Hugging Face's logo

DataForGood
/
yolov8_biolit_crop

Object Detection
biology
coastal
yolov8
Model card Files
xet
 Community
mandresyandri commited on
Commit
d066f5d
·
verified ·
1 Parent(s): 916266c

Upload folder using huggingface_hub

Browse files
Files changed (34) hide show
  1. .DS_Store +0 -0
  2. .gitattributes +20 -19
  3. README.md +4 -6
  4. runs/.DS_Store +0 -0
  5. runs/biolit_v1_bootstrap/F1_curve.png +3 -0
  6. runs/biolit_v1_bootstrap/PR_curve.png +3 -0
  7. runs/biolit_v1_bootstrap/results.png +3 -0
  8. runs/biolit_v1_bootstrap/yolov8l_biolit_v1.pt +3 -0
  9. runs/biolit_v2_bootstrap/.DS_Store +0 -0
  10. runs/biolit_v2_bootstrap/F1_curve.png +3 -0
  11. runs/biolit_v2_bootstrap/PR_curve.png +3 -0
  12. runs/biolit_v2_bootstrap/P_curve.png +3 -0
  13. runs/biolit_v2_bootstrap/R_curve.png +3 -0
  14. runs/biolit_v2_bootstrap/args.yaml +96 -0
  15. runs/biolit_v2_bootstrap/confusion_matrix.png +0 -0
  16. runs/biolit_v2_bootstrap/labels.jpg +3 -0
  17. runs/biolit_v2_bootstrap/labels_correlogram.jpg +3 -0
  18. runs/biolit_v2_bootstrap/results.csv +101 -0
  19. runs/biolit_v2_bootstrap/results.png +3 -0
  20. runs/biolit_v2_bootstrap/train_batch0.jpg +3 -0
  21. runs/biolit_v2_bootstrap/train_batch1.jpg +3 -0
  22. runs/biolit_v2_bootstrap/train_batch2.jpg +3 -0
  23. runs/biolit_v2_bootstrap/val_batch0_labels.jpg +3 -0
  24. runs/biolit_v2_bootstrap/val_batch0_pred.jpg +3 -0
  25. runs/biolit_v2_bootstrap/val_batch1_labels.jpg +3 -0
  26. runs/biolit_v2_bootstrap/val_batch1_pred.jpg +3 -0
  27. runs/biolit_v2_bootstrap/val_batch2_labels.jpg +3 -0
  28. runs/biolit_v2_bootstrap/val_batch2_pred.jpg +3 -0
  29. runs/biolit_v2_bootstrap/weights/best.pt +3 -0
  30. runs/biolit_v2_bootstrap/weights/last.pt +3 -0
  31. runs/biolit_v2_yolo_finetuned/best.pt +3 -0
  32. runs/biolit_v2_yolo_finetuned/metrics_post_training.png +0 -0
  33. runs/biolit_v2_yolo_finetuned/results.csv +51 -0
  34. runs/finetune-yolo-after-dyno-V2/best.pt +3 -0
.DS_Store ADDED
Binary file (6.15 kB). View file
 
.gitattributes CHANGED
@@ -33,22 +33,23 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
- biolit_v1_bootstrap/F1_curve.png filter=lfs diff=lfs merge=lfs -text
37
- biolit_v1_bootstrap/PR_curve.png filter=lfs diff=lfs merge=lfs -text
38
- biolit_v1_bootstrap/results.png filter=lfs diff=lfs merge=lfs -text
39
- biolit_v2_bootstrap/F1_curve.png filter=lfs diff=lfs merge=lfs -text
40
- biolit_v2_bootstrap/PR_curve.png filter=lfs diff=lfs merge=lfs -text
41
- biolit_v2_bootstrap/P_curve.png filter=lfs diff=lfs merge=lfs -text
42
- biolit_v2_bootstrap/R_curve.png filter=lfs diff=lfs merge=lfs -text
43
- biolit_v2_bootstrap/labels.jpg filter=lfs diff=lfs merge=lfs -text
44
- biolit_v2_bootstrap/labels_correlogram.jpg filter=lfs diff=lfs merge=lfs -text
45
- biolit_v2_bootstrap/results.png filter=lfs diff=lfs merge=lfs -text
46
- biolit_v2_bootstrap/train_batch0.jpg filter=lfs diff=lfs merge=lfs -text
47
- biolit_v2_bootstrap/train_batch1.jpg filter=lfs diff=lfs merge=lfs -text
48
- biolit_v2_bootstrap/train_batch2.jpg filter=lfs diff=lfs merge=lfs -text
49
- biolit_v2_bootstrap/val_batch0_labels.jpg filter=lfs diff=lfs merge=lfs -text
50
- biolit_v2_bootstrap/val_batch0_pred.jpg filter=lfs diff=lfs merge=lfs -text
51
- biolit_v2_bootstrap/val_batch1_labels.jpg filter=lfs diff=lfs merge=lfs -text
52
- biolit_v2_bootstrap/val_batch1_pred.jpg filter=lfs diff=lfs merge=lfs -text
53
- biolit_v2_bootstrap/val_batch2_labels.jpg filter=lfs diff=lfs merge=lfs -text
54
- biolit_v2_bootstrap/val_batch2_pred.jpg filter=lfs diff=lfs merge=lfs -text
 
