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  1. models/crack/F1_curve.png +0 -0
  2. models/crack/P_curve.png +0 -0
  3. models/crack/R_curve.png +0 -0
  4. models/crack/args.yaml +106 -0
  5. models/crack/confusion_matrix.png +0 -0
  6. models/crack/confusion_matrix_normalized.png +0 -0
  7. models/crack/labels.jpg +0 -0
  8. models/crack/labels_correlogram.jpg +0 -0
  9. models/crack/results.csv +11 -0
  10. models/crack/results.png +0 -0
  11. models/crack/train_batch0.jpg +0 -0
  12. models/crack/train_batch1.jpg +0 -0
  13. models/crack/train_batch2.jpg +0 -0
  14. models/crack/val_batch0_labels.jpg +0 -0
  15. models/crack/val_batch0_pred.jpg +0 -0
  16. models/crack/weights/best.pt +3 -0
  17. models/crack/weights/last.pt +3 -0
  18. smoke/F1_curve.png +0 -0
  19. smoke/PR_curve.png +0 -0
  20. smoke/P_curve.png +0 -0
  21. smoke/R_curve.png +0 -0
  22. models/fire and smoke/args.yaml +106 -0
  23. smoke/confusion_matrix.png +0 -0
  24. smoke/confusion_matrix_normalized.png +0 -0
  25. smoke/labels.jpg +0 -0
  26. smoke/labels_correlogram.jpg +0 -0
  27. models/fire and smoke/results.csv +151 -0
  28. smoke/results.png +0 -0
  29. smoke/train_batch0.jpg +0 -0
  30. smoke/train_batch1.jpg +0 -0
  31. smoke/train_batch2.jpg +0 -0
  32. smoke/train_batch23800.jpg +0 -0
  33. smoke/train_batch23801.jpg +0 -0
  34. smoke/train_batch23802.jpg +0 -0
  35. smoke/val_batch0_labels.jpg +0 -0
  36. smoke/val_batch0_pred.jpg +0 -0
  37. smoke/val_batch1_labels.jpg +0 -0
  38. smoke/val_batch1_pred.jpg +0 -0
  39. smoke/val_batch2_labels.jpg +0 -0
  40. smoke/val_batch2_pred.jpg +0 -0
  41. models/fire and smoke/weights/best.pt +3 -0
  42. models/fire and smoke/weights/last.pt +3 -0
  43. models/pothole/F1_curve.png +0 -0
  44. models/pothole/PR_curve.png +0 -0
  45. models/pothole/P_curve.png +0 -0
  46. models/pothole/R_curve.png +0 -0
  47. models/pothole/args.yaml +107 -0
  48. models/pothole/confusion_matrix.png +0 -0
  49. models/pothole/confusion_matrix_normalized.png +0 -0
  50. models/pothole/labels.jpg +0 -0
models/crack/F1_curve.png ADDED
models/crack/P_curve.png ADDED
models/crack/R_curve.png ADDED
models/crack/args.yaml ADDED
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+ task: detect
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+ mode: train
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+ model: yolov8n.pt
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+ data: upload/data.yaml
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+ epochs: 10
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+ time: null
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+ patience: 100
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+ tracker: botsort.yaml
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+ save_dir: /home/user/.pyenv/runs/detect/train
models/crack/confusion_matrix.png ADDED
models/crack/confusion_matrix_normalized.png ADDED
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models/crack/labels_correlogram.jpg ADDED
models/crack/results.csv ADDED
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+ epoch, train/box_loss, train/cls_loss, train/dfl_loss, metrics/precision(B), metrics/recall(B), metrics/mAP50(B), metrics/mAP50-95(B), val/box_loss, val/cls_loss, val/dfl_loss, lr/pg0, lr/pg1, lr/pg2
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+ task: detect
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+ mode: train
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+ model: yolov8n.pt
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+ data: upload/data.yaml
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+ epochs: 150
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+ patience: 100
