]Best score: 3.7448: : 103iter [00:10, 10.56iter/s]Best score: 3.7448: : 104iter [00:10, 10.56iter/s]Best score: 3.7448: : 105iter [00:10, 10.89iter/s]Best score: 3.7448: : 105iter [00:11, 10.89iter/s]Best score: 3.7448: : 106iter [00:11, 10.89iter/s]Best score: 3.7448: : 107iter [00:11, 11.09iter/s]Best score: 3.7448: : 107iter [00:11, 11.09iter/s]Best score: 3.7448: : 108iter [00:11, 11.09iter/s]Best score: 3.7448: : 109iter [00:11, 11.25iter/s]Best score: 3.7448: : 109iter [00:11, 11.25iter/s]Best score: 3.7448: : 110iter [00:11, 11.25iter/s]Best score: 3.7448: : 111iter [00:11, 11.22iter/s]Best score: 3.7448: : 111iter [00:11, 11.22iter/s]Best score: 3.7448: : 112iter [00:11, 11.22iter/s]Best score: 3.7448: : 113iter [00:11, 11.34iter/s]Best score: 3.7448: : 113iter [00:11, 11.34iter/s]Best score: 3.7448: : 114iter [00:11, 11.34iter/s]Best score: 3.7448: : 115iter [00:11, 11.43iter/s]Best score: 3.7448: : 115iter [00:11, 11.43iter/s]Best score: 3.7448: : 116iter [00:12, 11.43iter/s]Best score: 3.7448: : 117iter [00:12, 11.51iter/s]Best score: 3.7448: : 117iter [00:12, 11.51iter/s]Best score: 3.7448: : 118iter [00:12, 11.51iter/s]Best score: 3.7448: : 119iter [00:12, 11.59iter/s]Best score: 3.7448: : 119iter [00:12, 11.59iter/s]Best score: 3.7448: : 120iter [00:12, 11.59iter/s]Best score: 3.7448: : 121iter [00:12, 11.43iter/s]Best score: 3.7448: : 121iter [00:12, 11.43iter/s]Best score: 3.7448: : 122iter [00:12, 11.43iter/s]Best score: 3.7448: : 123iter [00:12, 11.48iter/s]Best score: 3.7448: : 123iter [00:12, 11.48iter/s]Best score: 3.7448: : 124iter [00:12, 11.48iter/s]Best score: 3.7448: : 125iter [00:12, 11.55iter/s]Best score: 3.7448: : 125iter [00:12, 11.55iter/s]Best score: 3.7448: : 126iter [00:12, 11.55iter/s]Best score: 3.7448: : 127iter [00:12, 11.62iter/s]Best score: 3.7448: : 127iter [00:12, 11.62iter/s]Best score: 3.7448: : 128iter [00:13, 11.62iter/s]Best score: 3.7448: : 129iter [00:13, 11.63iter/s]Best score: 3.7448: : 129iter [00:13, 11.63iter/s]Best score: 3.7448: : 130iter [00:13, 11.63iter/s]Best score: 3.7448: : 131iter [00:13, 11.45iter/s]Best score: 3.7448: : 131iter [00:13, 11.45iter/s]Best score: 3.7448: : 132iter [00:13, 11.45iter/s]Best score: 3.7448: : 133iter [00:13, 11.57iter/s]Best score: 3.7448: : 133iter [00:13, 11.57iter/s]Best score: 3.7448: : 134iter [00:13, 11.57iter/s]Best score: 3.7448: : 135iter [00:13, 11.61iter/s]Best score: 3.7448: : 135iter [00:13, 11.61iter/s]Best score: 3.7448: : 136iter [00:13, 11.61iter/s]Best score: 3.7448: : 137iter [00:13, 11.58iter/s]Best score: 3.7448: : 137iter [00:13, 11.58iter/s]Best score: 3.7448: : 138iter [00:13, 11.58iter/s]Best score: 3.7448: : 139iter [00:13, 11.63iter/s]Best score: 3.7448: : 139iter [00:14, 11.63iter/s]Best score: 3.7448: : 140iter [00:14, 11.63iter/s]Best score: 3.7448: : 141iter [00:14, 11.44iter/s]Best score: 3.7448: : 141iter [00:14, 11.44iter/s]Best score: 3.7448: : 142iter [00:14, 11.44iter/s]Best score: 3.7448: : 143iter [00:14, 11.55iter/s]Best score: 3.7448: : 143iter [00:14, 11.55iter/s]Best score: 3.7448: : 144iter [00:14, 11.55iter/s]Best score: 3.7448: : 145iter [00:14, 11.61iter/s]Best score: 3.7448: : 145iter [00:14, 11.61iter/s]Best score: 3.7448: : 146iter [00:14, 11.61iter/s]Best score: 3.7448: : 147iter [00:14, 11.67iter/s]Best score: 3.7448: : 147iter [00:14, 11.67iter/s]Best score: 3.7448: : 148iter [00:14, 11.67iter/s]Best score: 3.7448: : 149iter [00:14, 11.68iter/s]
[ITER 150] Best: 3.7448
[PARAMS] Current best parameters:
  fx: 551.3117
  fy: 549.2025
  px: 996.0331
  py: 765.9423
  k1: -0.00483679
  k2: -0.01965450
  k3: 0.00608361
  k4: 0.00084159
  p1: 0.00340576
  p2: 0.01363824
  p3: -0.01901772
  p4: 0.00456068
  s1: -0.0023
  s2: 0.0072
  s3: 0.0012
  s4: 0.0165
  tilt_x: 0.0238
  tilt_y: -0.0141
  scale: 2.9895
  rotation: 0.6441
Best score: 3.7448: : 149iter [00:14, 11.68iter/s]
[Periodic outlier @ iter 50] Removing 2000R frame 13 (score=41.40, threshold=21.57)
  Remaining frames: 78
Best score: 3.7448: : 150iter [00:15, 11.68iter/s]Best score: 3.7448: : 151iter [00:15,  6.57iter/s]Best score: 3.7448: : 151iter [00:15,  6.57iter/s]Best score: 3.7448: : 152iter [00:15,  6.57iter/s]Best score: 3.7448: : 153iter [00:15,  7.57iter/s]Best score: 3.7448: : 153iter [00:15,  7.57iter/s]Best score: 3.7448: : 154iter [00:15,  7.57iter/s]Best score: 3.7448: : 155iter [00:15,  8.47iter/s]Best score: 3.7448: : 155iter [00:15,  8.47iter/s]Best score: 3.7448: : 156iter [00:15,  8.47iter/s]Best score: 3.7448: : 157iter [00:15,  9.22iter/s]Best score: 3.7448: : 157iter [00:16,  9.22iter/s]Best score: 3.7448: : 158iter [00:16,  9.22iter/s]Best score: 3.7448: : 159iter [00:16,  9.87iter/s]Best score: 3.2988: : 159iter [00:16,  9.87iter/s]Best score: 3.2988: : 160iter [00:16,  9.87iter/s]Best score: 3.2988: : 161iter [00:16, 10.25iter/s]Best score: 3.2988: : 161iter [00:16, 10.25iter/s]Best score: 3.2988: : 162iter [00:16, 10.25iter/s]Best score: 3.2988: : 163iter [00:16, 10.69iter/s]Best score: 3.2988: : 163iter [00:16, 10.69iter/s]Best score: 3.2988: : 164iter [00:16, 10.69iter/s]Best score: 3.2988: : 165iter [00:16, 11.01iter/s]Best score: 3.2988: : 165iter [00:16, 11.01iter/s]Best score: 3.2988: : 166iter [00:16, 11.01iter/s]Best score: 3.2988: : 167iter [00:16, 11.22iter/s]Best score: 3.2988: : 167iter [00:16, 11.22iter/s]Best score: 3.2988: : 168iter [00:16, 11.22iter/s]Best score: 3.2988: : 169iter [00:16, 11.40iter/s]Best score: 3.2988: : 169iter [00:17, 11.40iter/s]Best score: 3.2988: : 170iter [00:17, 11.40iter/s]Best score: 3.2988: : 171iter [00:17, 11.35iter/s]Best score: 3.2988: : 171iter [00:17, 11.35iter/s]Best score: 3.2988: : 172iter [00:17, 11.35iter/s]Best score: 3.2988: : 173iter [00:17, 11.47iter/s]Best score: 3.2988: : 173iter [00:17, 11.47iter/s]Best score: 3.2988: : 174iter [00:17, 11.47iter/s]Best score: 3.2988: : 175iter [00:17, 11.59iter/s]Best score: 3.2988: : 175iter [00:17, 11.59iter/s]Best score: 3.2988: : 176iter [00:17, 11.59iter/s]Best score: 3.2988: : 177iter [00:17, 11.66iter/s]Best score: 3.2988: : 177iter [00:17, 11.66iter/s]Best score: 3.2988: : 178iter [00:17, 11.66iter/s]Best score: 3.2988: : 179iter [00:17, 11.72iter/s]Best score: 3.2988: : 179iter [00:17, 11.72iter/s]Best score: 3.2988: : 180iter [00:17, 11.72iter/s]Best score: 3.2988: : 181iter [00:17, 11.53iter/s]Best score: 3.2988: : 181iter [00:18, 11.53iter/s]Best score: 3.2988: : 182iter [00:18, 11.53iter/s]Best score: 3.2988: : 183iter [00:18, 11.62iter/s]Best score: 3.2988: : 183iter [00:18, 11.62iter/s]Best score: 3.2988: : 184iter [00:18, 11.62iter/s]Best score: 3.2988: : 185iter [00:18, 11.72iter/s]Best score: 3.2988: : 185iter [00:18, 11.72iter/s]Best score: 3.2988: : 186iter [00:18, 11.72iter/s]Best score: 3.2988: : 187iter [00:18, 11.76iter/s]Best score: 3.2988: : 187iter [00:18, 11.76iter/s]Best score: 3.2988: : 188iter [00:18, 11.76iter/s]Best score: 3.2988: : 189iter [00:18, 11.78iter/s]Best score: 3.2988: : 189iter [00:18, 11.78iter/s]Best score: 3.2988: : 190iter [00:18, 11.78iter/s]Best score: 3.2988: : 191iter [00:18, 11.65iter/s]Best score: 3.2988: : 191iter [00:18, 11.65iter/s]Best score: 3.2988: : 192iter [00:18, 11.65iter/s]Best score: 3.2988: : 193iter [00:18, 11.80iter/s]Best score: 3.2988: : 193iter [00:19, 11.80iter/s]Best score: 3.2988: : 194iter [00:19, 11.80iter/s]Best score: 3.2988: : 195iter [00:19, 11.89iter/s]Best score: 3.2988: : 195iter [00:19, 11.89iter/s]Best score: 3.2988: : 196iter [00:19, 11.89iter/s]Best score: 3.2988: : 197iter [00:19, 11.97iter/s]Best score: 3.2988: : 197iter [00:19, 11.97iter/s]Best score: 3.2988: : 198iter [00:19, 11.97iter/s]Best score: 3.2988: : 199iter [00:19, 12.03iter/s]
[ITER 200] Best: 3.2988
[PARAMS] Current best parameters:
  fx: 551.3117
  fy: 549.2025
  px: 996.0331
  py: 765.9423
  k1: -0.00483679
  k2: -0.01965450
  k3: 0.00608361
  k4: 0.00084159
  p1: 0.00340576
  p2: 0.01363824
  p3: -0.01901772
  p4: 0.00456068
  s1: -0.0023
  s2: 0.0072
  s3: 0.0012
  s4: 0.0165
  tilt_x: 0.0238
  tilt_y: -0.0141
  scale: 2.9895
  rotation: 0.6441
Best score: 3.2988: : 199iter [00:19, 12.03iter/s]
[Periodic outlier @ iter 100] Removing 2000R frame 12 (score=37.01, threshold=21.40)
  Remaining frames: 77
Best score: 3.2988: : 200iter [00:20, 12.03iter/s]Best score: 3.2988: : 201iter [00:20,  6.76iter/s]Best score: 3.2988: : 201iter [00:20,  6.76iter/s]Best score: 3.2988: : 202iter [00:20,  6.76iter/s]Best score: 3.2988: : 203iter [00:20,  7.79iter/s]Best score: 3.2988: : 203iter [00:20,  7.79iter/s]Best score: 3.2988: : 204iter [00:20,  7.79iter/s]Best score: 3.2988: : 205iter [00:20,  8.73iter/s]Best score: 3.2988: : 205iter [00:20,  8.73iter/s]Best score: 3.2988: : 206iter [00:20,  8.73iter/s]Best score: 3.2988: : 207iter [00:20,  9.51iter/s]Best score: 3.2988: : 207iter [00:20,  9.51iter/s]Best score: 3.2988: : 208iter [00:20,  9.51iter/s]Best score: 3.2988: : 209iter [00:20, 10.13iter/s]Best score: 2.8731: : 209iter [00:20, 10.13iter/s]Best score: 2.8731: : 210iter [00:20, 10.13iter/s]Best score: 2.8731: : 211iter [00:20, 10.48iter/s]Best score: 2.8731: : 211iter [00:21, 10.48iter/s]Best score: 2.8731: : 212iter [00:21, 10.48iter/s]Best score: 2.8731: : 213iter [00:21, 10.92iter/s]Best score: 2.8731: : 213iter [00:21, 10.92iter/s]Best score: 2.8731: : 214iter [00:21, 10.92iter/s]Best score: 2.8731: : 215iter [00:21, 11.25iter/s]Best score: 2.8731: : 215iter [00:21, 11.25iter/s]Best score: 2.8731: : 216iter [00:21, 11.25iter/s]Best score: 2.8731: : 217iter [00:21, 11.44iter/s]Best score: 2.8731: : 217iter [00:21, 11.44iter/s]Best score: 2.8731: : 218iter [00:21, 11.44iter/s]Best score: 2.8731: : 219iter [00:21, 11.60iter/s]Best score: 2.8731: : 219iter [00:21, 11.60iter/s]Best score: 2.8731: : 220iter [00:21, 11.60iter/s]Best score: 2.8731: : 221iter [00:21, 11.52iter/s]Best score: 2.8731: : 221iter [00:21, 11.52iter/s]Best score: 2.8731: : 222iter [00:21, 11.52iter/s]Best score: 2.8731: : 223iter [00:21, 11.67iter/s]Best score: 2.8731: : 223iter [00:22, 11.67iter/s]Best score: 2.8731: : 224iter [00:22, 11.67iter/s]Best score: 2.8731: : 225iter [00:22, 11.82iter/s]Best score: 2.8731: : 225iter [00:22, 11.82iter/s]Best score: 2.8731: : 226iter [00:22, 11.82iter/s]Best score: 2.8731: : 227iter [00:22, 11.90iter/s]Best score: 2.8731: : 227iter [00:22, 11.90iter/s]Best score: 2.8731: : 228iter [00:22, 11.90iter/s]Best score: 2.8731: : 229iter [00:22, 11.92iter/s]Best score: 2.8731: : 229iter [00:22, 11.92iter/s]Best score: 2.8731: : 230iter [00:22, 11.92iter/s]Best score: 2.8731: : 231iter [00:22, 11.79iter/s]Best score: 2.8731: : 231iter [00:22, 11.79iter/s]Best score: 2.8731: : 232iter [00:22, 11.79iter/s]Best score: 2.8731: : 233iter [00:22, 11.92iter/s]Best score: 2.8731: : 233iter [00:22, 11.92iter/s]Best score: 2.8731: : 234iter [00:22, 11.92iter/s]Best score: 2.8731: : 235iter [00:22, 11.92iter/s]Best score: 2.8731: : 235iter [00:23, 11.92iter/s]Best score: 2.8731: : 236iter [00:23, 11.92iter/s]Best score: 2.8731: : 237iter [00:23, 11.94iter/s]Best score: 2.8731: : 237iter [00:23, 11.94iter/s]Best score: 2.8731: : 238iter [00:23, 11.94iter/s]Best score: 2.8731: : 239iter [00:23, 12.04iter/s]Best score: 2.8731: : 239iter [00:23, 12.04iter/s]Best score: 2.8731: : 240iter [00:23, 12.04iter/s]Best score: 2.8731: : 241iter [00:23, 11.91iter/s]Best score: 2.8731: : 241iter [00:23, 11.91iter/s]Best score: 2.8731: : 242iter [00:23, 11.91iter/s]Best score: 2.8731: : 243iter [00:23, 12.00iter/s]Best score: 2.8731: : 243iter [00:23, 12.00iter/s]Best score: 2.8731: : 244iter [00:23, 12.00iter/s]Best score: 2.8731: : 245iter [00:23, 12.00iter/s]Best score: 2.8731: : 245iter [00:23, 12.00iter/s]Best score: 2.8731: : 246iter [00:23, 12.00iter/s]Best score: 2.8731: : 247iter [00:23, 12.05iter/s]Best score: 2.8731: : 247iter [00:24, 12.05iter/s]Best score: 2.8731: : 248iter [00:24, 12.05iter/s]Best score: 2.8731: : 249iter [00:24, 12.13iter/s]