 
33
  *.zip filter=lfs diff=lfs merge=lfs -text
34
  *.zst filter=lfs diff=lfs merge=lfs -text
35
  *tfevents* filter=lfs diff=lfs merge=lfs -text
36
+ runs/biolit_v2_bootstrap/F1_curve.png filter=lfs diff=lfs merge=lfs -text
37
+ runs/biolit_v2_bootstrap/PR_curve.png filter=lfs diff=lfs merge=lfs -text
38
+ runs/biolit_v2_bootstrap/P_curve.png filter=lfs diff=lfs merge=lfs -text
39
+ runs/biolit_v2_bootstrap/R_curve.png filter=lfs diff=lfs merge=lfs -text
40
+ runs/biolit_v2_bootstrap/labels.jpg filter=lfs diff=lfs merge=lfs -text
41
+ runs/biolit_v2_bootstrap/labels_correlogram.jpg filter=lfs diff=lfs merge=lfs -text
42
+ runs/biolit_v2_bootstrap/results.png filter=lfs diff=lfs merge=lfs -text
43
+ runs/biolit_v2_bootstrap/train_batch0.jpg filter=lfs diff=lfs merge=lfs -text
44
+ runs/biolit_v2_bootstrap/train_batch1.jpg filter=lfs diff=lfs merge=lfs -text
45
+ runs/biolit_v2_bootstrap/train_batch2.jpg filter=lfs diff=lfs merge=lfs -text
46
+ runs/biolit_v2_bootstrap/val_batch0_labels.jpg filter=lfs diff=lfs merge=lfs -text
47
+ runs/biolit_v2_bootstrap/val_batch0_pred.jpg filter=lfs diff=lfs merge=lfs -text
48
+ runs/biolit_v2_bootstrap/val_batch1_labels.jpg filter=lfs diff=lfs merge=lfs -text
49
+ runs/biolit_v2_bootstrap/val_batch1_pred.jpg filter=lfs diff=lfs merge=lfs -text
50
+ runs/biolit_v2_bootstrap/val_batch2_labels.jpg filter=lfs diff=lfs merge=lfs -text
51
+ runs/biolit_v2_bootstrap/val_batch2_pred.jpg filter=lfs diff=lfs merge=lfs -text
52
+ runs/biolit_v1_bootstrap/F1_curve.png filter=lfs diff=lfs merge=lfs -text
53
+ runs/biolit_v1_bootstrap/PR_curve.png filter=lfs diff=lfs merge=lfs -text
54
+ runs/biolit_v1_bootstrap/results.png filter=lfs diff=lfs merge=lfs -text
55
+ runs/biolit_v2_yolo_finetuned/results.png filter=lfs diff=lfs merge=lfs -text
README.md CHANGED
@@ -23,6 +23,9 @@ Utilisé pour la **saison 14**.
23
  - **Tâche** : détection d'objets (1 détection par image — l'espèce la plus confiante)
24
  - **Fichier** : `runs/biolit_v2_yolo_finetuned/best.pt`
25
 
 
 
 
26
  ## Données d'entraînement
27
 
28
  Fine-tuné sur ~1 400 images annotées manuellement par un bénévole d l'équipe ML2 en saison,
@@ -38,7 +41,7 @@ from ultralytics import YOLO
38
 
39
  model_path = hf_hub_download(
40
  repo_id="DataForGood/yolov8_biolit_crop",
41
- filename="runs/biolit_v2_yolo_finetuned/best.pt"
42
  )
43
 
44
  model = YOLO(model_path)
@@ -46,8 +49,3 @@ model = YOLO(model_path)
46
  results = model("chemin_vers_image_biolit.jpg", conf=0.4)
47
  results[0].show()
48
  ```
49
-
50
- ## Projet
51
-
52
- Ce modèle est développé dans le cadre du projet **[14_Biolit](https://github.com/dataforgoodfr/14_Biolit)** (Data for Good, saison 14).
53
- Le module d'inférence complet (config, logging, manifeste JSON) est disponible dans `ml/crop_inference/`.
 
23
  - **Tâche** : détection d'objets (1 détection par image — l'espèce la plus confiante)
24
  - **Fichier** : `runs/biolit_v2_yolo_finetuned/best.pt`
25
 
26
+ ## Méthodologie
27
+
28
+
29
  ## Données d'entraînement
30
 
31
  Fine-tuné sur ~1 400 images annotées manuellement par un bénévole d l'équipe ML2 en saison,
 
41
 
42
  model_path = hf_hub_download(
43
  repo_id="DataForGood/yolov8_biolit_crop",
44
+ filename="runs/finetune-yolo-after-dyno-V2/weights/best.pt"
45
  )
46
 
47
  model = YOLO(model_path)
 
49
  results = model("chemin_vers_image_biolit.jpg", conf=0.4)
50
  results[0].show()
51
  ```
 
 
 
 
 
runs/.DS_Store ADDED
Binary file (10.2 kB). View file
 
runs/biolit_v1_bootstrap/F1_curve.png ADDED

Git LFS Details

  • SHA256: 4835aa2a5946849b4e3088e875914dd7ac5755aa37b0e7886bf1ce2edfa42afc
  • Pointer size: 131 Bytes
  • Size of remote file: 120 kB
runs/biolit_v1_bootstrap/PR_curve.png ADDED

Git LFS Details

  • SHA256: b085ce0bae355c3f791b364e919152106a8952f23c96b65be9a7af94d3eebd9b
  • Pointer size: 131 Bytes
  • Size of remote file: 132 kB
runs/biolit_v1_bootstrap/results.png ADDED

Git LFS Details

  • SHA256: ab79206556ecc3eabe359106f620cf7691b71d6f2e3b90bf92fd4f6c87c19c12
  • Pointer size: 131 Bytes
  • Size of remote file: 258 kB
runs/biolit_v1_bootstrap/yolov8l_biolit_v1.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c7a9cf9a4febe897aacbb93aed41b42928831389274c6fef117a2b1ccb735b70
3
+ size 87621178
runs/biolit_v2_bootstrap/.DS_Store ADDED
Binary file (6.15 kB). View file
 
runs/biolit_v2_bootstrap/F1_curve.png ADDED

Git LFS Details

  • SHA256: 3f263f93bedbcdc9757ac201d17032e3bf85c3411759e2f182c0fb231273e8e1
  • Pointer size: 131 Bytes
  • Size of remote file: 133 kB
runs/biolit_v2_bootstrap/PR_curve.png ADDED

Git LFS Details

  • SHA256: cc4371b45fbd6cc69029b1b8721b302429c9182756aa3b61ed3be622c0891245
  • Pointer size: 131 Bytes
  • Size of remote file: 137 kB
runs/biolit_v2_bootstrap/P_curve.png ADDED

Git LFS Details

  • SHA256: efa392a98d9367f95f4577d53851cb06670655798ad62a11fe06d53d8c6ddd13
  • Pointer size: 131 Bytes
  • Size of remote file: 128 kB
runs/biolit_v2_bootstrap/R_curve.png ADDED

