Update run artifacts

DATA-606-2023-FALL-MONDAY · Dec 13, 2023 · 377df3e · 377df3e
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diff --git a/data/comb_full/data.yaml b/data/comb_full/data.yaml
@@ -0,0 +1,12 @@
+names:
+- surveillance
+nc: 1
+roboflow:
+  license: CC BY 4.0
+  project: cap-detect
+  url: https://universe.roboflow.com/seaberry/cap-detect/dataset/2
+  version: 2
+  workspace: seaberry
+test: test/images
+train: train/images
+val: valid/images
diff --git a/data/comb_full/train/labels.cache b/data/comb_full/train/labels.cache
diff --git a/data/comb_full/valid/labels.cache b/data/comb_full/valid/labels.cache
diff --git a/data/comb_tile/data.yaml b/data/comb_tile/data.yaml
@@ -0,0 +1,12 @@
+names:
+- surveillance
+nc: 1
+roboflow:
+  license: CC BY 4.0
+  project: cap-detect
+  url: https://universe.roboflow.com/seaberry/cap-detect/dataset/5
+  version: 5
+  workspace: seaberry
+test: test/images
+train: train/images
+val: valid/images
diff --git a/data/comb_tile/train/labels.cache b/data/comb_tile/train/labels.cache
diff --git a/data/comb_tile/valid/labels.cache b/data/comb_tile/valid/labels.cache
diff --git a/data/sv_full/data.yaml b/data/sv_full/data.yaml
@@ -0,0 +1,12 @@
+names:
+- surveillance
+nc: 1
+roboflow:
+  license: CC BY 4.0
+  project: cap-detect
+  url: https://universe.roboflow.com/seaberry/cap-detect/dataset/2
+  version: 2
+  workspace: seaberry
+test: test/images
+train: train/images
+val: valid/images
diff --git a/data/sv_tile/data.yaml b/data/sv_tile/data.yaml
@@ -0,0 +1,12 @@
+names:
+- surveillance
+nc: 1
+roboflow:
+  license: CC BY 4.0
+  project: cap-detect
+  url: https://universe.roboflow.com/seaberry/cap-detect/dataset/5
+  version: 5
+  workspace: seaberry
+test: test/images
+train: train/images
+val: valid/images
diff --git a/data/vis_full/data.yaml b/data/vis_full/data.yaml
@@ -0,0 +1,12 @@
+names:
+- surveillance
+nc: 1
+roboflow:
+  license: CC BY 4.0
+  project: vista-detect
+  url: https://universe.roboflow.com/seaberry/vista-detect/dataset/2
+  version: 2
+  workspace: seaberry
+test: test/images
+train: train/images
+val: valid/images
diff --git a/data/vis_tile/data.yaml b/data/vis_tile/data.yaml
@@ -0,0 +1,12 @@
+names:
+- surveillance
+nc: 1
+roboflow:
+  license: CC BY 4.0
+  project: vista-detect
+  url: https://universe.roboflow.com/seaberry/vista-detect/dataset/5
+  version: 5
+  workspace: seaberry
+test: test/images
+train: train/images
+val: valid/images
diff --git a/runs/detect/detr_full_frz_train/F1_curve.png b/runs/detect/detr_full_frz_train/F1_curve.png
diff --git a/runs/detect/detr_full_frz_train/PR_curve.png b/runs/detect/detr_full_frz_train/PR_curve.png
diff --git a/runs/detect/detr_full_frz_train/P_curve.png b/runs/detect/detr_full_frz_train/P_curve.png
diff --git a/runs/detect/detr_full_frz_train/R_curve.png b/runs/detect/detr_full_frz_train/R_curve.png
diff --git a/runs/detect/detr_full_frz_train/args.yaml b/runs/detect/detr_full_frz_train/args.yaml
@@ -4,7 +4,7 @@ model: rtdetr-l.pt
 data: /home/paperspace/seaberry_camille/data/comb_full/data.yaml
 epochs: 15
 patience: 10
-batch: 16
+batch: 8
 imgsz: 640
 save: true
 save_period: -1
@@ -22,9 +22,9 @@ deterministic: true
 single_cls: true
 rect: false
 cos_lr: true
-close_mosaic: 10
+close_mosaic: 5
 resume: false
-amp: false
+amp: true
 fraction: 1.0
 profile: false
 freeze: 20

diff --git a/runs/detect/detr_full_frz_train/confusion_matrix.png b/runs/detect/detr_full_frz_train/confusion_matrix.png
diff --git a/runs/detect/detr_full_frz_train/confusion_matrix_normalized.png b/runs/detect/detr_full_frz_train/confusion_matrix_normalized.png
diff --git a/runs/detect/detr_full_frz_train/labels.jpg b/runs/detect/detr_full_frz_train/labels.jpg
diff --git a/runs/detect/detr_full_frz_train/labels_correlogram.jpg b/runs/detect/detr_full_frz_train/labels_correlogram.jpg
diff --git a/runs/detect/detr_full_frz_train/results.csv b/runs/detect/detr_full_frz_train/results.csv
@@ -1,19 +1,16 @@
                   epoch,        train/giou_loss,         train/cls_loss,          train/l1_loss,   metrics/precision(B),      metrics/recall(B),       metrics/mAP50(B),    metrics/mAP50-95(B),          val/giou_loss,           val/cls_loss,            val/l1_loss,                 lr/pg0,                 lr/pg1,                 lr/pg2
-                      1,                 1.5252,                 2.1077,                0.27931,                0.28028,                0.25788,                0.16156,                0.04781,                 1.0619,                0.67032,                0.08668,             0.00066536,             0.00066536,             0.00066536