[ITER 250] Best: 2.8731
[PARAMS] Current best parameters:
  fx: 551.3117
  fy: 549.2025
  px: 996.0331
  py: 765.9423
  k1: -0.00483679
  k2: -0.01965450
  k3: 0.00608361
  k4: 0.00084159
  p1: 0.00340576
  p2: 0.01363824
  p3: -0.01901772
  p4: 0.00456068
  s1: -0.0023
  s2: 0.0072
  s3: 0.0012
  s4: 0.0165
  tilt_x: 0.0238
  tilt_y: -0.0141
  scale: 2.9895
  rotation: 0.6441
Best score: 2.8731: : 249iter [00:24, 12.13iter/s]
[Periodic outlier @ iter 150] Removing 2000R frame 11 (score=22.95, threshold=21.27)
  Remaining frames: 76
Best score: 2.8731: : 250iter [00:24, 12.13iter/s]Best score: 2.8731: : 251iter [00:24,  6.74iter/s]Best score: 2.8731: : 251iter [00:24,  6.74iter/s]Best score: 2.8731: : 252iter [00:24,  6.74iter/s]Best score: 2.8731: : 253iter [00:24,  7.78iter/s]Best score: 2.8731: : 253iter [00:24,  7.78iter/s]Best score: 2.8731: : 254iter [00:25,  7.78iter/s]Best score: 2.8731: : 255iter [00:25,  8.72iter/s]Best score: 2.8731: : 255iter [00:25,  8.72iter/s]Best score: 2.8731: : 256iter [00:25,  8.72iter/s]Best score: 2.8731: : 257iter [00:25,  9.52iter/s]Best score: 2.8731: : 257iter [00:25,  9.52iter/s]Best score: 2.8731: : 258iter [00:25,  9.52iter/s]Best score: 2.8731: : 259iter [00:25, 10.19iter/s]Best score: 2.6228: : 259iter [00:25, 10.19iter/s]Best score: 2.6228: : 260iter [00:25, 10.19iter/s]Best score: 2.6228: : 261iter [00:25, 10.55iter/s]Best score: 2.6228: : 261iter [00:25, 10.55iter/s]Best score: 2.6228: : 262iter [00:25, 10.55iter/s]Best score: 2.6228: : 263iter [00:25, 10.99iter/s]Best score: 2.6228: : 263iter [00:25, 10.99iter/s]Best score: 2.6228: : 264iter [00:25, 10.99iter/s]Best score: 2.6228: : 265iter [00:25, 11.30iter/s]Best score: 2.6228: : 265iter [00:25, 11.30iter/s]Best score: 2.6228: : 266iter [00:26, 11.30iter/s]Best score: 2.6228: : 267iter [00:26, 11.52iter/s]Best score: 2.6228: : 267iter [00:26, 11.52iter/s]Best score: 2.6228: : 268iter [00:26, 11.52iter/s]Best score: 2.6228: : 269iter [00:26, 11.67iter/s]Best score: 2.6228: : 269iter [00:26, 11.67iter/s]Best score: 2.6228: : 270iter [00:26, 11.67iter/s]Best score: 2.6228: : 271iter [00:26, 11.64iter/s]Best score: 2.6228: : 271iter [00:26, 11.64iter/s]Best score: 2.6228: : 272iter [00:26, 11.64iter/s]Best score: 2.6228: : 273iter [00:26, 11.75iter/s]Best score: 2.6228: : 273iter [00:26, 11.75iter/s]Best score: 2.6228: : 274iter [00:26, 11.75iter/s]Best score: 2.6228: : 275iter [00:26, 11.91iter/s]Best score: 2.6228: : 275iter [00:26, 11.91iter/s]Best score: 2.6228: : 276iter [00:26, 11.91iter/s]Best score: 2.6228: : 277iter [00:26, 11.93iter/s]Best score: 2.6228: : 277iter [00:26, 11.93iter/s]Best score: 2.6228: : 278iter [00:27, 11.93iter/s]Best score: 2.6228: : 279iter [00:27, 11.99iter/s]Best score: 2.6228: : 279iter [00:27, 11.99iter/s]Best score: 2.6228: : 280iter [00:27, 11.99iter/s]Best score: 2.6228: : 281iter [00:27, 11.83iter/s]Best score: 2.6228: : 281iter [00:27, 11.83iter/s]Best score: 2.6228: : 282iter [00:27, 11.83iter/s]Best score: 2.6228: : 283iter [00:27, 11.90iter/s]Best score: 2.6228: : 283iter [00:27, 11.90iter/s]Best score: 2.6228: : 284iter [00:27, 11.90iter/s]Best score: 2.6228: : 285iter [00:27, 12.00iter/s]Best score: 2.6228: : 285iter [00:27, 12.00iter/s]Best score: 2.6228: : 286iter [00:27, 12.00iter/s]Best score: 2.6228: : 287iter [00:27, 12.02iter/s]Best score: 2.6228: : 287iter [00:27, 12.02iter/s]Best score: 2.6228: : 288iter [00:27, 12.02iter/s]Best score: 2.6228: : 289iter [00:27, 12.10iter/s]Best score: 2.6228: : 289iter [00:27, 12.10iter/s]Best score: 2.6228: : 290iter [00:28, 12.10iter/s]Best score: 2.6228: : 291iter [00:28, 11.95iter/s]Best score: 2.6228: : 291iter [00:28, 11.95iter/s]Best score: 2.6228: : 292iter [00:28, 11.95iter/s]Best score: 2.6228: : 293iter [00:28, 12.01iter/s]Best score: 2.6228: : 293iter [00:28, 12.01iter/s]Best score: 2.6228: : 294iter [00:28, 12.01iter/s]Best score: 2.6228: : 295iter [00:28, 12.09iter/s]Best score: 2.6228: : 295iter [00:28, 12.09iter/s]Best score: 2.6228: : 296iter [00:28, 12.09iter/s]Best score: 2.6228: : 297iter [00:28, 12.13iter/s]Best score: 2.6228: : 297iter [00:28, 12.13iter/s]Best score: 2.6228: : 298iter [00:28, 12.13iter/s]Best score: 2.6228: : 299iter [00:28, 12.19iter/s]
[ITER 300] Best: 2.6228
[PARAMS] Current best parameters:
  fx: 551.3117
  fy: 549.2025
  px: 996.0331
  py: 765.9423
  k1: -0.00483679
  k2: -0.01965450
  k3: 0.00608361
  k4: 0.00084159
  p1: 0.00340576
  p2: 0.01363824
  p3: -0.01901772
  p4: 0.00456068
  s1: -0.0023
  s2: 0.0072
  s3: 0.0012
  s4: 0.0165
  tilt_x: 0.0238
  tilt_y: -0.0141
  scale: 2.9895
  rotation: 0.6441
Best score: 2.6228: : 299iter [00:28, 12.19iter/s]Best score: 2.6228: : 300iter [00:29, 12.19iter/s]Best score: 2.6228: : 301iter [00:29,  7.87iter/s]Best score: 2.6228: : 301iter [00:29,  7.87iter/s]Best score: 2.6228: : 302iter [00:29,  7.87iter/s]Best score: 2.6228: : 303iter [00:29,  8.82iter/s]Best score: 2.6228: : 303iter [00:29,  8.82iter/s]Best score: 2.6228: : 304iter [00:29,  8.82iter/s]Best score: 2.6228: : 305iter [00:29,  9.64iter/s]Best score: 2.6228: : 305iter [00:29,  9.64iter/s]Best score: 2.6228: : 306iter [00:29,  9.64iter/s]Best score: 2.6228: : 307iter [00:29, 10.34iter/s]Best score: 2.6228: : 307iter [00:29, 10.34iter/s]Best score: 2.6228: : 308iter [00:29, 10.34iter/s]Best score: 2.6228: : 309iter [00:29, 10.88iter/s]Best score: 2.6228: : 309iter [00:29, 10.88iter/s]Best score: 2.6228: : 310iter [00:29, 10.88iter/s]Best score: 2.6228: : 311iter [00:29, 11.12iter/s]Best score: 2.6228: : 311iter [00:30, 11.12iter/s]Best score: 2.6228: : 312iter [00:30, 11.12iter/s]Best score: 2.6228: : 313iter [00:30, 11.48iter/s]Best score: 2.6228: : 313iter [00:30, 11.48iter/s]Best score: 2.6228: : 314iter [00:30, 11.48iter/s]Best score: 2.6228: : 315iter [00:30, 11.77iter/s]Best score: 2.6228: : 315iter [00:30, 11.77iter/s]Best score: 2.6228: : 316iter [00:30, 11.77iter/s]Best score: 2.6228: : 317iter [00:30, 11.90iter/s]Best score: 2.6228: : 317iter [00:30, 11.90iter/s]Best score: 2.6228: : 318iter [00:30, 11.90iter/s]Best score: 2.6228: : 319iter [00:30, 12.05iter/s]Best score: 2.6228: : 319iter [00:30, 12.05iter/s]Best score: 2.6228: : 320iter [00:30, 12.05iter/s]Best score: 2.6228: : 321iter [00:30, 11.96iter/s]Best score: 2.6228: : 321iter [00:30, 11.96iter/s]Best score: 2.6228: : 322iter [00:30, 11.96iter/s]Best score: 2.6228: : 323iter [00:30, 12.12iter/s]Best score: 2.6228: : 323iter [00:31, 12.12iter/s]Best score: 2.6228: : 324iter [00:31, 12.12iter/s]Best score: 2.6228: : 325iter [00:31, 12.23iter/s]Best score: 2.6228: : 325iter [00:31, 12.23iter/s]Best score: 2.6228: : 326iter [00:31, 12.23iter/s]Best score: 2.6228: : 327iter [00:31, 12.31iter/s]Best score: 2.6228: : 327iter [00:31, 12.31iter/s]Best score: 2.6228: : 328iter [00:31, 12.31iter/s]Best score: 2.6228: : 329iter [00:31, 12.33iter/s]Best score: 2.6228: : 329iter [00:31, 12.33iter/s]Best score: 2.6228: : 330iter [00:31, 12.33iter/s]Best score: 2.6228: : 331iter [00:31, 12.16iter/s]Best score: 2.6228: : 331iter [00:31, 12.16iter/s]Best score: 2.6228: : 332iter [00:31, 12.16iter/s]Best score: 2.6228: : 333iter [00:31, 12.28iter/s]Best score: 2.6228: : 333iter [00:31, 12.28iter/s]Best score: 2.6228: : 334iter [00:31, 12.28iter/s]Best score: 2.6228: : 335iter [00:31, 12.37iter/s]Best score: 2.6228: : 335iter [00:31, 12.37iter/s]Best score: 2.6228: : 336iter [00:32, 12.37iter/s]Best score: 2.6228: : 337iter [00:32, 12.39iter/s]Best score: 2.6228: : 337iter [00:32, 12.39iter/s]Best score: 2.6228: : 338iter [00:32, 12.39iter/s]Best score: 2.6228: : 339iter [00:32, 12.41iter/s]Best score: 2.6228: : 339iter [00:32, 12.41iter/s]Best score: 2.6228: : 340iter [00:32, 12.41iter/s]Best score: 2.6228: : 341iter [00:32, 12.20iter/s]Best score: 2.6228: : 341iter [00:32, 12.20iter/s]Best score: 2.6228: : 342iter [00:32, 12.20iter/s]Best score: 2.6228: : 343iter [00:32, 12.29iter/s]Best score: 2.6228: : 343iter [00:32, 12.29iter/s]Best score: 2.6228: : 344iter [00:32, 12.29iter/s]Best score: 2.6228: : 345iter [00:32, 12.31iter/s]Best score: 2.6228: : 345iter [00:32, 12.31iter/s]Best score: 2.6228: : 346iter [00:32, 12.31iter/s]Best score: 2.6228: : 347iter [00:32, 12.35iter/s]Best score: 2.6228: : 347iter [00:32, 12.35iter/s]Best score: 2.6228: : 348iter [00:33, 12.35iter/s]Best score: 2.6228: : 349iter [00:33, 12.39iter/s]
[ITER 350] Best: 2.6228
[PARAMS] Current best parameters:
  fx: 551.3117
  fy: 549.2025
  px: 996.0331
  py: 765.9423
  k1: -0.00483679
  k2: -0.01965450
  k3: 0.00608361
  k4: 0.00084159
  p1: 0.00340576
  p2: 0.01363824
  p3: -0.01901772
  p4: 0.00456068
  s1: -0.0023
  s2: 0.0072
  s3: 0.0012
  s4: 0.0165
  tilt_x: 0.0238
  tilt_y: -0.0141
  scale: 2.9895
  rotation: 0.6441