Git LFS Details

  • SHA256: 13e854edc8cb8a547c0549dae777b178d90ef28283e347a7ab64f2ed37948ea0
  • Pointer size: 131 Bytes
  • Size of remote file: 146 kB
runs/biolit_v2_bootstrap/args.yaml ADDED
@@ -0,0 +1,96 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ task: detect
2
+ mode: train
3
+ model: yolov8s.pt
4
+ data: dataset_biolit/labeled-images/data.yaml
5
+ epochs: 100
6
+ patience: 50
7
+ batch: 32
8
+ imgsz: 640
9
+ save: true
10
+ save_period: -1
11
+ cache: false
12
+ device: '0'
13
+ workers: 8
14
+ project: runs/
15
+ name: biolit_v2_bootstrap
16
+ exist_ok: true
17
+ pretrained: false
18
+ optimizer: SGD
19
+ verbose: true
20
+ seed: 0
21
+ deterministic: true
22
+ single_cls: false
23
+ image_weights: false
24
+ rect: false
25
+ cos_lr: false
26
+ close_mosaic: 0
27
+ resume: false
28
+ amp: true
29
+ overlap_mask: true
30
+ mask_ratio: 4
31
+ dropout: 0.0
32
+ val: true
33
+ split: val
34
+ save_json: false
35
+ save_hybrid: false
36
+ conf: null
37
+ iou: 0.7
38
+ max_det: 300
39
+ half: false
40
+ dnn: false
41
+ plots: true
42
+ source: null
43
+ show: false
44
+ save_txt: false
45
+ save_conf: false
46
+ save_crop: false
47
+ show_labels: true
48
+ show_conf: true
49
+ vid_stride: 1
50
+ line_thickness: 3
51
+ visualize: false
52
+ augment: false
53
+ agnostic_nms: false
54
+ classes: null
55
+ retina_masks: false
56
+ boxes: true
57
+ format: torchscript
58
+ keras: false
59
+ optimize: false
60
+ int8: false
61
+ dynamic: false
62
+ simplify: false
63
+ opset: null
64
+ workspace: 4
65
+ nms: false
66
+ lr0: 0.01
67
+ lrf: 0.01
68
+ momentum: 0.937
69
+ weight_decay: 0.0005
70
+ warmup_epochs: 3.0
71
+ warmup_momentum: 0.8
72
+ warmup_bias_lr: 0.1
73
+ box: 7.5
74
+ cls: 0.5
75
+ dfl: 1.5
76
+ pose: 12.0
77
+ kobj: 1.0
78
+ label_smoothing: 0.0
79
+ nbs: 64
80
+ hsv_h: 0.015
81
+ hsv_s: 0.7
82
+ hsv_v: 0.4
83
+ degrees: 0.0
84
+ translate: 0.1
85
+ scale: 0.5
86
+ shear: 0.0
87
+ perspective: 0.0
88
+ flipud: 0.0
89
+ fliplr: 0.5
90
+ mosaic: 1.0
91
+ mixup: 0.0
92
+ copy_paste: 0.0
93
+ cfg: null
94
+ v5loader: false
95
+ tracker: botsort.yaml
96
+ save_dir: runs/biolit_v2_bootstrap
runs/biolit_v2_bootstrap/confusion_matrix.png ADDED
runs/biolit_v2_bootstrap/labels.jpg ADDED

Git LFS Details

  • SHA256: da7cccaed7e78c59f0b9092343c89a7137d411fac3a3586409534b95ca76f0bb
  • Pointer size: 131 Bytes
  • Size of remote file: 211 kB
runs/biolit_v2_bootstrap/labels_correlogram.jpg ADDED