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+ fraction: 1.0
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+ profile: false
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+ multi_scale: false
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+ 1, 1.9275, 2.8587, 1.8687, 0.25557, 0.3039, 0.19001, 0.06238, 2.2422, 3.6189, 2.2491, 0.0005524, 0.0005524, 0.0005524
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+ 7, 1.8391, 2.0239, 1.7536, 0.37822, 0.36713, 0.30294, 0.12752, 1.9364, 2.3259, 1.8561, 0.001601, 0.001601, 0.001601
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+ 15, 1.7274, 1.8334, 1.6723, 0.55583, 0.47652, 0.50403, 0.23326, 1.7813, 1.7334, 1.7453, 0.001513, 0.001513, 0.001513
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+ 19, 1.7183, 1.7715, 1.6518, 0.55602, 0.51457, 0.53689, 0.25723, 1.7236, 1.6227, 1.6966, 0.001469, 0.001469, 0.001469
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+ 20, 1.7134, 1.7853, 1.6546, 0.56567, 0.49941, 0.52813, 0.25865, 1.6908, 1.6649, 1.6704, 0.001458, 0.001458, 0.001458
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+ 22, 1.7024, 1.7575, 1.6338, 0.56334, 0.50159, 0.53509, 0.25786, 1.7233, 1.6477, 1.6704, 0.001436, 0.001436, 0.001436
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+ 23, 1.686, 1.7554, 1.6488, 0.56961, 0.51133, 0.5512, 0.26769, 1.7147, 1.6342, 1.689, 0.001425, 0.001425, 0.001425
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+ 24, 1.676, 1.7246, 1.6293, 0.54036, 0.47029, 0.49495, 0.23369, 1.7242, 1.7138, 1.6782, 0.0014139, 0.0014139, 0.0014139
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+ 27, 1.6498, 1.678, 1.6078, 0.56825, 0.52541, 0.54744, 0.27373, 1.6747, 1.5952, 1.6743, 0.0013809, 0.0013809, 0.0013809
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+ 28, 1.6537, 1.6596, 1.6021, 0.57046, 0.52521, 0.54932, 0.27113, 1.6676, 1.5473, 1.6737, 0.0013699, 0.0013699, 0.0013699
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+ 29, 1.6835, 1.71, 1.6308, 0.58273, 0.50996, 0.54938, 0.26096, 1.6948, 1.6316, 1.6571, 0.0013589, 0.0013589, 0.0013589
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+ 30, 1.6561, 1.6901, 1.621, 0.5803, 0.52415, 0.56067, 0.2726, 1.6856, 1.5735, 1.635, 0.0013479, 0.0013479, 0.0013479
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+ 31, 1.653, 1.6477, 1.6063, 0.60985, 0.54129, 0.58286, 0.28941, 1.6424, 1.5444, 1.6546, 0.0013369, 0.0013369, 0.0013369
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+ 32, 1.6522, 1.6509, 1.6174, 0.62272, 0.52217, 0.57853, 0.29246, 1.6588, 1.5042, 1.6546, 0.0013259, 0.0013259, 0.0013259
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+ 33, 1.643, 1.6532, 1.6048, 0.58906, 0.53926, 0.57636, 0.2854, 1.6624, 1.5259, 1.6494, 0.0013149, 0.0013149, 0.0013149
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+ 34, 1.6486, 1.6515, 1.6063, 0.60822, 0.55392, 0.60197, 0.29985, 1.6179, 1.4609, 1.5966, 0.0013039, 0.0013039, 0.0013039
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+ 35, 1.6573, 1.6433, 1.6115, 0.60808, 0.55699, 0.59762, 0.30489, 1.6119, 1.4949, 1.6002, 0.0012929, 0.0012929, 0.0012929
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+ 36, 1.6433, 1.6103, 1.5966, 0.62065, 0.56485, 0.61592, 0.30822, 1.6312, 1.4148, 1.6019, 0.0012819, 0.0012819, 0.0012819
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+ 37, 1.6133, 1.6101, 1.5828, 0.58511, 0.51842, 0.57054, 0.28592, 1.6368, 1.5876, 1.6211, 0.0012709, 0.0012709, 0.0012709
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+ 38, 1.6184, 1.5957, 1.5838, 0.64993, 0.56502, 0.62163, 0.31886, 1.5954, 1.3984, 1.5811, 0.0012599, 0.0012599, 0.0012599
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