Best score: 2.6228: : 349iter [00:33, 12.39iter/s]Best score: 2.6228: : 350iter [00:33, 12.39iter/s]Best score: 2.6228: : 351iter [00:33,  7.94iter/s]Best score: 2.6228: : 351iter [00:33,  7.94iter/s]Best score: 2.6228: : 352iter [00:33,  7.94iter/s]Best score: 2.6228: : 353iter [00:33,  8.93iter/s]Best score: 2.6228: : 353iter [00:33,  8.93iter/s]Best score: 2.6228: : 354iter [00:33,  8.93iter/s]Best score: 2.6228: : 355iter [00:33,  9.76iter/s]Best score: 2.6228: : 355iter [00:33,  9.76iter/s]Best score: 2.6228: : 356iter [00:33,  9.76iter/s]Best score: 2.6228: : 357iter [00:33, 10.43iter/s]Best score: 2.6228: : 357iter [00:34, 10.43iter/s]Best score: 2.6228: : 358iter [00:34, 10.43iter/s]Best score: 2.6228: : 359iter [00:34, 10.99iter/s]Best score: 2.6228: : 359iter [00:34, 10.99iter/s]Best score: 2.6228: : 360iter [00:34, 10.99iter/s]Best score: 2.6228: : 361iter [00:34, 11.22iter/s]Best score: 2.6228: : 361iter [00:34, 11.22iter/s]Best score: 2.6228: : 362iter [00:34, 11.22iter/s]Best score: 2.6228: : 363iter [00:34, 11.56iter/s]Best score: 2.6228: : 363iter [00:34, 11.56iter/s]Best score: 2.6228: : 364iter [00:34, 11.56iter/s]Best score: 2.6228: : 365iter [00:34, 11.79iter/s]Best score: 2.6228: : 365iter [00:34, 11.79iter/s]Best score: 2.6228: : 366iter [00:34, 11.79iter/s]Best score: 2.6228: : 367iter [00:34, 11.97iter/s]Best score: 2.6228: : 367iter [00:34, 11.97iter/s]Best score: 2.6228: : 368iter [00:34, 11.97iter/s]Best score: 2.6228: : 369iter [00:34, 12.14iter/s]Best score: 2.6228: : 369iter [00:35, 12.14iter/s]Best score: 2.6228: : 370iter [00:35, 12.14iter/s]Best score: 2.6228: : 371iter [00:35, 12.05iter/s]Best score: 2.6228: : 371iter [00:35, 12.05iter/s]Best score: 2.6228: : 372iter [00:35, 12.05iter/s]Best score: 2.6228: : 373iter [00:35, 12.17iter/s]Best score: 2.6228: : 373iter [00:35, 12.17iter/s]Best score: 2.6228: : 374iter [00:35, 12.17iter/s]Best score: 2.6228: : 375iter [00:35, 12.21iter/s]Best score: 2.6228: : 375iter [00:35, 12.21iter/s]Best score: 2.6228: : 376iter [00:35, 12.21iter/s]Best score: 2.6228: : 377iter [00:35, 12.29iter/s]Best score: 2.6228: : 377iter [00:35, 12.29iter/s]Best score: 2.6228: : 378iter [00:35, 12.29iter/s]Best score: 2.6228: : 379iter [00:35, 12.35iter/s]Best score: 2.6228: : 379iter [00:35, 12.35iter/s]Best score: 2.6228: : 380iter [00:35, 12.35iter/s]Best score: 2.6228: : 381iter [00:35, 12.22iter/s]Best score: 2.6228: : 381iter [00:36, 12.22iter/s]Best score: 2.6228: : 382iter [00:36, 12.22iter/s]Best score: 2.6228: : 383iter [00:36,  9.69iter/s]Best score: 2.6228: : 383iter [00:36,  9.69iter/s]Best score: 2.6228: : 384iter [00:36,  9.69iter/s]Best score: 2.6228: : 385iter [00:36, 10.35iter/s]Best score: 2.6228: : 385iter [00:36, 10.35iter/s]Best score: 2.6228: : 386iter [00:36, 10.35iter/s]Best score: 2.6228: : 387iter [00:36, 10.92iter/s]Best score: 2.6228: : 387iter [00:36, 10.92iter/s]Best score: 2.6228: : 388iter [00:36, 10.92iter/s]Best score: 2.6228: : 389iter [00:36, 11.34iter/s]Best score: 2.6228: : 389iter [00:36, 11.34iter/s]Best score: 2.6228: : 390iter [00:36, 11.34iter/s]Best score: 2.6228: : 391iter [00:36, 11.46iter/s]Best score: 2.6228: : 391iter [00:36, 11.46iter/s]Best score: 2.6228: : 392iter [00:37, 11.46iter/s]Best score: 2.6228: : 393iter [00:37, 11.70iter/s]Best score: 2.6228: : 393iter [00:37, 11.70iter/s]Best score: 2.6228: : 394iter [00:37, 11.70iter/s]Best score: 2.6228: : 395iter [00:37, 11.94iter/s]Best score: 2.6228: : 395iter [00:37, 11.94iter/s]Best score: 2.6228: : 396iter [00:37, 11.94iter/s]Best score: 2.6228: : 397iter [00:37, 12.12iter/s]Best score: 2.6228: : 397iter [00:37, 12.12iter/s]Best score: 2.6228: : 398iter [00:37, 12.12iter/s]Best score: 2.6228: : 399iter [00:37, 12.25iter/s]
[ITER 400] Best: 2.6228
[PARAMS] Current best parameters:
  fx: 551.3117
  fy: 549.2025
  px: 996.0331
  py: 765.9423
  k1: -0.00483679
  k2: -0.01965450
  k3: 0.00608361
  k4: 0.00084159
  p1: 0.00340576
  p2: 0.01363824
  p3: -0.01901772
  p4: 0.00456068
  s1: -0.0023
  s2: 0.0072
  s3: 0.0012
  s4: 0.0165
  tilt_x: 0.0238
  tilt_y: -0.0141
  scale: 2.9895
  rotation: 0.6441
Best score: 2.6228: : 399iter [00:37, 12.25iter/s]Best score: 2.6228: : 400iter [00:38, 12.25iter/s]Best score: 2.6228: : 401iter [00:38,  7.87iter/s]Best score: 2.6228: : 401iter [00:38,  7.87iter/s]Best score: 2.6228: : 402iter [00:38,  7.87iter/s]Best score: 2.6228: : 403iter [00:38,  8.87iter/s]Best score: 2.6228: : 403iter [00:38,  8.87iter/s]Best score: 2.6228: : 404iter [00:38,  8.87iter/s]Best score: 2.6228: : 405iter [00:38,  9.69iter/s]Best score: 2.6228: : 405iter [00:38,  9.69iter/s]Best score: 2.6228: : 406iter [00:38,  9.69iter/s]Best score: 2.6228: : 407iter [00:38, 10.33iter/s]Best score: 2.6228: : 407iter [00:38, 10.33iter/s]Best score: 2.6228: : 408iter [00:38, 10.33iter/s]Best score: 2.6228: : 409iter [00:38, 10.88iter/s]Best score: 1.8017: : 409iter [00:38, 10.88iter/s]Best score: 1.8017: : 410iter [00:38, 10.88iter/s]Best score: 1.8017: : 411iter [00:38, 11.11iter/s]Best score: 1.8017: : 411iter [00:38, 11.11iter/s]Best score: 1.8017: : 412iter [00:38, 11.11iter/s]Best score: 1.8017: : 413iter [00:38, 11.49iter/s]Best score: 1.8017: : 413iter [00:39, 11.49iter/s]Best score: 1.8017: : 414iter [00:39, 11.49iter/s]Best score: 1.8017: : 415iter [00:39, 11.82iter/s]Best score: 1.8017: : 415iter [00:39, 11.82iter/s]Best score: 1.8017: : 416iter [00:39, 11.82iter/s]Best score: 1.8017: : 417iter [00:39, 12.05iter/s]Best score: 1.8017: : 417iter [00:39, 12.05iter/s]Best score: 1.8017: : 418iter [00:39, 12.05iter/s]Best score: 1.8017: : 419iter [00:39, 12.21iter/s]Best score: 1.8017: : 419iter [00:39, 12.21iter/s]Best score: 1.8017: : 420iter [00:39, 12.21iter/s]Best score: 1.8017: : 421iter [00:39, 12.11iter/s]Best score: 1.8017: : 421iter [00:39, 12.11iter/s]Best score: 1.8017: : 422iter [00:39, 12.11iter/s]Best score: 1.8017: : 423iter [00:39, 12.23iter/s]Best score: 1.8017: : 423iter [00:39, 12.23iter/s]Best score: 1.8017: : 424iter [00:39, 12.23iter/s]Best score: 1.8017: : 425iter [00:39, 12.36iter/s]Best score: 1.8017: : 425iter [00:40, 12.36iter/s]Best score: 1.8017: : 426iter [00:40, 12.36iter/s]Best score: 1.8017: : 427iter [00:40, 12.40iter/s]Best score: 1.8017: : 427iter [00:40, 12.40iter/s]Best score: 1.8017: : 428iter [00:40, 12.40iter/s]Best score: 1.8017: : 429iter [00:40, 12.45iter/s]Best score: 1.3115: : 429iter [00:40, 12.45iter/s]Best score: 1.3115: : 430iter [00:40, 12.45iter/s]Best score: 1.3115: : 431iter [00:40, 12.25iter/s]Best score: 1.3115: : 431iter [00:40, 12.25iter/s]Best score: 1.3115: : 432iter [00:40, 12.25iter/s]Best score: 1.3115: : 433iter [00:40, 12.34iter/s]Best score: 1.3115: : 433iter [00:40, 12.34iter/s]Best score: 1.3115: : 434iter [00:40, 12.34iter/s]Best score: 1.3115: : 435iter [00:40, 12.43iter/s]Best score: 1.3115: : 435iter [00:40, 12.43iter/s]Best score: 1.3115: : 436iter [00:40, 12.43iter/s]Best score: 1.3115: : 437iter [00:40, 12.42iter/s]Best score: 1.3115: : 437iter [00:40, 12.42iter/s]Best score: 1.3115: : 438iter [00:41, 12.42iter/s]Best score: 1.3115: : 439iter [00:41, 12.47iter/s]Best score: 1.3115: : 439iter [00:41, 12.47iter/s]Best score: 1.3115: : 440iter [00:41, 12.47iter/s]Best score: 1.3115: : 441iter [00:41, 12.30iter/s]Best score: 1.3115: : 441iter [00:41, 12.30iter/s]Best score: 1.3115: : 442iter [00:41, 12.30iter/s]Best score: 1.3115: : 443iter [00:41, 12.37iter/s]Best score: 1.3115: : 443iter [00:41, 12.37iter/s]Best score: 1.3115: : 444iter [00:41, 12.37iter/s]Best score: 1.3115: : 445iter [00:41, 12.44iter/s]Best score: 1.3115: : 445iter [00:41, 12.44iter/s]Best score: 1.3115: : 446iter [00:41, 12.44iter/s]Best score: 1.3115: : 447iter [00:41, 12.43iter/s]Best score: 1.3115: : 447iter [00:41, 12.43iter/s]Best score: 1.3115: : 448iter [00:41, 12.43iter/s]Best score: 1.3115: : 449iter [00:41, 12.41iter/s]
[ITER 450] Best: 0.7813
[PARAMS] Current best parameters:
  fx: 579.4897
  fy: 577.8938
  px: 992.3306
  py: 759.5806
  k1: -0.04046814
  k2: -0.03183677
  k3: 0.03645030
  k4: -0.01059047
  p1: 0.01141993
  p2: 0.00745780
  p3: -0.01388106
  p4: 0.00061234
  s1: 0.0029
  s2: 0.0018
  s3: 0.0003
  s4: -0.0051
  tilt_x: -0.0227
  tilt_y: -0.0024
  scale: 2.9948
  rotation: 0.2404
Best score: 0.7813: : 449iter [00:41, 12.41iter/s]Best score: 0.7813: : 450iter [00:42, 12.41iter/s]Best score: 0.7813: : 451iter [00:42,  7.92iter/s]Best score: 0.7813: : 451iter [00:42,  7.92iter/s]Best score: 0.7813: : 452iter [00:42,  7.92iter/s]Best score: 0.7813: : 453iter [00:42,  8.89iter/s]Best score: 0.7813: : 453iter [00:42,  8.89iter/s]Best score: 0.7813: : 454iter [00:42,  8.89iter/s]Best score: 0.7813: : 455iter [00:42,  9.74iter/s]Best score: 0.7813: : 455iter [00:42,  9.74iter/s]Best score: 0.7813: : 456iter [00:42,  9.74iter/s]Best score: 0.7813: : 457iter [00:42, 10.40iter/s]Best score: 0.7813: : 457iter [00:42, 10.40iter/s]Best score: 0.7813: : 458iter [00:42, 10.40iter/s]Best score: 0.7813: : 459iter [00:42, 10.95iter/s]Best score: 0.7330: : 459iter [00:43, 10.95iter/s]Best score: 0.7330: : 460iter [00:43, 10.95iter/s]Best score: 0.7330: : 461iter [00:43, 11.18iter/s]Best score: 0.7330: : 461iter [00:43, 11.18iter/s]Best score: 0.7330: : 462iter [00:43, 11.18iter/s]Best score: 0.7330: : 463iter [00:43, 11.57iter/s]Best score: 0.7330: : 463iter [00:43, 11.57iter/s]Best score: 0.7330: : 464iter [00:43, 11.57iter/s]Best score: 0.7330: : 465iter [00:43, 11.80iter/s]Best score: 0.7330: : 465iter [00:43, 11.80iter/s]Best score: 0.7330: : 466iter [00:43, 11.80iter/s]Best score: 0.7330: : 467iter [00:43, 12.01iter/s]Best score: 0.7330: : 467iter [00:43, 12.01iter/s]Best score: 0.7330: : 468iter [00:43, 12.01iter/s]Best score: 0.7330: : 469iter [00:43, 12.14iter/s]Best score: 0.7330: : 469iter [00:43, 12.14iter/s]Best score: 0.7330: : 470iter [00:43, 12.14iter/s]Best score: 0.7330: : 471iter [00:43, 12.06iter/s]Best score: 0.7330: : 471iter [00:44, 12.06iter/s]Best score: 0.7330: : 472iter [00:44, 12.06iter/s]Best score: 0.7330: : 473iter [00:44, 12.18iter/s]Best score: 0.7330: : 473iter [00:44, 12.18iter/s]Best score: 0.7330: : 474iter [00:44, 12.18iter/s]Best score: 0.7330: : 475iter [00:44, 12.24iter/s]Best score: 0.7330: : 475iter [00:44, 12.24iter/s]Best score: 0.7330: : 476iter [00:44, 12.24iter/s]Best score: 0.7330: : 477iter [00:44, 12.32iter/s]Best score: 0.7330: : 477iter [00:44, 12.32iter/s]Best score: 0.7330: : 478iter [00:44, 12.32iter/s]Best score: 0.7330: : 479iter [00:44, 12.39iter/s]Best score: 0.7330: : 479iter [00:44, 12.39iter/s]Best score: 0.7330: : 480iter [00:44, 12.39iter/s]Best score: 0.7330: : 481iter [00:44, 12.23iter/s]Best score: 0.7330: : 481iter [00:44, 12.23iter/s]Best score: 0.7330: : 482iter [00:44, 12.23iter/s]Best score: 0.7330: : 483iter [00:44, 12.34iter/s]Best score: 0.7330: : 483iter [00:45, 12.34iter/s]Best score: 0.7330: : 484iter [00:45, 12.34iter/s]Best score: 0.7330: : 485iter [00:45, 12.39iter/s]Best score: 0.7330: : 485iter [00:45, 12.39iter/s]Best score: 0.7330: : 486iter [00:45, 12.39iter/s]Best score: 0.7330: : 487iter [00:45, 12.40iter/s]Best score: 0.7330: : 487iter [00:45, 12.40iter/s]Best score: 0.7330: : 488iter [00:45, 12.40iter/s]Best score: 0.7330: : 489iter [00:45, 12.44iter/s]Best score: 0.5142: : 489iter [00:45, 12.44iter/s]Best score: 0.5142: : 490iter [00:45, 12.44iter/s]Best score: 0.5142: : 491iter [00:45, 12.23iter/s]Best score: 0.5142: : 491iter [00:45, 12.23iter/s]Best score: 0.5142: : 492iter [00:45, 12.23iter/s]Best score: 0.5142: : 493iter [00:45, 12.24iter/s]Best score: 0.5142: : 493iter [00:45, 12.24iter/s]Best score: 0.5142: : 494iter [00:45, 12.24iter/s]Best score: 0.5142: : 495iter [00:45, 12.28iter/s]Best score: 0.5142: : 495iter [00:45, 12.28iter/s]Best score: 0.5142: : 496iter [00:46, 12.28iter/s]Best score: 0.5142: : 497iter [00:46, 12.30iter/s]Best score: 0.5142: : 497iter [00:46, 12.30iter/s]Best score: 0.5142: : 498iter [00:46, 12.30iter/s]Best score: 0.5142: : 499iter [00:46, 12.38iter/s]