Git LFS Details

  • SHA256: cdf8fd3786952010061431c73bdca3cde4c31ba4e2aad0056316d8255100ad6a
  • Pointer size: 131 Bytes
  • Size of remote file: 213 kB
runs/biolit_v2_bootstrap/results.csv ADDED
@@ -0,0 +1,101 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 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
2
+ 0, 0.68449, 1.5591, 1.2188, 0.61324, 0.65687, 0.65745, 0.53721, 0.64774, 1.2749, 1.1201, 0.070105, 0.0033216, 0.0033216
3
+ 1, 0.6236, 1.1176, 1.1601, 0.65793, 0.67704, 0.70137, 0.57562, 0.68487, 1.1472, 1.1595, 0.040039, 0.0065891, 0.0065891
4
+ 2, 0.71537, 1.1822, 1.2223, 0.57281, 0.60603, 0.59426, 0.42052, 0.98825, 1.4841, 1.4342, 0.0099075, 0.0097905, 0.0097905
5
+ 3, 0.81197, 1.2813, 1.2941, 0.56499, 0.61296, 0.57525, 0.42426, 0.95214, 1.4346, 1.428, 0.009703, 0.009703, 0.009703
6
+ 4, 0.78404, 1.2258, 1.2788, 0.64747, 0.61926, 0.64165, 0.49184, 0.85067, 1.3263, 1.3075, 0.009703, 0.009703, 0.009703
7
+ 5, 0.75016, 1.152, 1.2525, 0.63988, 0.63612, 0.64126, 0.50979, 0.80911, 1.2029, 1.2897, 0.009604, 0.009604, 0.009604
8
+ 6, 0.72089, 1.1169, 1.2339, 0.61433, 0.63812, 0.65396, 0.52449, 0.75256, 1.1615, 1.2093, 0.009505, 0.009505, 0.009505
9
+ 7, 0.69933, 1.0902, 1.2217, 0.68116, 0.68159, 0.71748, 0.57988, 0.72394, 1.0795, 1.1779, 0.009406, 0.009406, 0.009406
10
+ 8, 0.67854, 1.0496, 1.205, 0.67862, 0.68205, 0.71555, 0.57981, 0.72486, 1.055, 1.1973, 0.009307, 0.009307, 0.009307
11
+ 9, 0.66565, 1.0387, 1.197, 0.68355, 0.68477, 0.72577, 0.60002, 0.69555, 1.0393, 1.1563, 0.009208, 0.009208, 0.009208
12
+ 10, 0.65346, 1.021, 1.1878, 0.69793, 0.69241, 0.73455, 0.60229, 0.69325, 1.0183, 1.1525, 0.009109, 0.009109, 0.009109
13
+ 11, 0.63761, 0.99647, 1.1763, 0.69431, 0.6916, 0.7383, 0.61145, 0.67153, 1.0116, 1.1402, 0.00901, 0.00901, 0.00901
14
+ 12, 0.6284, 0.97447, 1.1711, 0.68402, 0.69163, 0.72829, 0.60605, 0.67282, 1.0068, 1.1361, 0.008911, 0.008911, 0.008911
15
+ 13, 0.61953, 0.96641, 1.1667, 0.7266, 0.69543, 0.75019, 0.63359, 0.63375, 0.96711, 1.1158, 0.008812, 0.008812, 0.008812
16
+ 14, 0.60351, 0.94061, 1.1509, 0.73778, 0.70598, 0.77137, 0.6505, 0.62074, 0.93386, 1.0848, 0.008713, 0.008713, 0.008713
17
+ 15, 0.59774, 0.92832, 1.1515, 0.72396, 0.70489, 0.75734, 0.64448, 0.61478, 0.94591, 1.0832, 0.008614, 0.008614, 0.008614
18
+ 16, 0.59294, 0.92581, 1.1442, 0.73978, 0.70837, 0.76053, 0.64163, 0.62661, 0.94258, 1.1133, 0.008515, 0.008515, 0.008515
19
+ 17, 0.58725, 0.90528, 1.1428, 0.7279, 0.70026, 0.75658, 0.65103, 0.58869, 0.91876, 1.0745, 0.008416, 0.008416, 0.008416
20
+ 18, 0.5775, 0.89076, 1.1319, 0.72625, 0.72957, 0.77831, 0.66837, 0.58387, 0.88676, 1.0662, 0.008317, 0.008317, 0.008317
21
+ 19, 0.571, 0.88258, 1.1283, 0.73464, 0.7164, 0.78165, 0.66853, 0.59259, 0.88932, 1.0699, 0.008218, 0.008218, 0.008218
22
+ 20, 0.56511, 0.8829, 1.1267, 0.75078, 0.71286, 0.78677, 0.68368, 0.56327, 0.86814, 1.0449, 0.008119, 0.008119, 0.008119
23
+ 21, 0.55951, 0.87203, 1.1216, 0.73778, 0.72429, 0.78531, 0.68047, 0.56527, 0.87278, 1.0499, 0.00802, 0.00802, 0.00802
24
+ 22, 0.54823, 0.85417, 1.115, 0.71482, 0.72399, 0.78091, 0.66542, 0.571, 0.87014, 1.0526, 0.007921, 0.007921, 0.007921
25
+ 23, 0.54474, 0.8417, 1.1122, 0.737, 0.72984, 0.7886, 0.68589, 0.5513, 0.85755, 1.0382, 0.007822, 0.007822, 0.007822
26
+ 24, 0.54523, 0.84508, 1.1122, 0.74706, 0.70506, 0.77885, 0.67385, 0.56793, 0.87097, 1.0523, 0.007723, 0.007723, 0.007723
27
+ 25, 0.53787, 0.8265, 1.1054, 0.76088, 0.71902, 0.79556, 0.69563, 0.54441, 0.84084, 1.029, 0.007624, 0.007624, 0.007624
28
+ 26, 0.53121, 0.8185, 1.1022, 0.73685, 0.75186, 0.80201, 0.6999, 0.54138, 0.83533, 1.0262, 0.007525, 0.007525, 0.007525
29
+ 27, 0.52909, 0.81359, 1.0973, 0.72164, 0.74926, 0.79527, 0.69234, 0.53997, 0.84354, 1.0254, 0.007426, 0.007426, 0.007426
30
+ 28, 0.52206, 0.80797, 1.0955, 0.75656, 0.73027, 0.80015, 0.70138, 0.53229, 0.82867, 1.0208, 0.007327, 0.007327, 0.007327
31
+ 29, 0.52098, 0.79488, 1.0931, 0.74388, 0.72835, 0.79943, 0.69858, 0.53279, 0.83914, 1.0273, 0.007228, 0.007228, 0.007228
32
+ 30, 0.50819, 0.78353, 1.0866, 0.76794, 0.72015, 0.80466, 0.7069, 0.52353, 0.82094, 1.01, 0.007129, 0.007129, 0.007129
33
+ 31, 0.51263, 0.78663, 1.0889, 0.75494, 0.73996, 0.80478, 0.70843, 0.51843, 0.81014, 1.0127, 0.00703, 0.00703, 0.00703
34
+ 32, 0.50993, 0.77113, 1.0814, 0.74709, 0.73508, 0.79921, 0.70545, 0.51942, 0.83661, 1.0135, 0.006931, 0.006931, 0.006931
35
+ 33, 0.49927, 0.7659, 1.0796, 0.75849, 0.72999, 0.80256, 0.70871, 0.50758, 0.82112, 1.0051, 0.006832, 0.006832, 0.006832
36
+ 34, 0.50039, 0.75849, 1.0797, 0.76677, 0.73774, 0.80444, 0.71114, 0.51053, 0.80962, 1.012, 0.006733, 0.006733, 0.006733
37
+ 35, 0.49535, 0.75206, 1.0755, 0.75662, 0.74591, 0.81087, 0.71903, 0.50202, 0.79502, 1.0036, 0.006634, 0.006634, 0.006634
38
+ 36, 0.48776, 0.74349, 1.0674, 0.76537, 0.73731, 0.80514, 0.71539, 0.50079, 0.80423, 1.0033, 0.006535, 0.006535, 0.006535
39
+ 37, 0.48665, 0.72856, 1.0681, 0.76692, 0.72981, 0.80799, 0.71417, 0.50589, 0.80028, 1.0059, 0.006436, 0.006436, 0.006436
40
+ 38, 0.48619, 0.73017, 1.0684, 0.76805, 0.74231, 0.81037, 0.72141, 0.49602, 0.79067, 0.98938, 0.006337, 0.006337, 0.006337
41
+ 39, 0.47733, 0.71879, 1.063, 0.77608, 0.73332, 0.8081, 0.72054, 0.49884, 0.79419, 0.99751, 0.006238, 0.006238, 0.006238
42
+ 40, 0.47737, 0.7111, 1.061, 0.76321, 0.75188, 0.81874, 0.73204, 0.49187, 0.77177, 0.99628, 0.006139, 0.006139, 0.006139
43
+ 41, 0.47862, 0.70617, 1.063, 0.76339, 0.75327, 0.81592, 0.72661, 0.49969, 0.78109, 1.0043, 0.00604, 0.00604, 0.00604
44
+ 42, 0.47153, 0.70973, 1.0575, 0.76238, 0.74566, 0.81263, 0.73084, 0.47976, 0.77845, 0.98552, 0.005941, 0.005941, 0.005941
45
+ 43, 0.46657, 0.69068, 1.0552, 0.76328, 0.7504, 0.8187, 0.73189, 0.48603, 0.76756, 0.99279, 0.005842, 0.005842, 0.005842
46
+ 44, 0.46384, 0.68655, 1.0571, 0.77241, 0.72824, 0.81465, 0.72755, 0.47856, 0.77881, 0.98131, 0.005743, 0.005743, 0.005743
47
+ 45, 0.46181, 0.6791, 1.0487, 0.75601, 0.74649, 0.81222, 0.72918, 0.47257, 0.78493, 0.98138, 0.005644, 0.005644, 0.005644
48
+ 46, 0.45599, 0.67445, 1.046, 0.7825, 0.73734, 0.81948, 0.737, 0.47344, 0.75876, 0.97808, 0.005545, 0.005545, 0.005545
49
+ 47, 0.45258, 0.66656, 1.0426, 0.7733, 0.73664, 0.81285, 0.73023, 0.48088, 0.77339, 0.98184, 0.005446, 0.005446, 0.005446
50
+ 48, 0.45192, 0.65988, 1.0446, 0.7728, 0.74941, 0.8171, 0.73406, 0.47711, 0.76046, 0.98006, 0.005347, 0.005347, 0.005347
51
+ 49, 0.44823, 0.65564, 1.0371, 0.7567, 0.75547, 0.81568, 0.73428, 0.47308, 0.77014, 0.98067, 0.005248, 0.005248, 0.005248
52
+ 50, 0.44693, 0.64441, 1.0357, 0.78062, 0.74524, 0.81798, 0.73678, 0.47335, 0.76127, 0.97886, 0.005149, 0.005149, 0.005149
53
+ 51, 0.44266, 0.63783, 1.0334, 0.7693, 0.75036, 0.81736, 0.73711, 0.47549, 0.7571, 0.97969, 0.00505, 0.00505, 0.00505
54
+ 52, 0.43697, 0.63639, 1.0317, 0.78582, 0.73172, 0.81932, 0.73989, 0.46294, 0.75658, 0.97263, 0.004951, 0.004951, 0.004951
55
+ 53, 0.43745, 0.63091, 1.0316, 0.76632, 0.75569, 0.82194, 0.74192, 0.4645, 0.75582, 0.97208, 0.004852, 0.004852, 0.004852
56
+ 54, 0.43468, 0.62173, 1.0322, 0.77456, 0.74583, 0.81612, 0.73797, 0.4658, 0.76476, 0.97482, 0.004753, 0.004753, 0.004753
57
+ 55, 0.43169, 0.61779, 1.0298, 0.76992, 0.75106, 0.81782, 0.73959, 0.46063, 0.76649, 0.96868, 0.004654, 0.004654, 0.004654
58
+ 56, 0.42871, 0.61421, 1.0284, 0.76989, 0.75887, 0.82376, 0.74635, 0.45831, 0.75074, 0.97124, 0.004555, 0.004555, 0.004555
59
+ 57, 0.42505, 0.60544, 1.0233, 0.77675, 0.7484, 0.82051, 0.74247, 0.46042, 0.76221, 0.97436, 0.004456, 0.004456, 0.004456
60
+ 58, 0.42678, 0.59804, 1.0251, 0.78705, 0.73642, 0.82209, 0.74517, 0.45515, 0.75334, 0.96755, 0.004357, 0.004357, 0.004357
61
+ 59, 0.42453, 0.59301, 1.0219, 0.77948, 0.74787, 0.8178, 0.74101, 0.45913, 0.76101, 0.96923, 0.004258, 0.004258, 0.004258
62
+ 60, 0.41821, 0.58885, 1.0163, 0.77705, 0.74996, 0.8197, 0.74197, 0.45967, 0.76231, 0.97115, 0.004159, 0.004159, 0.004159
63
+ 61, 0.41573, 0.57826, 1.0168, 0.77841, 0.74701, 0.81864, 0.74378, 0.45388, 0.76187, 0.96794, 0.00406, 0.00406, 0.00406
64
+ 62, 0.41408, 0.57604, 1.0143, 0.77901, 0.75071, 0.81494, 0.74083, 0.45285, 0.76884, 0.96923, 0.003961, 0.003961, 0.003961
65
+ 63, 0.4117, 0.57275, 1.0171, 0.77746, 0.75219, 0.8188, 0.74254, 0.45494, 0.76885, 0.97292, 0.003862, 0.003862, 0.003862
66
+ 64, 0.4071, 0.56701, 1.0112, 0.77994, 0.75784, 0.8212, 0.74659, 0.45255, 0.76122, 0.96734, 0.003763, 0.003763, 0.003763
67
+ 65, 0.40467, 0.55856, 1.0101, 0.7859, 0.74682, 0.82066, 0.74715, 0.45189, 0.76275, 0.96815, 0.003664, 0.003664, 0.003664
68