[ITER 500] Best: 0.5142
[PARAMS] Current best parameters:
  fx: 570.2340
  fy: 570.4245
  px: 996.4079
  py: 760.3236
  k1: -0.01989569
  k2: -0.03974415
  k3: 0.02985933
  k4: -0.00678779
  p1: 0.02222145
  p2: 0.00724679
  p3: -0.01795182
  p4: -0.01451472
  s1: 0.0189
  s2: 0.0113
  s3: 0.0051
  s4: 0.0008
  tilt_x: -0.0412
  tilt_y: -0.0190
  scale: 2.9878
  rotation: 0.3802
Best score: 0.5142: : 499iter [00:46, 12.38iter/s]Best score: 0.5142: : 500iter [00:46, 12.38iter/s]Best score: 0.5142: : 501iter [00:46,  7.90iter/s]Best score: 0.5142: : 501iter [00:46,  7.90iter/s]Best score: 0.5142: : 502iter [00:46,  7.90iter/s]Best score: 0.5142: : 503iter [00:46,  8.85iter/s]Best score: 0.5142: : 503iter [00:46,  8.85iter/s]Best score: 0.5142: : 504iter [00:47,  8.85iter/s]Best score: 0.5142: : 505iter [00:47,  9.73iter/s]Best score: 0.5142: : 505iter [00:47,  9.73iter/s]Best score: 0.5142: : 506iter [00:47,  9.73iter/s]Best score: 0.5142: : 507iter [00:47, 10.39iter/s]Best score: 0.5142: : 507iter [00:47, 10.39iter/s]Best score: 0.5142: : 508iter [00:47, 10.39iter/s]Best score: 0.5142: : 509iter [00:47, 10.97iter/s]Best score: 0.5095: : 509iter [00:47, 10.97iter/s]Best score: 0.5095: : 510iter [00:47, 10.97iter/s]Best score: 0.5095: : 511iter [00:47, 11.20iter/s]Best score: 0.5095: : 511iter [00:47, 11.20iter/s]Best score: 0.5095: : 512iter [00:47, 11.20iter/s]Best score: 0.5095: : 513iter [00:47, 11.58iter/s]Best score: 0.5095: : 513iter [00:47, 11.58iter/s]Best score: 0.5095: : 514iter [00:47, 11.58iter/s]Best score: 0.5095: : 515iter [00:47, 11.86iter/s]Best score: 0.5095: : 515iter [00:47, 11.86iter/s]Best score: 0.5095: : 516iter [00:47, 11.86iter/s]Best score: 0.5095: : 517iter [00:47, 12.04iter/s]Best score: 0.5095: : 517iter [00:48, 12.04iter/s]Best score: 0.5095: : 518iter [00:48, 12.04iter/s]Best score: 0.5095: : 519iter [00:48, 12.10iter/s]Best score: 0.3977: : 519iter [00:48, 12.10iter/s]Best score: 0.3977: : 520iter [00:48, 12.10iter/s]Best score: 0.3977: : 521iter [00:48, 12.05iter/s]Best score: 0.3977: : 521iter [00:48, 12.05iter/s]Best score: 0.3977: : 522iter [00:48, 12.05iter/s]Best score: 0.3977: : 523iter [00:48, 12.12iter/s]Best score: 0.3977: : 523iter [00:48, 12.12iter/s]Best score: 0.3977: : 524iter [00:48, 12.12iter/s]Best score: 0.3977: : 525iter [00:48, 12.17iter/s]Best score: 0.3977: : 525iter [00:48, 12.17iter/s]Best score: 0.3977: : 526iter [00:48, 12.17iter/s]Best score: 0.3977: : 527iter [00:48, 12.26iter/s]Best score: 0.3977: : 527iter [00:48, 12.26iter/s]Best score: 0.3977: : 528iter [00:48, 12.26iter/s]Best score: 0.3977: : 529iter [00:48, 12.32iter/s]Best score: 0.3977: : 529iter [00:49, 12.32iter/s]Best score: 0.3977: : 530iter [00:49, 12.32iter/s]Best score: 0.3977: : 531iter [00:49, 12.17iter/s]Best score: 0.3977: : 531iter [00:49, 12.17iter/s]Best score: 0.3977: : 532iter [00:49, 12.17iter/s]Best score: 0.3977: : 533iter [00:49, 12.29iter/s]Best score: 0.3977: : 533iter [00:49, 12.29iter/s]Best score: 0.3977: : 534iter [00:49, 12.29iter/s]Best score: 0.3977: : 535iter [00:49, 12.33iter/s]Best score: 0.3977: : 535iter [00:49, 12.33iter/s]Best score: 0.3977: : 536iter [00:49, 12.33iter/s]Best score: 0.3977: : 537iter [00:49, 12.38iter/s]Best score: 0.3977: : 537iter [00:49, 12.38iter/s]Best score: 0.3977: : 538iter [00:49, 12.38iter/s]Best score: 0.3977: : 539iter [00:49, 12.41iter/s]Best score: 0.3729: : 539iter [00:49, 12.41iter/s]Best score: 0.3729: : 540iter [00:49, 12.41iter/s]Best score: 0.3729: : 541iter [00:49, 12.25iter/s]Best score: 0.3729: : 541iter [00:50, 12.25iter/s]Best score: 0.3729: : 542iter [00:50, 12.25iter/s]Best score: 0.3729: : 543iter [00:50, 12.33iter/s]Best score: 0.3729: : 543iter [00:50, 12.33iter/s]Best score: 0.3729: : 544iter [00:50, 12.33iter/s]Best score: 0.3729: : 545iter [00:50, 12.40iter/s]Best score: 0.3729: : 545iter [00:50, 12.40iter/s]Best score: 0.3729: : 546iter [00:50, 12.40iter/s]Best score: 0.3729: : 547iter [00:50, 12.46iter/s]Best score: 0.3729: : 547iter [00:50, 12.46iter/s]Best score: 0.3729: : 548iter [00:50, 12.46iter/s]Best score: 0.3729: : 549iter [00:50, 12.45iter/s]
[ITER 550] Best: 0.3418
[PARAMS] Current best parameters:
  fx: 560.2477
  fy: 560.4636
  px: 995.2435
  py: 759.2973
  k1: -0.00991530
  k2: -0.03123885
  k3: 0.01958940
  k4: -0.00398659
  p1: 0.00977567
  p2: 0.01621739
  p3: -0.01433645
  p4: -0.01895304
  s1: -0.0025
  s2: 0.0233
  s3: 0.0002
  s4: 0.0181
  tilt_x: -0.0198
  tilt_y: 0.0025
  scale: 2.9778
  rotation: 0.2875
Best score: 0.3418: : 549iter [00:50, 12.45iter/s]Best score: 0.3418: : 550iter [00:51, 12.45iter/s]Best score: 0.3418: : 551iter [00:51,  7.90iter/s]Best score: 0.3418: : 551iter [00:51,  7.90iter/s]Best score: 0.3418: : 552iter [00:51,  7.90iter/s]Best score: 0.3418: : 553iter [00:51,  8.88iter/s]Best score: 0.3418: : 553iter [00:51,  8.88iter/s]Best score: 0.3418: : 554iter [00:51,  8.88iter/s]Best score: 0.3418: : 555iter [00:51,  9.73iter/s]Best score: 0.3418: : 555iter [00:51,  9.73iter/s]Best score: 0.3418: : 556iter [00:51,  9.73iter/s]Best score: 0.3418: : 557iter [00:51, 10.43iter/s]Best score: 0.3418: : 557iter [00:51, 10.43iter/s]Best score: 0.3418: : 558iter [00:51, 10.43iter/s]Best score: 0.3418: : 559iter [00:51, 10.97iter/s]Best score: 0.3418: : 559iter [00:51, 10.97iter/s]Best score: 0.3418: : 560iter [00:51, 10.97iter/s]Best score: 0.3418: : 561iter [00:51, 11.22iter/s]Best score: 0.3418: : 561iter [00:51, 11.22iter/s]Best score: 0.3418: : 562iter [00:52, 11.22iter/s]Best score: 0.3418: : 563iter [00:52, 11.58iter/s]Best score: 0.3418: : 563iter [00:52, 11.58iter/s]Best score: 0.3418: : 564iter [00:52, 11.58iter/s]Best score: 0.3418: : 565iter [00:52, 11.83iter/s]Best score: 0.3418: : 565iter [00:52, 11.83iter/s]Best score: 0.3418: : 566iter [00:52, 11.83iter/s]Best score: 0.3418: : 567iter [00:52, 12.02iter/s]Best score: 0.3418: : 567iter [00:52, 12.02iter/s]Best score: 0.3418: : 568iter [00:52, 12.02iter/s]Best score: 0.3418: : 569iter [00:52, 12.13iter/s]Best score: 0.3418: : 569iter [00:52, 12.13iter/s]Best score: 0.3418: : 570iter [00:52, 12.13iter/s]Best score: 0.3418: : 571iter [00:52, 12.01iter/s]Best score: 0.3418: : 571iter [00:52, 12.01iter/s]Best score: 0.3418: : 572iter [00:52, 12.01iter/s]Best score: 0.3418: : 573iter [00:52, 12.18iter/s]Best score: 0.3418: : 573iter [00:52, 12.18iter/s]Best score: 0.3418: : 574iter [00:52, 12.18iter/s]Best score: 0.3418: : 575iter [00:52, 12.25iter/s]Best score: 0.3418: : 575iter [00:53, 12.25iter/s]Best score: 0.3418: : 576iter [00:53, 12.25iter/s]Best score: 0.3418: : 577iter [00:53, 12.34iter/s]Best score: 0.3418: : 577iter [00:53, 12.34iter/s]Best score: 0.3418: : 578iter [00:53, 12.34iter/s]Best score: 0.3418: : 579iter [00:53, 12.40iter/s]Best score: 0.3195: : 579iter [00:53, 12.40iter/s]Best score: 0.3195: : 580iter [00:53, 12.40iter/s]Best score: 0.3195: : 581iter [00:53, 12.22iter/s]Best score: 0.3195: : 581iter [00:53, 12.22iter/s]Best score: 0.3195: : 582iter [00:53, 12.22iter/s]Best score: 0.3195: : 583iter [00:53, 12.32iter/s]Best score: 0.3195: : 583iter [00:53, 12.32iter/s]Best score: 0.3195: : 584iter [00:53, 12.32iter/s]Best score: 0.3195: : 585iter [00:53, 12.38iter/s]Best score: 0.3195: : 585iter [00:53, 12.38iter/s]Best score: 0.3195: : 586iter [00:53, 12.38iter/s]Best score: 0.3195: : 587iter [00:53, 12.43iter/s]Best score: 0.3195: : 587iter [00:54, 12.43iter/s]Best score: 0.3195: : 588iter [00:54, 12.43iter/s]Best score: 0.3195: : 589iter [00:54, 12.46iter/s]Best score: 0.2845: : 589iter [00:54, 12.46iter/s]Best score: 0.2845: : 590iter [00:54, 12.46iter/s]Best score: 0.2845: : 591iter [00:54, 12.30iter/s]Best score: 0.2845: : 591iter [00:54, 12.30iter/s]Best score: 0.2845: : 592iter [00:54, 12.30iter/s]Best score: 0.2845: : 593iter [00:54, 12.37iter/s]Best score: 0.2845: : 593iter [00:54, 12.37iter/s]Best score: 0.2845: : 594iter [00:54, 12.37iter/s]Best score: 0.2845: : 595iter [00:54, 12.41iter/s]Best score: 0.2845: : 595iter [00:54, 12.41iter/s]Best score: 0.2845: : 596iter [00:54, 12.41iter/s]Best score: 0.2845: : 597iter [00:54, 12.41iter/s]Best score: 0.2845: : 597iter [00:54, 12.41iter/s]Best score: 0.2845: : 598iter [00:54, 12.41iter/s]Best score: 0.2845: : 599iter [00:54, 12.45iter/s]
[ITER 600] Best: 0.2547
[PARAMS] Current best parameters:
  fx: 559.8266
  fy: 559.7990
  px: 994.5793
  py: 759.8964
  k1: 0.00370979
  k2: -0.05261160
  k3: 0.03294419
  k4: -0.00704872
  p1: 0.01247734
  p2: 0.01622407
  p3: -0.00903439
  p4: -0.01330662
  s1: -0.0032
  s2: 0.0117
  s3: -0.0088
  s4: 0.0148
  tilt_x: -0.0241
  tilt_y: 0.0045
  scale: 2.9637
  rotation: 0.3139
Best score: 0.2547: : 599iter [00:55, 12.45iter/s]Best score: 0.2547: : 600iter [00:55, 12.45iter/s]Best score: 0.2547: : 601iter [00:55,  7.92iter/s]Best score: 0.2547: : 601iter [00:55,  7.92iter/s]Best score: 0.2547: : 602iter [00:55,  7.92iter/s]Best score: 0.2547: : 603iter [00:55,  8.90iter/s]Best score: 0.2547: : 603iter [00:55,  8.90iter/s]Best score: 0.2547: : 604iter [00:55,  8.90iter/s]Best score: 0.2547: : 605iter [00:55,  9.73iter/s]Best score: 0.2547: : 605iter [00:55,  9.73iter/s]Best score: 0.2547: : 606iter [00:55,  9.73iter/s]Best score: 0.2547: : 607iter [00:55, 10.43iter/s]Best score: 0.2547: : 607iter [00:55, 10.43iter/s]Best score: 0.2547: : 608iter [00:56, 10.43iter/s]Best score: 0.2547: : 609iter [00:56, 10.98iter/s]Best score: 0.2547: : 609iter [00:56, 10.98iter/s]Best score: 0.2547: : 610iter [00:56, 10.98iter/s]Best score: 0.2547: : 611iter [00:56, 11.23iter/s]Best score: 0.2547: : 611iter [00:56, 11.23iter/s]Best score: 0.2547: : 612iter [00:56, 11.23iter/s]Best score: 0.2547: : 613iter [00:56, 11.59iter/s]Best score: 0.2547: : 613iter [00:56, 11.59iter/s]Best score: 0.2547: : 614iter [00:56, 11.59iter/s]Best score: 0.2547: : 615iter [00:56, 11.85iter/s]Best score: 0.2547: : 615iter [00:56, 11.85iter/s]Best score: 0.2547: : 616iter [00:56, 11.85iter/s]Best score: 0.2547: : 617iter [00:56, 12.04iter/s]Best score: 0.2547: : 617iter [00:56, 12.04iter/s]Best score: 0.2547: : 618iter [00:56, 12.04iter/s]Best score: 0.2547: : 619iter [00:56, 12.16iter/s]Best score: 0.2512: : 619iter [00:56, 12.16iter/s]Best score: 0.2512: : 620iter [00:57, 12.16iter/s]Best score: 0.2512: : 621iter [00:57, 12.08iter/s]Best score: 0.2512: : 621iter [00:57, 12.08iter/s]Best score: 0.2512: : 622iter [00:57, 12.08iter/s]Best score: 0.2512: : 623iter [00:57, 12.19iter/s]Best score: 0.2512: : 623iter [00:57, 12.19iter/s]Best score: 0.2512: : 624iter [00:57, 12.19iter/s]Best score: 0.2512: : 625iter [00:57, 12.30iter/s]Best score: 0.2512: : 625iter [00:57, 12.30iter/s]Best score: 0.2512: : 626iter [00:57, 12.30iter/s]Best score: 0.2512: : 627iter [00:57, 12.36iter/s]Best score: 0.2512: : 627iter [00:57, 12.36iter/s]Best score: 0.2512: : 628iter [00:57, 12.36iter/s]Best score: 0.2512: : 629iter [00:57, 12.42iter/s]Best score: 0.2512: : 629iter [00:57, 12.42iter/s]Best score: 0.2512: : 630iter [00:57, 12.42iter/s]Best score: 0.2512: : 631iter [00:57, 12.26iter/s]Best score: 0.2512: : 631iter [00:57, 12.26iter/s]Best score: 0.2512: : 632iter [00:57, 12.26iter/s]Best score: 0.2512: : 633iter [00:57, 12.27iter/s]Best score: 0.2512: : 633iter [00:58, 12.27iter/s]Best score: 0.2512: : 634iter [00:58, 12.27iter/s]Best score: 0.2512: : 635iter [00:58, 12.34iter/s]Best score: 0.2512: : 635iter [00:58, 12.34iter/s]Best score: 0.2512: : 636iter [00:58, 12.34iter/s]Best score: 0.2512: : 637iter [00:58, 12.42iter/s]Best score: 0.2512: : 637iter [00:58, 12.42iter/s]Best score: 0.2512: : 638iter [00:58, 12.42iter/s]Best score: 0.2512: : 639iter [00:58, 12.35iter/s]Best score: 0.2512: : 639iter [00:58, 12.35iter/s]Best score: 0.2512: : 640iter [00:58, 12.35iter/s]Best score: 0.2512: : 641iter [00:58, 12.16iter/s]Best score: 0.2512: : 641iter [00:58, 12.16iter/s]Best score: 0.2512: : 642iter [00:58, 12.16iter/s]Best score: 0.2512: : 643iter [00:58, 12.25iter/s]Best score: 0.2512: : 643iter [00:58, 12.25iter/s]Best score: 0.2512: : 644iter [00:58, 12.25iter/s]Best score: 0.2512: : 645iter [00:58, 12.33iter/s]Best score: 0.2512: : 645iter [00:59, 12.33iter/s]Best score: 0.2512: : 646iter [00:59, 12.33iter/s]Best score: 0.2512: : 647iter [00:59, 12.39iter/s]Best score: 0.2512: : 647iter [00:59, 12.39iter/s]Best score: 0.2512: : 648iter [00:59, 12.39iter/s]Best score: 0.2512: : 649iter [00:59, 12.46iter/s]