+ 66, 0.4053, 0.55397, 1.0128, 0.78668, 0.74277, 0.82081, 0.74629, 0.45561, 0.7708, 0.97299, 0.003565, 0.003565, 0.003565
69
+ 67, 0.40242, 0.55117, 1.0097, 0.79413, 0.73328, 0.81916, 0.74524, 0.45026, 0.77149, 0.96875, 0.003466, 0.003466, 0.003466
70
+ 68, 0.40207, 0.5483, 1.0085, 0.79173, 0.74399, 0.81907, 0.74617, 0.45031, 0.77198, 0.96913, 0.003367, 0.003367, 0.003367
71
+ 69, 0.39395, 0.53267, 1.004, 0.77023, 0.75508, 0.8194, 0.7451, 0.45243, 0.77202, 0.9733, 0.003268, 0.003268, 0.003268
72
+ 70, 0.39687, 0.53746, 1.0064, 0.77414, 0.75501, 0.81892, 0.74515, 0.44935, 0.77186, 0.97201, 0.003169, 0.003169, 0.003169
73
+ 71, 0.39185, 0.52719, 1.0012, 0.77443, 0.75681, 0.81913, 0.74563, 0.44928, 0.77495, 0.97057, 0.00307, 0.00307, 0.00307
74
+ 72, 0.38796, 0.52214, 0.99733, 0.77661, 0.74344, 0.81836, 0.74572, 0.44584, 0.7764, 0.9666, 0.002971, 0.002971, 0.002971
75
+ 73, 0.38297, 0.51612, 0.99693, 0.7552, 0.76581, 0.81871, 0.74576, 0.44416, 0.78179, 0.96556, 0.002872, 0.002872, 0.002872
76
+ 74, 0.38328, 0.50984, 0.99605, 0.79051, 0.73261, 0.81721, 0.74504, 0.44264, 0.78403, 0.96387, 0.002773, 0.002773, 0.002773
77
+ 75, 0.38065, 0.51312, 0.99488, 0.76253, 0.7631, 0.81701, 0.74555, 0.44333, 0.783, 0.96519, 0.002674, 0.002674, 0.002674
78
+ 76, 0.38023, 0.50148, 0.99617, 0.77275, 0.75688, 0.81679, 0.7457, 0.441, 0.78371, 0.9636, 0.002575, 0.002575, 0.002575
79
+ 77, 0.37829, 0.49838, 0.9913, 0.79776, 0.73149, 0.81595, 0.74639, 0.44016, 0.78821, 0.96275, 0.002476, 0.002476, 0.002476
80
+ 78, 0.37453, 0.49757, 0.99186, 0.77537, 0.75092, 0.81557, 0.74527, 0.44111, 0.79119, 0.96226, 0.002377, 0.002377, 0.002377
81
+ 79, 0.37079, 0.48205, 0.98839, 0.76906, 0.75743, 0.81612, 0.74545, 0.44259, 0.79501, 0.9634, 0.002278, 0.002278, 0.002278
82
+ 80, 0.37143, 0.48187, 0.98822, 0.78819, 0.74159, 0.81663, 0.74554, 0.44308, 0.79266, 0.96585, 0.002179, 0.002179, 0.002179
83
+ 81, 0.36892, 0.4794, 0.98876, 0.78833, 0.74047, 0.81602, 0.74498, 0.44235, 0.79738, 0.96498, 0.00208, 0.00208, 0.00208
84
+ 82, 0.36541, 0.47264, 0.98351, 0.79396, 0.73312, 0.8164, 0.74664, 0.44347, 0.79966, 0.96515, 0.001981, 0.001981, 0.001981
85
+ 83, 0.36774, 0.46847, 0.98382, 0.78638, 0.73818, 0.81517, 0.74568, 0.4439, 0.80116, 0.96535, 0.001882, 0.001882, 0.001882
86
+ 84, 0.3591, 0.4644, 0.98343, 0.77295, 0.75054, 0.81422, 0.74395, 0.44454, 0.80546, 0.96644, 0.001783, 0.001783, 0.001783
87
+ 85, 0.36028, 0.46109, 0.97996, 0.77396, 0.75068, 0.81328, 0.74355, 0.44463, 0.80783, 0.96812, 0.001684, 0.001684, 0.001684
88
+ 86, 0.35766, 0.45343, 0.98284, 0.78921, 0.73307, 0.81284, 0.74365, 0.44547, 0.8121, 0.96923, 0.001585, 0.001585, 0.001585
89
+ 87, 0.35524, 0.44931, 0.97617, 0.78532, 0.73619, 0.81153, 0.74282, 0.44422, 0.81386, 0.96769, 0.001486, 0.001486, 0.001486
90
+ 88, 0.35573, 0.44626, 0.97833, 0.77879, 0.741, 0.80973, 0.74162, 0.44378, 0.81729, 0.96786, 0.001387, 0.001387, 0.001387
91
+ 89, 0.3503, 0.44128, 0.9786, 0.78494, 0.73525, 0.80859, 0.73966, 0.44454, 0.81999, 0.96867, 0.001288, 0.001288, 0.001288
92
+ 90, 0.34999, 0.43556, 0.97193, 0.78556, 0.73314, 0.80753, 0.73889, 0.44491, 0.82273, 0.96958, 0.001189, 0.001189, 0.001189
93
+ 91, 0.35123, 0.43429, 0.97559, 0.76831, 0.74664, 0.80789, 0.73883, 0.44555, 0.82807, 0.97053, 0.00109, 0.00109, 0.00109
94
+ 92, 0.34565, 0.42851, 0.9725, 0.76148, 0.75474, 0.80793, 0.73904, 0.44619, 0.83054, 0.97136, 0.000991, 0.000991, 0.000991
95
+ 93, 0.34204, 0.42083, 0.96888, 0.76572, 0.7509, 0.80735, 0.73824, 0.44655, 0.83476, 0.97294, 0.000892, 0.000892, 0.000892
96
+ 94, 0.34172, 0.42041, 0.96882, 0.77525, 0.74165, 0.80574, 0.73689, 0.44708, 0.83761, 0.97426, 0.000793, 0.000793, 0.000793
97
+ 95, 0.33895, 0.41637, 0.97023, 0.7831, 0.73596, 0.80532, 0.73672, 0.44642, 0.84236, 0.97449, 0.000694, 0.000694, 0.000694
98
+ 96, 0.33931, 0.41337, 0.96674, 0.78538, 0.73319, 0.80465, 0.73684, 0.44708, 0.84459, 0.97555, 0.000595, 0.000595, 0.000595
99
+ 97, 0.33407, 0.41116, 0.96683, 0.79202, 0.72903, 0.80424, 0.73661, 0.44746, 0.84773, 0.9763, 0.000496, 0.000496, 0.000496
100
+ 98, 0.33734, 0.40675, 0.96734, 0.79787, 0.72623, 0.80381, 0.73574, 0.44794, 0.85008, 0.97718, 0.000397, 0.000397, 0.000397
101
+ 99, 0.33692, 0.40994, 0.96826, 0.79949, 0.72651, 0.8035, 0.73513, 0.44795, 0.85233, 0.97768, 0.000298, 0.000298, 0.000298
runs/biolit_v2_bootstrap/results.png ADDED

Git LFS Details

  • SHA256: c8a16e4649ef4f3bc687e86f236f70dc3c16ed0fd5183efdea7e421f337e8a11
  • Pointer size: 131 Bytes
  • Size of remote file: 227 kB
runs/biolit_v2_bootstrap/train_batch0.jpg ADDED

Git LFS Details

  • SHA256: 00f648ba586ab5b2ebc6ad73442f80b26e137f6c7bdd8f7289e26e40bce862a6
  • Pointer size: 131 Bytes
  • Size of remote file: 726 kB
runs/biolit_v2_bootstrap/train_batch1.jpg ADDED

Git LFS Details

  • SHA256: cf7b1fddf7e4b9d957c34741703afb9e857cc8fc9a2d856267e54b4cd2ab9402
  • Pointer size: 131 Bytes
  • Size of remote file: 684 kB
runs/biolit_v2_bootstrap/train_batch2.jpg ADDED

Git LFS Details

  • SHA256: c4caf6fa015e0e369bc088f624f342f8a3151493d7fe9cebab4ef945bbe01427
  • Pointer size: 131 Bytes
  • Size of remote file: 672 kB
runs/biolit_v2_bootstrap/val_batch0_labels.jpg ADDED

Git LFS Details

  • SHA256: 80750bbcf658ae9d44613d1127a1a9807bbbaab4e783ffd9b27518ab2a0e05ed
  • Pointer size: 131 Bytes
  • Size of remote file: 411 kB
runs/biolit_v2_bootstrap/val_batch0_pred.jpg ADDED

Git LFS Details

  • SHA256: 9faf9b4949e2a7e73d8a6acc834a395b595bd421bda4960a9f0c5d17f6e56f1a
  • Pointer size: 131 Bytes
  • Size of remote file: 415 kB
runs/biolit_v2_bootstrap/val_batch1_labels.jpg ADDED

Git LFS Details

  • SHA256: a6f3e20f810930cd3ac50005fdac53af41602cec52351c9ca3da1bb93f654b76
  • Pointer size: 131 Bytes
  • Size of remote file: 493 kB
runs/biolit_v2_bootstrap/val_batch1_pred.jpg ADDED

Git LFS Details

  • SHA256: 10b67b36e9da46762328458c35bd6360dd47d09d3af82e6aab7df4bc16d66f01
  • Pointer size: 131 Bytes
  • Size of remote file: 507 kB
runs/biolit_v2_bootstrap/val_batch2_labels.jpg ADDED

Git LFS Details

  • SHA256: 6c74700eba4ffff7e93b9dc3b4e1c5a9308c89a25ad94132925241d8e914bc43
  • Pointer size: 131 Bytes
  • Size of remote file: 548 kB
runs/biolit_v2_bootstrap/val_batch2_pred.jpg ADDED