[ITER 650] Best: 0.2512
[PARAMS] Current best parameters:
  fx: 559.7002
  fy: 559.4893
  px: 994.5128
  py: 760.8124
  k1: 0.00147694
  k2: -0.05210023
  k3: 0.03474483
  k4: -0.00788900
  p1: 0.01058019
  p2: 0.01504835
  p3: -0.01130807
  p4: -0.00973467
  s1: -0.0017
  s2: 0.0110
  s3: -0.0048
  s4: 0.0119
  tilt_x: -0.0153
  tilt_y: 0.0037
  scale: 2.9691
  rotation: 0.3406
Best score: 0.2512: : 649iter [00:59, 12.46iter/s]Best score: 0.2512: : 650iter [00:59, 12.46iter/s]Best score: 0.2512: : 651iter [00:59,  7.93iter/s]Best score: 0.2512: : 651iter [00:59,  7.93iter/s]Best score: 0.2512: : 652iter [00:59,  7.93iter/s]Best score: 0.2512: : 653iter [00:59,  8.89iter/s]Best score: 0.2512: : 653iter [00:59,  8.89iter/s]Best score: 0.2512: : 654iter [01:00,  8.89iter/s]Best score: 0.2512: : 655iter [01:00,  9.73iter/s]Best score: 0.2512: : 655iter [01:00,  9.73iter/s]Best score: 0.2512: : 656iter [01:00,  9.73iter/s]Best score: 0.2512: : 657iter [01:00, 10.43iter/s]Best score: 0.2512: : 657iter [01:00, 10.43iter/s]Best score: 0.2512: : 658iter [01:00, 10.43iter/s]Best score: 0.2512: : 659iter [01:00, 10.97iter/s]Best score: 0.2440: : 659iter [01:00, 10.97iter/s]Best score: 0.2440: : 660iter [01:00, 10.97iter/s]Best score: 0.2440: : 661iter [01:00, 11.21iter/s]Best score: 0.2440: : 661iter [01:00, 11.21iter/s]Best score: 0.2440: : 662iter [01:00, 11.21iter/s]Best score: 0.2440: : 663iter [01:00, 11.55iter/s]Best score: 0.2440: : 663iter [01:00, 11.55iter/s]Best score: 0.2440: : 664iter [01:00, 11.55iter/s]Best score: 0.2440: : 665iter [01:00, 11.83iter/s]Best score: 0.2440: : 665iter [01:00, 11.83iter/s]Best score: 0.2440: : 666iter [01:01, 11.83iter/s]Best score: 0.2440: : 667iter [01:01, 12.01iter/s]Best score: 0.2440: : 667iter [01:01, 12.01iter/s]Best score: 0.2440: : 668iter [01:01, 12.01iter/s]Best score: 0.2440: : 669iter [01:01, 12.16iter/s]Best score: 0.2353: : 669iter [01:01, 12.16iter/s]Best score: 0.2353: : 670iter [01:01, 12.16iter/s]Best score: 0.2353: : 671iter [01:01, 12.04iter/s]Best score: 0.2353: : 671iter [01:01, 12.04iter/s]Best score: 0.2353: : 672iter [01:01, 12.04iter/s]Best score: 0.2353: : 673iter [01:01, 12.17iter/s]Best score: 0.2353: : 673iter [01:01, 12.17iter/s]Best score: 0.2353: : 674iter [01:01, 12.17iter/s]Best score: 0.2353: : 675iter [01:01, 12.24iter/s]Best score: 0.2353: : 675iter [01:01, 12.24iter/s]Best score: 0.2353: : 676iter [01:01, 12.24iter/s]Best score: 0.2353: : 677iter [01:01, 12.30iter/s]Best score: 0.2353: : 677iter [01:01, 12.30iter/s]Best score: 0.2353: : 678iter [01:01, 12.30iter/s]Best score: 0.2353: : 679iter [01:01, 12.35iter/s]Best score: 0.2139: : 679iter [01:02, 12.35iter/s]Best score: 0.2139: : 680iter [01:02, 12.35iter/s]Best score: 0.2139: : 681iter [01:02, 12.18iter/s]Best score: 0.2139: : 681iter [01:02, 12.18iter/s]Best score: 0.2139: : 682iter [01:02, 12.18iter/s]Best score: 0.2139: : 683iter [01:02, 12.28iter/s]Best score: 0.2139: : 683iter [01:02, 12.28iter/s]Best score: 0.2139: : 684iter [01:02, 12.28iter/s]Best score: 0.2139: : 685iter [01:02, 12.34iter/s]Best score: 0.2139: : 685iter [01:02, 12.34iter/s]Best score: 0.2139: : 686iter [01:02, 12.34iter/s]Best score: 0.2139: : 687iter [01:02, 12.35iter/s]Best score: 0.2139: : 687iter [01:02, 12.35iter/s]Best score: 0.2139: : 688iter [01:02, 12.35iter/s]Best score: 0.2139: : 689iter [01:02, 12.34iter/s]Best score: 0.2139: : 689iter [01:02, 12.34iter/s]Best score: 0.2139: : 690iter [01:02, 12.34iter/s]Best score: 0.2139: : 691iter [01:02, 12.17iter/s]Best score: 0.2139: : 691iter [01:03, 12.17iter/s]Best score: 0.2139: : 692iter [01:03, 12.17iter/s]Best score: 0.2139: : 693iter [01:03, 12.22iter/s]Best score: 0.2139: : 693iter [01:03, 12.22iter/s]Best score: 0.2139: : 694iter [01:03, 12.22iter/s]Best score: 0.2139: : 695iter [01:03, 12.30iter/s]Best score: 0.2139: : 695iter [01:03, 12.30iter/s]Best score: 0.2139: : 696iter [01:03, 12.30iter/s]Best score: 0.2139: : 697iter [01:03, 12.30iter/s]Best score: 0.2139: : 697iter [01:03, 12.30iter/s]Best score: 0.2139: : 698iter [01:03, 12.30iter/s]Best score: 0.2139: : 699iter [01:03, 12.30iter/s]
[ITER 700] Best: 0.2093
[PARAMS] Current best parameters:
  fx: 553.1984
  fy: 553.1369
  px: 989.5302
  py: 759.3728
  k1: -0.01317952
  k2: -0.01733293
  k3: 0.01389148
  k4: -0.00372705
  p1: 0.01398062
  p2: 0.01615213
  p3: -0.01299436
  p4: -0.01548422
  s1: -0.0052
  s2: 0.0158
  s3: -0.0040
  s4: 0.0142
  tilt_x: -0.0303
  tilt_y: 0.0305
  scale: 2.9953
  rotation: 0.2915
Best score: 0.2093: : 699iter [01:03, 12.30iter/s]Best score: 0.2093: : 700iter [01:04, 12.30iter/s]Best score: 0.2093: : 701iter [01:04,  7.87iter/s]Best score: 0.2093: : 701iter [01:04,  7.87iter/s]Best score: 0.2093: : 702iter [01:04,  7.87iter/s]Best score: 0.2093: : 703iter [01:04,  8.86iter/s]Best score: 0.2093: : 703iter [01:04,  8.86iter/s]Best score: 0.2093: : 704iter [01:04,  8.86iter/s]Best score: 0.2093: : 705iter [01:04,  9.72iter/s]Best score: 0.2093: : 705iter [01:04,  9.72iter/s]Best score: 0.2093: : 706iter [01:04,  9.72iter/s]Best score: 0.2093: : 707iter [01:04, 10.45iter/s]Best score: 0.2093: : 707iter [01:04, 10.45iter/s]Best score: 0.2093: : 708iter [01:04, 10.45iter/s]Best score: 0.2093: : 709iter [01:04, 10.93iter/s]Best score: 0.2047: : 709iter [01:04, 10.93iter/s]Best score: 0.2047: : 710iter [01:04, 10.93iter/s]Best score: 0.2047: : 711iter [01:04, 11.17iter/s]Best score: 0.2047: : 711iter [01:04, 11.17iter/s]Best score: 0.2047: : 712iter [01:05, 11.17iter/s]Best score: 0.2047: : 713iter [01:05, 11.47iter/s]Best score: 0.2047: : 713iter [01:05, 11.47iter/s]Best score: 0.2047: : 714iter [01:05, 11.47iter/s]Best score: 0.2047: : 715iter [01:05, 11.69iter/s]Best score: 0.2047: : 715iter [01:05, 11.69iter/s]Best score: 0.2047: : 716iter [01:05, 11.69iter/s]Best score: 0.2047: : 717iter [01:05, 11.92iter/s]Best score: 0.2047: : 717iter [01:05, 11.92iter/s]Best score: 0.2047: : 718iter [01:05, 11.92iter/s]Best score: 0.2047: : 719iter [01:05, 12.07iter/s]Best score: 0.2047: : 719iter [01:05, 12.07iter/s]Best score: 0.2047: : 720iter [01:05, 12.07iter/s]Best score: 0.2047: : 721iter [01:05, 11.98iter/s]Best score: 0.2047: : 721iter [01:05, 11.98iter/s]Best score: 0.2047: : 722iter [01:05, 11.98iter/s]Best score: 0.2047: : 723iter [01:05, 12.11iter/s]Best score: 0.2047: : 723iter [01:05, 12.11iter/s]Best score: 0.2047: : 724iter [01:06, 12.11iter/s]Best score: 0.2047: : 725iter [01:06, 12.27iter/s]Best score: 0.2047: : 725iter [01:06, 12.27iter/s]Best score: 0.2047: : 726iter [01:06, 12.27iter/s]Best score: 0.2047: : 727iter [01:06, 12.32iter/s]Best score: 0.2047: : 727iter [01:06, 12.32iter/s]Best score: 0.2047: : 728iter [01:06, 12.32iter/s]Best score: 0.2047: : 729iter [01:06, 12.38iter/s]Best score: 0.2047: : 729iter [01:06, 12.38iter/s]Best score: 0.2047: : 730iter [01:06, 12.38iter/s]Best score: 0.2047: : 731iter [01:06, 12.21iter/s]Best score: 0.2047: : 731iter [01:06, 12.21iter/s]Best score: 0.2047: : 732iter [01:06, 12.21iter/s]Best score: 0.2047: : 733iter [01:06, 12.30iter/s]Best score: 0.2047: : 733iter [01:06, 12.30iter/s]Best score: 0.2047: : 734iter [01:06, 12.30iter/s]Best score: 0.2047: : 735iter [01:06, 12.40iter/s]Best score: 0.2047: : 735iter [01:06, 12.40iter/s]Best score: 0.2047: : 736iter [01:07, 12.40iter/s]Best score: 0.2047: : 737iter [01:07, 12.44iter/s]Best score: 0.2047: : 737iter [01:07, 12.44iter/s]Best score: 0.2047: : 738iter [01:07, 12.44iter/s]Best score: 0.2047: : 739iter [01:07, 12.48iter/s]Best score: 0.2027: : 739iter [01:07, 12.48iter/s]Best score: 0.2027: : 740iter [01:07, 12.48iter/s]Best score: 0.2027: : 741iter [01:07, 12.23iter/s]Best score: 0.2027: : 741iter [01:07, 12.23iter/s]Best score: 0.2027: : 742iter [01:07, 12.23iter/s]Best score: 0.2027: : 743iter [01:07, 12.26iter/s]Best score: 0.2027: : 743iter [01:07, 12.26iter/s]Best score: 0.2027: : 744iter [01:07, 12.26iter/s]Best score: 0.2027: : 745iter [01:07, 12.26iter/s]Best score: 0.2027: : 745iter [01:07, 12.26iter/s]Best score: 0.2027: : 746iter [01:07, 12.26iter/s]Best score: 0.2027: : 747iter [01:07, 12.37iter/s]Best score: 0.2027: : 747iter [01:07, 12.37iter/s]Best score: 0.2027: : 748iter [01:07, 12.37iter/s]Best score: 0.2027: : 749iter [01:07, 12.40iter/s]
[ITER 750] Best: 0.2027
[PARAMS] Current best parameters:
  fx: 552.5269
  fy: 552.4107
  px: 989.6121
  py: 758.9335
  k1: -0.00261844
  k2: -0.03374848
  k3: 0.02384723
  k4: -0.00587750
  p1: 0.01282730
  p2: 0.01486655
  p3: -0.01846467
  p4: -0.00934083
  s1: 0.0029
  s2: 0.0086
  s3: 0.0017
  s4: 0.0083
  tilt_x: -0.0298
  tilt_y: 0.0284
  scale: 2.9859
  rotation: 0.2875
Best score: 0.2027: : 749iter [01:08, 12.40iter/s]Best score: 0.2027: : 750iter [01:08, 12.40iter/s]Best score: 0.2027: : 751iter [01:08,  7.92iter/s]Best score: 0.2027: : 751iter [01:08,  7.92iter/s]Best score: 0.2027: : 752iter [01:08,  7.92iter/s]Best score: 0.2027: : 753iter [01:08,  8.91iter/s]Best score: 0.2027: : 753iter [01:08,  8.91iter/s]Best score: 0.2027: : 754iter [01:08,  8.91iter/s]Best score: 0.2027: : 755iter [01:08,  9.77iter/s]Best score: 0.2027: : 755iter [01:08,  9.77iter/s]Best score: 0.2027: : 756iter [01:08,  9.77iter/s]Best score: 0.2027: : 757iter [01:08, 10.48iter/s]Best score: 0.2027: : 757iter [01:08, 10.48iter/s]Best score: 0.2027: : 758iter [01:09, 10.48iter/s]Best score: 0.2027: : 759iter [01:09, 11.03iter/s]Best score: 0.1985: : 759iter [01:09, 11.03iter/s]Best score: 0.1985: : 760iter [01:09, 11.03iter/s]Best score: 0.1985: : 761iter [01:09, 11.28iter/s]Best score: 0.1985: : 761iter [01:09, 11.28iter/s]Best score: 0.1985: : 762iter [01:09, 11.28iter/s]Best score: 0.1985: : 763iter [01:09, 11.64iter/s]Best score: 0.1985: : 763iter [01:09, 11.64iter/s]Best score: 0.1985: : 764iter [01:09, 11.64iter/s]Best score: 0.1985: : 765iter [01:09, 11.89iter/s]Best score: 0.1985: : 765iter [01:09, 11.89iter/s]Best score: 0.1985: : 766iter [01:09, 11.89iter/s]Best score: 0.1985: : 767iter [01:09, 12.08iter/s]Best score: 0.1985: : 767iter [01:09, 12.08iter/s]Best score: 0.1985: : 768iter [01:09, 12.08iter/s]Best score: 0.1985: : 769iter [01:09, 12.22iter/s]Best score: 0.1985: : 769iter [01:09, 12.22iter/s]Best score: 0.1985: : 770iter [01:10, 12.22iter/s]Best score: 0.1985: : 771iter [01:10, 12.15iter/s]Best score: 0.1985: : 771iter [01:10, 12.15iter/s]Best score: 0.1985: : 772iter [01:10, 12.15iter/s]Best score: 0.1985: : 773iter [01:10, 12.31iter/s]Best score: 0.1985: : 773iter [01:10, 12.31iter/s]Best score: 0.1985: : 774iter [01:10, 12.31iter/s]Best score: 0.1985: : 775iter [01:10, 12.42iter/s]Best score: 0.1985: : 775iter [01:10, 12.42iter/s]Best score: 0.1985: : 776iter [01:10, 12.42iter/s]Best score: 0.1985: : 777iter [01:10, 12.46iter/s]Best score: 0.1985: : 777iter [01:10, 12.46iter/s]Best score: 0.1985: : 778iter [01:10, 12.46iter/s]Best score: 0.1985: : 779iter [01:10, 12.47iter/s]Best score: 0.1985: : 779iter [01:10, 12.47iter/s]Best score: 0.1985: : 780iter [01:10, 12.47iter/s]Best score: 0.1985: : 781iter [01:10, 12.30iter/s]Best score: 0.1985: : 781iter [01:10, 12.30iter/s]Best score: 0.1985: : 782iter [01:11, 12.30iter/s]Best score: 0.1985: : 783iter [01:11, 12.39iter/s]Best score: 0.1985: : 783iter [01:11, 12.39iter/s]Best score: 0.1985: : 784iter [01:11, 12.39iter/s]Best score: 0.1985: : 785iter [01:11, 12.47iter/s]Best score: 0.1985: : 785iter [01:11, 12.47iter/s]Best score: 0.1985: : 786iter [01:11, 12.47iter/s]Best score: 0.1985: : 787iter [01:11, 12.53iter/s]Best score: 0.1985: : 787iter [01:11, 12.53iter/s]Best score: 0.1985: : 788iter [01:11, 12.53iter/s]Best score: 0.1985: : 789iter [01:11, 12.54iter/s]Best score: 0.1980: : 789iter [01:11, 12.54iter/s]Best score: 0.1980: : 790iter [01:11, 12.54iter/s]Best score: 0.1980: : 791iter [01:11, 12.32iter/s]Best score: 0.1980: : 791iter [01:11, 12.32iter/s]Best score: 0.1980: : 792iter [01:11, 12.32iter/s]Best score: 0.1980: : 793iter [01:11, 12.36iter/s]Best score: 0.1980: : 793iter [01:11, 12.36iter/s]Best score: 0.1980: : 794iter [01:11, 12.36iter/s]Best score: 0.1980: : 795iter [01:11, 12.43iter/s]Best score: 0.1980: : 795iter [01:12, 12.43iter/s]Best score: 0.1980: : 796iter [01:12, 12.43iter/s]Best score: 0.1980: : 797iter [01:12, 12.50iter/s]Best score: 0.1980: : 797iter [01:12, 12.50iter/s]Best score: 0.1980: : 798iter [01:12, 12.50iter/s]Best score: 0.1980: : 799iter [01:12, 12.51iter/s]
[ITER 800] Best: 0.1980
[PARAMS] Current best parameters:
  fx: 546.5433
  fy: 546.4532
  px: 989.5942
  py: 758.9430
  k1: -0.00987178
  k2: -0.01428423
  k3: 0.01276436
  k4: -0.00371691
  p1: 0.01271394
  p2: 0.01478783
  p3: -0.00890003
  p4: -0.01509695
  s1: -0.0073
  s2: 0.0150
  s3: -0.0064
  s4: 0.0134
  tilt_x: -0.0300
  tilt_y: 0.0287
  scale: 3.0038
  rotation: 0.3166
Best score: 0.1980: : 799iter [01:12, 12.51iter/s]Best score: 0.1980: : 800iter [01:12, 12.51iter/s]Best score: 0.1980: : 801iter [01:12,  7.89iter/s]Best score: 0.1980: : 801iter [01:12,  7.89iter/s]Best score: 0.1980: : 802iter [01:12,  7.89iter/s]Best score: 0.1980: : 803iter [01:12,  8.87iter/s]Best score: 0.1980: : 803iter [01:13,  8.87iter/s]Best score: 0.1980: : 804iter [01:13,  8.87iter/s]Best score: 0.1980: : 805iter [01:13,  9.71iter/s]Best score: 0.1980: : 805iter [01:13,  9.71iter/s]Best score: 0.1980: : 806iter [01:13,  9.71iter/s]Best score: 0.1980: : 807iter [01:13, 10.42iter/s]Best score: 0.1980: : 807iter [01:13, 10.42iter/s]Best score: 0.1980: : 808iter [01:13, 10.42iter/s]Best score: 0.1980: : 809iter [01:13, 10.96iter/s]Best score: 0.1960: : 809iter [01:13, 10.96iter/s]Best score: 0.1960: : 810iter [01:13, 10.96iter/s]Best score: 0.1960: : 811iter [01:13, 11.21iter/s]Best score: 0.1960: : 811iter [01:13, 11.21iter/s]Best score: 0.1960: : 812iter [01:13, 11.21iter/s]Best score: 0.1960: : 813iter [01:13, 11.59iter/s]Best score: 0.1960: : 813iter [01:13, 11.59iter/s]Best score: 0.1960: : 814iter [01:13, 11.59iter/s]Best score: 0.1960: : 815iter [01:13, 11.89iter/s]Best score: 0.1960: : 815iter [01:13, 11.89iter/s]Best score: 0.1960: : 816iter [01:14, 11.89iter/s]Best score: 0.1960: : 817iter [01:14, 12.06iter/s]Best score: 0.1960: : 817iter [01:14, 12.06iter/s]Best score: 0.1960: : 818iter [01:14, 12.06iter/s]Best score: 0.1960: : 819iter [01:14, 12.19iter/s]Best score: 0.1951: : 819iter [01:14, 12.19iter/s]Best score: 0.1951: : 820iter [01:14, 12.19iter/s]Best score: 0.1951: : 821iter [01:14, 12.02iter/s]Best score: 0.1951: : 821iter [01:14, 12.02iter/s]Best score: 0.1951: : 822iter [01:14, 12.02iter/s]Best score: 0.1951: : 823iter [01:14, 12.10iter/s]Best score: 0.1951: : 823iter [01:14, 12.10iter/s]Best score: 0.1951: : 824iter [01:14, 12.10iter/s]Best score: 0.1951: : 825iter [01:14, 12.22iter/s]Best score: 0.1951: : 825iter [01:14, 12.22iter/s]Best score: 0.1951: : 826iter [01:14, 12.22iter/s]Best score: 0.1951: : 827iter [01:14, 12.34iter/s]Best score: 0.1951: : 827iter [01:14, 12.34iter/s]Best score: 0.1951: : 828iter [01:15, 12.34iter/s]Best score: 0.1951: : 829iter [01:15, 12.32iter/s]Best score: 0.1921: : 829iter [01:15, 12.32iter/s]Best score: 0.1921: : 830iter [01:15, 12.32iter/s]Best score: 0.1921: : 831iter [01:15, 12.21iter/s]Best score: 0.1921: : 831iter [01:15, 12.21iter/s]Best score: 0.1921: : 832iter [01:15, 12.21iter/s]Best score: 0.1921: : 833iter [01:15, 12.30iter/s]Best score: 0.1921: : 833iter [01:15, 12.30iter/s]Best score: 0.1921: : 834iter [01:15, 12.30iter/s]Best score: 0.1921: : 835iter [01:15, 12.38iter/s]Best score: 0.1921: : 835iter [01:15, 12.38iter/s]Best score: 0.1921: : 836iter [01:15, 12.38iter/s]Best score: 0.1921: : 837iter [01:15, 12.44iter/s]Best score: 0.1921: : 837iter [01:15, 12.44iter/s]Best score: 0.1921: : 838iter [01:15, 12.44iter/s]Best score: 0.1921: : 839iter [01:15, 12.47iter/s]Best score: 0.1921: : 839iter [01:15, 12.47iter/s]Best score: 0.1921: : 840iter [01:15, 12.47iter/s]Best score: 0.1921: : 841iter [01:15, 12.29iter/s]Best score: 0.1921: : 841iter [01:16, 12.29iter/s]Best score: 0.1921: : 842iter [01:16, 12.29iter/s]Best score: 0.1921: : 843iter [01:16, 12.41iter/s]Best score: 0.1921: : 843iter [01:16, 12.41iter/s]Best score: 0.1921: : 844iter [01:16, 12.41iter/s]Best score: 0.1921: : 845iter [01:16, 12.47iter/s]Best score: 0.1921: : 845iter [01:16, 12.47iter/s]Best score: 0.1921: : 846iter [01:16, 12.47iter/s]Best score: 0.1921: : 847iter [01:16, 12.46iter/s]Best score: 0.1921: : 847iter [01:16, 12.46iter/s]Best score: 0.1921: : 848iter [01:16, 12.46iter/s]Best score: 0.1921: : 849iter [01:16, 12.39iter/s]
[ITER 850] Best: 0.1921
[PARAMS] Current best parameters:
  fx: 549.3204
  fy: 549.2219
  px: 989.0728
  py: 758.5467
  k1: -0.00815296
  k2: -0.01994742
  k3: 0.01522791
  k4: -0.00397552
  p1: 0.01290781
  p2: 0.01443140
  p3: -0.00876781
  p4: -0.01359965
  s1: -0.0065
  s2: 0.0127
  s3: -0.0079
  s4: 0.0127
  tilt_x: -0.0327
  tilt_y: 0.0304
  scale: 2.9978
  rotation: 0.2976
Best score: 0.1921: : 849iter [01:16, 12.39iter/s]Best score: 0.1921: : 850iter [01:17, 12.39iter/s]Best score: 0.1921: : 851iter [01:17,  7.88iter/s]Best score: 0.1921: : 851iter [01:17,  7.88iter/s]Best score: 0.1921: : 852iter [01:17,  7.88iter/s]Best score: 0.1921: : 853iter [01:17,  8.88iter/s]Best score: 0.1921: : 853iter [01:17,  8.88iter/s]Best score: 0.1921: : 854iter [01:17,  8.88iter/s]Best score: 0.1921: : 855iter [01:17,  9.74iter/s]Best score: 0.1921: : 855iter [01:17,  9.74iter/s]Best score: 0.1921: : 856iter [01:17,  9.74iter/s]Best score: 0.1921: : 857iter [01:17,  8.70iter/s]Best score: 0.1921: : 857iter [01:17,  8.70iter/s]Best score: 0.1921: : 858iter [01:17,  8.70iter/s]Best score: 0.1921: : 859iter [01:17,  9.57iter/s]Best score: 0.1921: : 859iter [01:17,  9.57iter/s]Best score: 0.1921: : 860iter [01:18,  9.57iter/s]Best score: 0.1921: : 861iter [01:18, 10.15iter/s]Best score: 0.1921: : 861iter [01:18, 10.15iter/s]Best score: 0.1921: : 862iter [01:18, 10.15iter/s]Best score: 0.1921: : 863iter [01:18, 10.78iter/s]Best score: 0.1921: : 863iter [01:18, 10.78iter/s]Best score: 0.1921: : 864iter [01:18, 10.78iter/s]Best score: 0.1921: : 865iter [01:18, 11.25iter/s]Best score: 0.1921: : 865iter [01:18, 11.25iter/s]Best score: 0.1921: : 866iter [01:18, 11.25iter/s]Best score: 0.1921: : 867iter [01:18, 11.61iter/s]Best score: 0.1921: : 867iter [01:18, 11.61iter/s]Best score: 0.1921: : 868iter [01:18, 11.61iter/s]Best score: 0.1921: : 869iter [01:18, 11.87iter/s]Best score: 0.1901: : 869iter [01:18, 11.87iter/s]Best score: 0.1901: : 870iter [01:18, 11.87iter/s]Best score: 0.1901: : 871iter [01:18, 11.86iter/s]Best score: 0.1901: : 871iter [01:18, 11.86iter/s]Best score: 0.1901: : 872iter [01:19, 11.86iter/s]Best score: 0.1901: : 873iter [01:19, 12.05iter/s]Best score: 0.1901: : 873iter [01:19, 12.05iter/s]Best score: 0.1901: : 874iter [01:19, 12.05iter/s]Best score: 0.1901: : 875iter [01:19, 12.19iter/s]Best score: 0.1901: : 875iter [01:19, 12.19iter/s]Best score: 0.1901: : 876iter [01:19, 12.19iter/s]Best score: 0.1901: : 877iter [01:19, 12.31iter/s]Best score: 0.1901: : 877iter [01:19, 12.31iter/s]Best score: 0.1901: : 878iter [01:19, 12.31iter/s]Best score: 0.1901: : 879iter [01:19, 12.39iter/s]Best score: 0.1900: : 879iter [01:19, 12.39iter/s]Best score: 0.1900: : 880iter [01:19, 12.39iter/s]Best score: 0.1900: : 881iter [01:19, 12.23iter/s]Best score: 0.1900: : 881iter [01:19, 12.23iter/s]Best score: 0.1900: : 882iter [01:19, 12.23iter/s]Best score: 0.1900: : 883iter [01:19, 12.34iter/s]Best score: 0.1900: : 883iter [01:19, 12.34iter/s]Best score: 0.1900: : 884iter [01:19, 12.34iter/s]Best score: 0.1900: : 885iter [01:19, 12.42iter/s]Best score: 0.1900: : 885iter [01:20, 12.42iter/s]Best score: 0.1900: : 886iter [01:20, 12.42iter/s]Best score: 0.1900: : 887iter [01:20, 12.49iter/s]Best score: 0.1900: : 887iter [01:20, 12.49iter/s]Best score: 0.1900: : 888iter [01:20, 12.49iter/s]Best score: 0.1900: : 889iter [01:20, 12.51iter/s]Best score: 0.1900: : 889iter [01:20, 12.51iter/s]Best score: 0.1900: : 890iter [01:20, 12.51iter/s]Best score: 0.1900: : 891iter [01:20, 12.31iter/s]Best score: 0.1900: : 891iter [01:20, 12.31iter/s]Best score: 0.1900: : 892iter [01:20, 12.31iter/s]Best score: 0.1900: : 893iter [01:20, 12.37iter/s]Best score: 0.1900: : 893iter [01:20, 12.37iter/s]Best score: 0.1900: : 894iter [01:20, 12.37iter/s]Best score: 0.1900: : 895iter [01:20, 12.43iter/s]Best score: 0.1900: : 895iter [01:20, 12.43iter/s]Best score: 0.1900: : 896iter [01:20, 12.43iter/s]Best score: 0.1900: : 897iter [01:20, 12.47iter/s]Best score: 0.1900: : 897iter [01:21, 12.47iter/s]Best score: 0.1900: : 898iter [01:21, 12.47iter/s]Best score: 0.1900: : 899iter [01:21, 12.48iter/s]