Git LFS Details

  • SHA256: de382e4fb03cd17d12c2cbf64e2b8d45853c1091dbca6f7acf9d0211063524a1
  • Pointer size: 131 Bytes
  • Size of remote file: 555 kB
runs/biolit_v2_bootstrap/weights/best.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b45bc1c51374def9ea1386b7dec96876eb7fb3f1d611ba9a061199ecdeab6973
3
+ size 22486698
runs/biolit_v2_bootstrap/weights/last.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:511d6f68b04dad0d46936370c877fa5fee9bb241d686cf00eacee8d4970d98f1
3
+ size 22486698
runs/biolit_v2_yolo_finetuned/best.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0eca96e96cfb9c7bba7cf04efd17ff57f536d3b9c06a7b923b0e0fce3302da19
3
+ size 6230634
runs/biolit_v2_yolo_finetuned/metrics_post_training.png ADDED
runs/biolit_v2_yolo_finetuned/results.csv ADDED
@@ -0,0 +1,51 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ epoch,time,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
2
+ 1,521.282,1.3882,2.61451,1.60066,0.38792,0.2738,0.27989,0.12367,1.69797,3.17184,1.97201,0.000550615,0.000550615,0.000550615
3
+ 2,1143.85,1.56598,2.41898,1.74072,0.15803,0.49031,0.1596,0.06356,1.85252,6.74716,2.44194,0.00108438,0.00108438,0.00108438
4
+ 3,1576.87,1.64339,2.39437,1.79389,0.24686,0.17656,0.18194,0.08356,2.0505,4.41326,2.2888,0.00159614,0.00159614,0.00159614
5
+ 4,1958.91,1.65425,2.32951,1.80519,0.30744,0.31135,0.2242,0.10617,2.01844,3.45056,2.2347,0.00156798,0.00156798,0.00156798
6
+ 5,2356.43,1.63454,2.21891,1.76835,0.54068,0.40364,0.36013,0.15283,1.97681,2.45012,2.17238,0.00153497,0.00153497,0.00153497
7
+ 6,2743.79,1.61388,2.20282,1.76481,0.30315,0.40547,0.24664,0.11937,1.85147,2.82066,2.13852,0.00150197,0.00150197,0.00150197
8
+ 7,3126.1,1.58472,2.09453,1.76508,0.47175,0.47423,0.4588,0.22481,1.93177,2.18942,2.09189,0.00146896,0.00146896,0.00146896
9
+ 8,3513.82,1.53112,2.00346,1.7024,0.44661,0.42832,0.32876,0.15747,1.78789,2.43981,1.99916,0.00143595,0.00143595,0.00143595
10
+ 9,3899.54,1.48255,1.95877,1.67542,0.52082,0.43067,0.41554,0.21195,1.7908,2.62569,2.0002,0.00140295,0.00140295,0.00140295
11
+ 10,4284.43,1.50845,1.95963,1.7,0.54024,0.40621,0.39643,0.21643,1.66215,2.15989,1.87199,0.00136994,0.00136994,0.00136994
12
+ 11,4671.06,1.4499,1.84304,1.6424,0.47941,0.52329,0.48523,0.27526,1.6212,2.05144,1.86962,0.00133693,0.00133693,0.00133693
13
+ 12,5085.69,1.43417,1.86236,1.63258,0.53733,0.3443,0.39553,0.2017,1.6536,2.00006,1.81665,0.00130393,0.00130393,0.00130393
14
+ 13,5471.09,1.40499,1.80905,1.61507,0.58644,0.50382,0.50767,0.27684,1.70129,2.00281,1.96205,0.00127092,0.00127092,0.00127092
15
+ 14,5864.49,1.40736,1.78444,1.60286,0.51281,0.51511,0.42286,0.23187,1.66543,2.04316,1.8554,0.00123791,0.00123791,0.00123791
16
+ 15,6260.03,1.38504,1.76676,1.58305,0.45956,0.52106,0.45466,0.25141,1.61158,1.87872,1.82649,0.00120491,0.00120491,0.00120491
17
+ 16,6643.84,1.37646,1.71172,1.57416,0.5111,0.36604,0.44906,0.24761,1.58007,2.00147,1.79996,0.0011719,0.0011719,0.0011719
18
+ 17,7029.22,1.35529,1.68447,1.57008,0.60195,0.43625,0.45598,0.24356,1.65313,1.9458,1.87572,0.00113889,0.00113889,0.00113889
19
+ 18,7412.62,1.33657,1.66783,1.55775,0.56861,0.59636,0.54977,0.32077,1.56377,1.72188,1.79038,0.00110589,0.00110589,0.00110589
20
+ 19,7811.98,1.33312,1.61587,1.53189,0.48104,0.52971,0.51783,0.28973,1.59215,1.85802,1.75274,0.00107288,0.00107288,0.00107288
21
+ 20,8200.16,1.30921,1.60062,1.53527,0.56081,0.4895,0.51255,0.30336,1.46256,1.95143,1.70692,0.00103987,0.00103987,0.00103987
22
+ 21,8586.76,1.28379,1.55502,1.51947,0.56952,0.57697,0.51217,0.31536,1.4928,1.84221,1.78402,0.00100687,0.00100687,0.00100687
23
+ 22,8972.82,1.26286,1.52704,1.50009,0.47747,0.51763,0.4396,0.25048,1.52184,1.86488,1.76089,0.000973861,0.000973861,0.000973861
24
+ 23,9364.77,1.26892,1.48438,1.4958,0.59427,0.54994,0.51833,0.31732,1.45539,1.7582,1.71347,0.000940855,0.000940855,0.000940855
25
+ 24,9758.18,1.24834,1.44429,1.45739,0.59211,0.63954,0.52384,0.29441,1.40256,1.62111,1.61941,0.000907848,0.000907848,0.000907848
26
+ 25,10171.6,1.20315,1.41054,1.45036,0.52444,0.6369,0.53331,0.31789,1.43947,1.54928,1.69335,0.000874842,0.000874842,0.000874842
27
+ 26,10564,1.1981,1.39891,1.44067,0.52873,0.53114,0.46431,0.27294,1.43294,1.66025,1.64787,0.000841835,0.000841835,0.000841835
28
+ 27,10953,1.21827,1.3757,1.44233,0.65126,0.54655,0.54029,0.35046,1.46965,1.69511,1.70905,0.000808828,0.000808828,0.000808828
29
+ 28,11345.9,1.19667,1.35084,1.41903,0.54308,0.52133,0.48137,0.26992,1.43459,1.83918,1.66558,0.000775822,0.000775822,0.000775822
30
+ 29,11734.1,1.1898,1.30497,1.42013,0.48071,0.6369,0.48155,0.29366,1.46459,1.78199,1.66962,0.000742815,0.000742815,0.000742815
31
+ 30,12125.7,1.15579,1.26906,1.39597,0.60356,0.50687,0.49623,0.30241,1.40658,1.58813,1.64281,0.000709809,0.000709809,0.000709809
32
+ 31,13264.6,1.15109,1.24517,1.40212,0.55674,0.52497,0.4548,0.2594,1.48197,1.72895,1.65709,0.000676802,0.000676802,0.000676802
33
+ 32,614.314,1.12761,1.21819,1.39122,0.55451,0.60987,0.53053,0.30203,1.5246,1.5084,1.69086,0.000643795,0.000643795,0.000643795
34
+ 33,1329.03,1.11712,1.2042,1.36965,0.48575,0.57854,0.49757,0.32307,1.35707,1.56997,1.5953,0.000610789,0.000610789,0.000610789
35
+ 34,1919.4,1.11409,1.19796,1.36614,0.48285,0.599,0.50056,0.31405,1.43666,1.75855,1.70859,0.000577782,0.000577782,0.000577782
36
+ 35,2498.08,1.09915,1.19114,1.35092,0.58985,0.5969,0.53905,0.3453,1.42465,1.44853,1.69148,0.000544776,0.000544776,0.000544776
37
+ 36,3970.25,1.08366,1.14863,1.35715,0.64974,0.52291,0.53043,0.32154,1.41337,1.57207,1.64562,0.000511769,0.000511769,0.000511769
38
+ 37,811.596,0.98639,1.01596,1.29307,0.6419,0.49882,0.52599,0.33001,1.34919,1.53477,1.56721,0.000478762,0.000478762,0.000478762
39
+ 38,1663.06,0.96334,0.96429,1.26425,0.53929,0.58549,0.54949,0.34241,1.38235,1.617,1.63464,0.000445756,0.000445756,0.000445756
40
+ 39,2255.59,0.95944,0.96151,1.26117,0.49807,0.51234,0.46765,0.28232,1.44337,1.9097,1.66744,0.000412749,0.000412749,0.000412749
41
+ 40,2842.16,0.9502,0.95933,1.25308,0.64047,0.58165,0.56764,0.34791,1.41698,1.53543,1.674,0.000379743,0.000379743,0.000379743
42
+ 41,3324.23,1.01986,0.88585,1.3355,0.5472,0.58813,0.52155,0.33191,1.43297,1.66424,1.66778,0.000346736,0.000346736,0.000346736
43
+ 42,3859.5,0.99371,0.82518,1.31128,0.55828,0.69607,0.58445,0.36548,1.33683,1.50723,1.64789,0.000313729,0.000313729,0.000313729
44
+ 43,4335.74,0.95681,0.77776,1.28878,0.68464,0.53114,0.55364,0.36969,1.35795,1.53945,1.66851,0.000280723,0.000280723,0.000280723
45
+ 44,4881.13,0.96347,0.76571,1.3105,0.69274,0.55817,0.58315,0.37954,1.29316,1.45137,1.56653,0.000247716,0.000247716,0.000247716
46
+ 45,5410.56,0.9164,0.71002,1.25019,0.57152,0.62603,0.54594,0.34206,1.34016,1.57588,1.62368,0.00021471,0.00021471,0.00021471
47
+ 46,5913.12,0.90566,0.70699,1.24842,0.66719,0.48611,0.53152,0.32975,1.35041,1.61484,1.61899,0.000181703,0.000181703,0.000181703
48
+ 47,6365.27,0.88505,0.67188,1.23375,0.62391,0.62283,0.57687,0.36766,1.33403,1.5254,1.58103,0.000148696,0.000148696,0.000148696
49
+ 48,6823.99,0.85638,0.644,1.21695,0.58375,0.64366,0.59527,0.37731,1.31391,1.48786,1.56287,0.00011569,0.00011569,0.00011569
50
+ 49,7291.68,0.85499,0.65254,1.21506,0.61533,0.64038,0.56217,0.35462,1.3757,1.50086,1.62576,8.26832e-05,8.26832e-05,8.26832e-05
51
+ 50,7747.19,0.84862,0.62872,1.20434,0.63715,0.63781,0.56902,0.36831,1.35436,1.50874,1.62288,4.96766e-05,4.96766e-05,4.96766e-05
runs/finetune-yolo-after-dyno-V2/best.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6c5b1d419ca6c00edba6ab06b21091eb7d7d9015c9314596469e209a9f82d156
3
+ size 22525418