[ITER 900] Best: 0.1893
[PARAMS] Current best parameters:
  fx: 547.5393
  fy: 547.5082
  px: 990.3740
  py: 757.4716
  k1: -0.00426772
  k2: -0.02298672
  k3: 0.01668375
  k4: -0.00426288
  p1: 0.00981106
  p2: 0.01249109
  p3: -0.00812052
  p4: -0.01253935
  s1: -0.0044
  s2: 0.0118
  s3: -0.0075
  s4: 0.0122
  tilt_x: -0.0316
  tilt_y: 0.0199
  scale: 2.9948
  rotation: 0.3125
Best score: 0.1893: : 899iter [01:21, 12.48iter/s]Best score: 0.1893: : 900iter [01:21, 12.48iter/s]Best score: 0.1893: : 901iter [01:21,  7.92iter/s]Best score: 0.1893: : 901iter [01:21,  7.92iter/s]Best score: 0.1893: : 902iter [01:21,  7.92iter/s]Best score: 0.1893: : 903iter [01:21,  8.92iter/s]Best score: 0.1893: : 903iter [01:21,  8.92iter/s]Best score: 0.1893: : 904iter [01:21,  8.92iter/s]Best score: 0.1893: : 905iter [01:21,  9.76iter/s]Best score: 0.1893: : 905iter [01:21,  9.76iter/s]Best score: 0.1893: : 906iter [01:22,  9.76iter/s]Best score: 0.1893: : 907iter [01:22, 10.47iter/s]Best score: 0.1893: : 907iter [01:22, 10.47iter/s]Best score: 0.1893: : 908iter [01:22, 10.47iter/s]Best score: 0.1893: : 909iter [01:22, 10.96iter/s]Best score: 0.1893: : 909iter [01:22, 10.96iter/s]Best score: 0.1893: : 910iter [01:22, 10.96iter/s]Best score: 0.1893: : 911iter [01:22, 11.23iter/s]Best score: 0.1893: : 911iter [01:22, 11.23iter/s]Best score: 0.1893: : 912iter [01:22, 11.23iter/s]Best score: 0.1893: : 913iter [01:22, 11.58iter/s]Best score: 0.1893: : 913iter [01:22, 11.58iter/s]Best score: 0.1893: : 914iter [01:22, 11.58iter/s]Best score: 0.1893: : 915iter [01:22, 11.83iter/s]Best score: 0.1893: : 915iter [01:22, 11.83iter/s]Best score: 0.1893: : 916iter [01:22, 11.83iter/s]Best score: 0.1893: : 917iter [01:22, 12.00iter/s]Best score: 0.1893: : 917iter [01:22, 12.00iter/s]Best score: 0.1893: : 918iter [01:23, 12.00iter/s]Best score: 0.1893: : 919iter [01:23, 12.12iter/s]Best score: 0.1886: : 919iter [01:23, 12.12iter/s]Best score: 0.1886: : 920iter [01:23, 12.12iter/s]Best score: 0.1886: : 921iter [01:23, 12.07iter/s]Best score: 0.1886: : 921iter [01:23, 12.07iter/s]Best score: 0.1886: : 922iter [01:23, 12.07iter/s]Best score: 0.1886: : 923iter [01:23, 12.15iter/s]Best score: 0.1886: : 923iter [01:23, 12.15iter/s]Best score: 0.1886: : 924iter [01:23, 12.15iter/s]Best score: 0.1886: : 925iter [01:23, 12.26iter/s]Best score: 0.1886: : 925iter [01:23, 12.26iter/s]Best score: 0.1886: : 926iter [01:23, 12.26iter/s]Best score: 0.1886: : 927iter [01:23, 12.34iter/s]Best score: 0.1886: : 927iter [01:23, 12.34iter/s]Best score: 0.1886: : 928iter [01:23, 12.34iter/s]Best score: 0.1886: : 929iter [01:23, 12.35iter/s]Best score: 0.1884: : 929iter [01:23, 12.35iter/s]Best score: 0.1884: : 930iter [01:23, 12.35iter/s]Best score: 0.1884: : 931iter [01:23, 12.17iter/s]Best score: 0.1884: : 931iter [01:24, 12.17iter/s]Best score: 0.1884: : 932iter [01:24, 12.17iter/s]Best score: 0.1884: : 933iter [01:24, 12.29iter/s]Best score: 0.1884: : 933iter [01:24, 12.29iter/s]Best score: 0.1884: : 934iter [01:24, 12.29iter/s]Best score: 0.1884: : 935iter [01:24, 12.41iter/s]Best score: 0.1884: : 935iter [01:24, 12.41iter/s]Best score: 0.1884: : 936iter [01:24, 12.41iter/s]Best score: 0.1884: : 937iter [01:24, 12.39iter/s]Best score: 0.1884: : 937iter [01:24, 12.39iter/s]Best score: 0.1884: : 938iter [01:24, 12.39iter/s]Best score: 0.1884: : 939iter [01:24, 12.45iter/s]Best score: 0.1879: : 939iter [01:24, 12.45iter/s]Best score: 0.1879: : 940iter [01:24, 12.45iter/s]Best score: 0.1879: : 941iter [01:24, 12.30iter/s]Best score: 0.1879: : 941iter [01:24, 12.30iter/s]Best score: 0.1879: : 942iter [01:24, 12.30iter/s]Best score: 0.1879: : 943iter [01:24, 12.36iter/s]Best score: 0.1879: : 943iter [01:25, 12.36iter/s]Best score: 0.1879: : 944iter [01:25, 12.36iter/s]Best score: 0.1879: : 945iter [01:25, 12.41iter/s]Best score: 0.1879: : 945iter [01:25, 12.41iter/s]Best score: 0.1879: : 946iter [01:25, 12.41iter/s]Best score: 0.1879: : 947iter [01:25, 12.44iter/s]Best score: 0.1879: : 947iter [01:25, 12.44iter/s]Best score: 0.1879: : 948iter [01:25, 12.44iter/s]Best score: 0.1879: : 949iter [01:25, 12.42iter/s]
[ITER 950] Best: 0.1872
[PARAMS] Current best parameters:
  fx: 542.8042
  fy: 542.9063
  px: 991.0462
  py: 755.3465
  k1: -0.00373952
  k2: -0.01336287
  k3: 0.00899828
  k4: -0.00237194
  p1: 0.00897055
  p2: 0.00882700
  p3: -0.01151008
  p4: -0.01200183
  s1: 0.0028
  s2: 0.0118
  s3: -0.0054
  s4: 0.0117
  tilt_x: -0.0400
  tilt_y: 0.0094
  scale: 2.9981
  rotation: 0.3162
Best score: 0.1872: : 949iter [01:25, 12.42iter/s]Best score: 0.1872: : 950iter [01:25, 12.42iter/s]Best score: 0.1872: : 951iter [01:25,  7.94iter/s]Best score: 0.1872: : 951iter [01:25,  7.94iter/s]Best score: 0.1872: : 952iter [01:26,  7.94iter/s]Best score: 0.1872: : 953iter [01:26,  8.93iter/s]Best score: 0.1872: : 953iter [01:26,  8.93iter/s]Best score: 0.1872: : 954iter [01:26,  8.93iter/s]Best score: 0.1872: : 955iter [01:26,  9.81iter/s]Best score: 0.1872: : 955iter [01:26,  9.81iter/s]Best score: 0.1872: : 956iter [01:26,  9.81iter/s]Best score: 0.1872: : 957iter [01:26, 10.48iter/s]Best score: 0.1872: : 957iter [01:26, 10.48iter/s]Best score: 0.1872: : 958iter [01:26, 10.48iter/s]Best score: 0.1872: : 959iter [01:26, 11.03iter/s]Best score: 0.1869: : 959iter [01:26, 11.03iter/s]Best score: 0.1869: : 960iter [01:26, 11.03iter/s]Best score: 0.1869: : 961iter [01:26, 11.27iter/s]Best score: 0.1869: : 961iter [01:26, 11.27iter/s]Best score: 0.1869: : 962iter [01:26, 11.27iter/s]Best score: 0.1869: : 963iter [01:26, 11.56iter/s]Best score: 0.1869: : 963iter [01:26, 11.56iter/s]Best score: 0.1869: : 964iter [01:27, 11.56iter/s]Best score: 0.1869: : 965iter [01:27, 11.79iter/s]Best score: 0.1869: : 965iter [01:27, 11.79iter/s]Best score: 0.1869: : 966iter [01:27, 11.79iter/s]Best score: 0.1869: : 967iter [01:27, 11.99iter/s]Best score: 0.1869: : 967iter [01:27, 11.99iter/s]Best score: 0.1869: : 968iter [01:27, 11.99iter/s]Best score: 0.1869: : 969iter [01:27, 12.09iter/s]Best score: 0.1869: : 969iter [01:27, 12.09iter/s]Best score: 0.1869: : 970iter [01:27, 12.09iter/s]Best score: 0.1869: : 971iter [01:27, 11.98iter/s]Best score: 0.1869: : 971iter [01:27, 11.98iter/s]Best score: 0.1869: : 972iter [01:27, 11.98iter/s]Best score: 0.1869: : 973iter [01:27, 12.19iter/s]Best score: 0.1869: : 973iter [01:27, 12.19iter/s]Best score: 0.1869: : 974iter [01:27, 12.19iter/s]Best score: 0.1869: : 975iter [01:27, 12.32iter/s]Best score: 0.1869: : 975iter [01:27, 12.32iter/s]Best score: 0.1869: : 976iter [01:27, 12.32iter/s]Best score: 0.1869: : 977iter [01:27, 12.42iter/s]Best score: 0.1869: : 977iter [01:28, 12.42iter/s]Best score: 0.1869: : 978iter [01:28, 12.42iter/s]Best score: 0.1869: : 979iter [01:28, 12.48iter/s]Best score: 0.1866: : 979iter [01:28, 12.48iter/s]Best score: 0.1866: : 980iter [01:28, 12.48iter/s]Best score: 0.1866: : 981iter [01:28, 12.30iter/s]Best score: 0.1866: : 981iter [01:28, 12.30iter/s]Best score: 0.1866: : 982iter [01:28, 12.30iter/s]Best score: 0.1866: : 983iter [01:28, 12.37iter/s]Best score: 0.1866: : 983iter [01:28, 12.37iter/s]Best score: 0.1866: : 984iter [01:28, 12.37iter/s]Best score: 0.1866: : 985iter [01:28, 12.47iter/s]Best score: 0.1866: : 985iter [01:28, 12.47iter/s]Best score: 0.1866: : 986iter [01:28, 12.47iter/s]Best score: 0.1866: : 987iter [01:28, 12.50iter/s]Best score: 0.1866: : 987iter [01:28, 12.50iter/s]Best score: 0.1866: : 988iter [01:28, 12.50iter/s]Best score: 0.1866: : 989iter [01:28, 12.50iter/s]Best score: 0.1861: : 989iter [01:29, 12.50iter/s]Best score: 0.1861: : 990iter [01:29, 12.50iter/s]Best score: 0.1861: : 991iter [01:29, 12.30iter/s]Best score: 0.1861: : 991iter [01:29, 12.30iter/s]Best score: 0.1861: : 992iter [01:29, 12.30iter/s]Best score: 0.1861: : 993iter [01:29, 12.39iter/s]Best score: 0.1861: : 993iter [01:29, 12.39iter/s]Best score: 0.1861: : 994iter [01:29, 12.39iter/s]Best score: 0.1861: : 995iter [01:29, 12.44iter/s]Best score: 0.1861: : 995iter [01:29, 12.44iter/s]Best score: 0.1861: : 996iter [01:29, 12.44iter/s]Best score: 0.1861: : 997iter [01:29, 12.46iter/s]Best score: 0.1861: : 997iter [01:29, 12.46iter/s]Best score: 0.1861: : 998iter [01:29, 12.46iter/s]Best score: 0.1861: : 999iter [01:29, 12.50iter/s]
[ITER 1000] Best: 0.1861
[PARAMS] Current best parameters:
  fx: 541.2387
  fy: 541.3203
  px: 989.9579
  py: 754.8913
  k1: -0.00252320
  k2: -0.01350070
  k3: 0.00956039
  k4: -0.00264355
  p1: 0.00853970
  p2: 0.00838103
  p3: -0.01554568
  p4: -0.00883266
  s1: 0.0062
  s2: 0.0087
  s3: -0.0017
  s4: 0.0088
  tilt_x: -0.0413
  tilt_y: 0.0139
  scale: 3.0000
  rotation: 0.3156
Best score: 0.1861: : 999iter [01:29, 12.50iter/s]Best score: 0.1861: : 1000iter [01:30, 12.50iter/s]Best score: 0.1861: : 1001iter [01:30,  7.88iter/s]Best score: 0.1861: : 1001iter [01:30,  7.88iter/s]Best score: 0.1861: : 1002iter [01:30,  7.88iter/s]Best score: 0.1861: : 1003iter [01:30,  8.87iter/s]Best score: 0.1861: : 1003iter [01:30,  8.87iter/s]Best score: 0.1861: : 1004iter [01:30,  8.87iter/s]Best score: 0.1861: : 1005iter [01:30,  9.70iter/s]Best score: 0.1861: : 1005iter [01:30,  9.70iter/s]Best score: 0.1861: : 1006iter [01:30,  9.70iter/s]Best score: 0.1861: : 1007iter [01:30, 10.39iter/s]Best score: 0.1861: : 1007iter [01:30, 10.39iter/s]Best score: 0.1861: : 1008iter [01:30, 10.39iter/s]Best score: 0.1861: : 1009iter [01:30, 10.99iter/s]Best score: 0.1861: : 1009iter [01:30, 10.99iter/s]Best score: 0.1861: : 1010iter [01:31, 10.99iter/s]Best score: 0.1861: : 1011iter [01:31, 11.25iter/s]Best score: 0.1861: : 1011iter [01:31, 11.25iter/s]Best score: 0.1861: : 1012iter [01:31, 11.25iter/s]Best score: 0.1861: : 1013iter [01:31, 11.60iter/s]Best score: 0.1861: : 1013iter [01:31, 11.60iter/s]Best score: 0.1861: : 1014iter [01:31, 11.60iter/s]Best score: 0.1861: : 1015iter [01:31, 11.87iter/s]Best score: 0.1861: : 1015iter [01:31, 11.87iter/s]Best score: 0.1861: : 1016iter [01:31, 11.87iter/s]Best score: 0.1861: : 1017iter [01:31, 12.06iter/s]Best score: 0.1861: : 1017iter [01:31, 12.06iter/s]Best score: 0.1861: : 1018iter [01:31, 12.06iter/s]Best score: 0.1861: : 1019iter [01:31, 12.15iter/s]Best score: 0.1859: : 1019iter [01:31, 12.15iter/s]Best score: 0.1859: : 1020iter [01:31, 12.15iter/s]Best score: 0.1859: : 1021iter [01:31, 12.10iter/s]Best score: 0.1859: : 1021iter [01:31, 12.10iter/s]Best score: 0.1859: : 1022iter [01:32, 12.10iter/s]Best score: 0.1859: : 1023iter [01:32, 12.26iter/s]Best score: 0.1859: : 1023iter [01:32, 12.26iter/s]Best score: 0.1859: : 1024iter [01:32, 12.26iter/s]Best score: 0.1859: : 1025iter [01:32, 12.35iter/s]Best score: 0.1859: : 1025iter [01:32, 12.35iter/s]Best score: 0.1859: : 1026iter [01:32, 12.35iter/s]Best score: 0.1859: : 1027iter [01:32, 12.46iter/s]Best score: 0.1859: : 1027iter [01:32, 12.46iter/s]Best score: 0.1859: : 1028iter [01:32, 12.46iter/s]Best score: 0.1859: : 1029iter [01:32, 12.45iter/s]Best score: 0.1859: : 1029iter [01:32, 12.45iter/s]Best score: 0.1859: : 1030iter [01:32, 12.45iter/s]Best score: 0.1859: : 1031iter [01:32, 12.23iter/s]Best score: 0.1859: : 1031iter [01:32, 12.23iter/s]Best score: 0.1859: : 1032iter [01:32, 12.23iter/s]Best score: 0.1859: : 1033iter [01:32, 12.36iter/s]Best score: 0.1859: : 1033iter [01:32, 12.36iter/s]Best score: 0.1859: : 1034iter [01:32, 12.36iter/s]Best score: 0.1859: : 1035iter [01:32, 12.35iter/s]Best score: 0.1859: : 1035iter [01:33, 12.35iter/s]Best score: 0.1859: : 1036iter [01:33, 12.35iter/s]Best score: 0.1859: : 1037iter [01:33, 12.30iter/s]Best score: 0.1859: : 1037iter [01:33, 12.30iter/s]Best score: 0.1859: : 1038iter [01:33, 12.30iter/s]Best score: 0.1859: : 1039iter [01:33, 12.29iter/s]Best score: 0.1859: : 1039iter [01:33, 12.29iter/s]Best score: 0.1859: : 1040iter [01:33, 12.29iter/s]Best score: 0.1859: : 1041iter [01:33, 12.17iter/s]Best score: 0.1859: : 1041iter [01:33, 12.17iter/s]Best score: 0.1859: : 1042iter [01:33, 12.17iter/s]Best score: 0.1859: : 1043iter [01:33, 12.32iter/s]Best score: 0.1859: : 1043iter [01:33, 12.32iter/s]Best score: 0.1859: : 1044iter [01:33, 12.32iter/s]Best score: 0.1859: : 1045iter [01:33, 12.43iter/s]Best score: 0.1859: : 1045iter [01:33, 12.43iter/s]Best score: 0.1859: : 1046iter [01:33, 12.43iter/s]Best score: 0.1859: : 1047iter [01:33, 12.47iter/s]Best score: 0.1859: : 1047iter [01:34, 12.47iter/s]Best score: 0.1859: : 1048iter [01:34, 12.47iter/s]Best score: 0.1859: : 1049iter [01:34, 12.46iter/s]
[ITER 1050] Best: 0.1859
[PARAMS] Current best parameters:
  fx: 541.6058
  fy: 541.6874
  px: 990.1968
  py: 755.0699
  k1: -0.00414743
  k2: -0.01132319
  k3: 0.00814360
  k4: -0.00230158
  p1: 0.00855479
  p2: 0.00940922
  p3: -0.01364607
  p4: -0.01101501
  s1: 0.0036
  s2: 0.0110
  s3: -0.0032
  s4: 0.0109
  tilt_x: -0.0406
  tilt_y: 0.0148
  scale: 3.0009
  rotation: 0.3109
Best score: 0.1859: : 1049iter [01:34, 12.46iter/s]Best score: 0.1859: : 1050iter [01:34, 12.46iter/s]Best score: 0.1859: : 1051iter [01:34,  7.94iter/s]Best score: 0.1859: : 1051iter [01:34,  7.94iter/s]Best score: 0.1859: : 1052iter [01:34,  7.94iter/s]Best score: 0.1859: : 1053iter [01:34,  8.92iter/s]Best score: 0.1859: : 1053iter [01:34,  8.92iter/s]Best score: 0.1859: : 1054iter [01:34,  8.92iter/s]Best score: 0.1859: : 1055iter [01:34,  9.80iter/s]Best score: 0.1859: : 1055iter [01:34,  9.80iter/s]Best score: 0.1859: : 1056iter [01:35,  9.80iter/s]Best score: 0.1859: : 1057iter [01:35, 10.47iter/s]Best score: 0.1859: : 1057iter [01:35, 10.47iter/s]Best score: 0.1859: : 1058iter [01:35, 10.47iter/s]Best score: 0.1859: : 1059iter [01:35, 10.98iter/s]Best score: 0.1859: : 1059iter [01:35, 10.98iter/s]Best score: 0.1859: : 1060iter [01:35, 10.98iter/s]Best score: 0.1859: : 1061iter [01:35, 11.18iter/s]Best score: 0.1859: : 1061iter [01:35, 11.18iter/s]Best score: 0.1859: : 1062iter [01:35, 11.18iter/s]Best score: 0.1859: : 1063iter [01:35, 11.49iter/s]Best score: 0.1859: : 1063iter [01:35, 11.49iter/s]Best score: 0.1859: : 1064iter [01:35, 11.49iter/s]Best score: 0.1859: : 1065iter [01:35, 11.72iter/s]Best score: 0.1859: : 1065iter [01:35, 11.72iter/s]Best score: 0.1859: : 1066iter [01:35, 11.72iter/s]Best score: 0.1859: : 1067iter [01:35, 11.89iter/s]Best score: 0.1859: : 1067iter [01:35, 11.89iter/s]Best score: 0.1859: : 1068iter [01:36, 11.89iter/s]Best score: 0.1859: : 1069iter [01:36, 12.06iter/s]Best score: 0.1859: : 1069iter [01:36, 12.06iter/s]Best score: 0.1859: : 1070iter [01:36, 12.06iter/s]Best score: 0.1859: : 1071iter [01:36, 12.01iter/s]Best score: 0.1859: : 1071iter [01:36, 12.01iter/s]Best score: 0.1859: : 1072iter [01:36, 12.01iter/s]Best score: 0.1859: : 1073iter [01:36, 12.17iter/s]Best score: 0.1859: : 1073iter [01:36, 12.17iter/s]Best score: 0.1859: : 1074iter [01:36, 12.17iter/s]Best score: 0.1859: : 1075iter [01:36, 12.28iter/s]Best score: 0.1859: : 1075iter [01:36, 12.28iter/s]Best score: 0.1859: : 1076iter [01:36, 12.28iter/s]Best score: 0.1859: : 1077iter [01:36, 12.40iter/s]Best score: 0.1859: : 1077iter [01:36, 12.40iter/s]Best score: 0.1859: : 1078iter [01:36, 12.40iter/s]Best score: 0.1859: : 1079iter [01:36, 12.47iter/s]Best score: 0.1859: : 1079iter [01:36, 12.47iter/s]Best score: 0.1859: : 1080iter [01:37, 12.47iter/s]Best score: 0.1859: : 1081iter [01:37, 12.26iter/s]Best score: 0.1859: : 1081iter [01:37, 12.26iter/s]Best score: 0.1859: : 1082iter [01:37, 12.26iter/s]Best score: 0.1859: : 1083iter [01:37, 12.29iter/s]Best score: 0.1859: : 1083iter [01:37, 12.29iter/s]Best score: 0.1859: : 1084iter [01:37, 12.29iter/s]Best score: 0.1859: : 1085iter [01:37, 12.33iter/s]Best score: 0.1859: : 1085iter [01:37, 12.33iter/s]Best score: 0.1859: : 1086iter [01:37, 12.33iter/s]Best score: 0.1859: : 1087iter [01:37, 12.40iter/s]Best score: 0.1859: : 1087iter [01:37, 12.40iter/s]Best score: 0.1859: : 1088iter [01:37, 12.40iter/s]Best score: 0.1859: : 1089iter [01:37, 12.45iter/s]Best score: 0.1859: : 1089iter [01:37, 12.45iter/s]Best score: 0.1859: : 1090iter [01:37, 12.45iter/s]Best score: 0.1859: : 1091iter [01:37, 12.24iter/s]Best score: 0.1859: : 1091iter [01:37, 12.24iter/s]Best score: 0.1859: : 1092iter [01:37, 12.24iter/s]Best score: 0.1859: : 1093iter [01:37, 12.27iter/s]Best score: 0.1859: : 1093iter [01:38, 12.27iter/s]Best score: 0.1859: : 1094iter [01:38, 12.27iter/s]Best score: 0.1859: : 1095iter [01:38, 12.35iter/s]Best score: 0.1859: : 1095iter [01:38, 12.35iter/s]Best score: 0.1859: : 1096iter [01:38, 12.35iter/s]Best score: 0.1859: : 1097iter [01:38, 12.41iter/s]Best score: 0.1859: : 1097iter [01:38, 12.41iter/s]Best score: 0.1859: : 1098iter [01:38, 12.41iter/s]Best score: 0.1859: : 1099iter [01:38, 12.47iter/s]
[ITER 1100] Best: 0.1856
[PARAMS] Current best parameters:
  fx: 541.0592
  fy: 541.1778
  px: 989.5894
  py: 754.4147
  k1: -0.00268780
  k2: -0.01243413
  k3: 0.00853452
  k4: -0.00233950
  p1: 0.00834963
  p2: 0.00835103
  p3: -0.01680677
  p4: -0.00914839
  s1: 0.0072
  s2: 0.0090
  s3: -0.0009
  s4: 0.0094
  tilt_x: -0.0432
  tilt_y: 0.0157
  scale: 3.0002
  rotation: 0.3119
Best score: 0.1856: : 1099iter [01:38, 12.47iter/s]Best score: 0.1856: : 1100iter [01:38, 11.13iter/s]

[📈] Running L-BFGS-B polish after 1100 DE iterations...
  Polish improved score: 0.185632 -> 0.185506

[⭕] Ring refinement pass (3500mm diameter)...
  Points: 95,373 → 88,237 within 3500mm ring
  Ring polish did not improve score: 0.185506
  Success: True
  Tangential distortion: p1=0.008342, p2=0.008346, p3=-0.016806, p4=-0.009138
  ✓ Tangential correction is significant for corner improvement
[✅] Square reference optimization complete. Score: 0.1855
[✅] Parameters copied to: /working/MDC036_W018(6)_2025-10-31/calibration/params.json
[📌] Selecting best parameters...
[✅] Saved final refined parameters.


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


[DEBUG] Parameters being applied to PTD conversion:
    fx: 541.0591508124846
    fy: 541.1778009453104
    px: 989.5893617194542
    py: 754.4146954110429
    k1: -0.0026691484700450932
    k2: -0.012454897149528408
    k3: 0.008504425381133657
    k4: -0.0023168525139193284
    p1: 0.008341507980196387
    p2: 0.008346290768293829
    p3: -0.016805895413363834
    p4: -0.009138187938507871
    scale: 3.0002676132093717
    rotation: 0.31190668714122555
    mmpp: 3.443736283950959

[🔄] Converting 866 frames to PTD, creating debug images for 400 calibration frames...
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[✅] Saved PTDs: /working/MDC036_W018(6)_2025-10-31/calibration/debug/4_undistorted/output/ptd
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[✅] Saved PTDs: /working/MDC036_W018(6)_2025-10-31/calibration/debug/4_undistorted/temp_ptd
[WARN] No .tfd files found for serial extraction
[WARN] Failed to extract serial number from .tfd file. Check that .tfd files exist and contain 'LASERbidh' or 'LASERbidg' pattern. Using 'unknown' as fallback.
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[✅] LUT written to: /working/MDC036_W018(6)_2025-10-31/calibration/debug/4_undistorted/output/LUT.lut
[WARN] Folder name 'MDC036_W018(6)_2025-10-31' does not match expected pattern MDC042_W007_5_28_2025. Using simple naming convention.
[✅] LUT copied to: /working/MDC036_W018(6)_2025-10-31/calibration/MDC036_W018(6)_2025-10-31_unknown.lut

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

[ℹ️] Detected device type: SMD_P3D (rigs: [1000, 1500, 2000]mm)
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                                                                 [A[✅] 2000L: /working/MDC036_W018(6)_2025-10-31/calibration/debug/5_heatmap/2000L_heatmap.png
[✅] 2000L (fitted): /working/MDC036_W018(6)_2025-10-31/calibration/debug/5_heatmap/2000L_heatmap_fitted.png
📁 Rigs (heatmap):  25%|██▌       | 1/4 [00:04<00:12,  4.15s/rig]
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                                                                 [A[✅] 2000R: /working/MDC036_W018(6)_2025-10-31/calibration/debug/5_heatmap/2000R_heatmap.png
[✅] 2000R (fitted): /working/MDC036_W018(6)_2025-10-31/calibration/debug/5_heatmap/2000R_heatmap_fitted.png
📁 Rigs (heatmap):  50%|█████     | 2/4 [00:07<00:07,  3.93s/rig]
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                                                                [A[✅] 1500: /working/MDC036_W018(6)_2025-10-31/calibration/debug/5_heatmap/1500_heatmap.png
[✅] 1500 (fitted): /working/MDC036_W018(6)_2025-10-31/calibration/debug/5_heatmap/1500_heatmap_fitted.png
📁 Rigs (heatmap):  75%|███████▌  | 3/4 [00:12<00:04,  4.15s/rig]
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                                                                [A[✅] 1000: /working/MDC036_W018(6)_2025-10-31/calibration/debug/5_heatmap/1000_heatmap.png
[✅] 1000 (fitted): /working/MDC036_W018(6)_2025-10-31/calibration/debug/5_heatmap/1000_heatmap_fitted.png
📁 Rigs (heatmap): 100%|██████████| 4/4 [00:15<00:00,  3.60s/rig]📁 Rigs (heatmap): 100%|██████████| 4/4 [00:15<00:00,  3.78s/rig]
[✅] all_rigs_average.png
[✅] all_rigs_best.png
[✅] all_rigs_average_fitted.png
[✅] all_rigs_best_fitted.png
[✅] Heatmaps saved to: /working/MDC036_W018(6)_2025-10-31/calibration/debug/5_heatmap
[🏁] Finished processing MDC036_W018(6)_2025-10-31


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