-                      2,                  1.189,                0.60268,                0.11722,                0.31501,                0.25169,                 0.1825,                 0.0576,                 1.0598,                0.60589,                0.08372,              0.0013176,              0.0013176,              0.0013176
-                      3,                 1.1436,                0.61239,                0.10992,                0.30345,                0.28247,                0.20174,                0.06077,                 1.0796,                0.60084,                0.09173,              0.0019132,              0.0019132,              0.0019132
-                      1,                 1.5376,                  2.173,                0.28615,                0.26096,                0.24212,                0.13966,                 0.0397,                 1.1137,                0.60966,                0.08871,             0.00066405,             0.00066405,             0.00066405
-                      2,                 1.1854,                0.59917,                0.12458,                0.33932,                0.28499,                0.21579,                0.07303,                 1.1011,                0.57787,                0.09251,              0.0013163,              0.0013163,              0.0013163
-                      3,                 1.1554,                0.60074,                0.11196,                0.31951,                0.25536,                0.19722,                0.05823,                 1.0686,                0.60885,                0.07846,              0.0019119,              0.0019119,              0.0019119
-                      4,                 1.1084,                0.60979,                0.09854,                0.38838,                0.29571,                0.24196,                0.08333,                 1.0561,                0.58297,                0.07875,              0.0018109,              0.0018109,              0.0018109
-                      5,                 1.1183,                0.62616,                0.09628,                0.40622,                0.31841,                0.26631,                 0.0917,                 1.0232,                0.61153,                  0.071,              0.0018109,              0.0018109,              0.0018109
-                      6,                 1.0144,                0.63989,                0.08461,                0.39042,                0.29256,                0.25332,                0.08675,                 1.0391,                0.59961,                0.07478,              0.0016724,              0.0016724,              0.0016724
-                      7,                 1.0083,                0.62757,                0.08473,                0.39863,                0.33607,                0.26101,                0.08229,                   1.04,                0.57251,                0.07408,               0.001505,               0.001505,               0.001505
-                      8,                0.98833,                0.63032,                0.08061,                0.42105,                0.29823,                0.27106,                 0.0938,                 1.0441,                 0.5807,                  0.072,              0.0013159,              0.0013159,              0.0013159
-                      9,                0.98575,                0.62146,                0.08114,                0.43269,                0.32724,                0.29205,                0.09428,                 1.0326,                0.57703,                0.07636,              0.0011135,              0.0011135,              0.0011135
-                     10,                0.99625,                0.61288,                0.08306,                0.48729,                0.31221,                0.29567,                0.09158,                 1.0606,                0.53323,                0.08044,             0.00090652,             0.00090652,             0.00090652
-                     11,                0.96714,                0.59823,                0.07521,                0.48463,                0.33165,                0.31801,                0.11177,                 1.0214,                0.57038,                0.07499,             0.00070407,             0.00070407,             0.00070407
-                     12,                0.93984,                0.60349,                0.07269,                0.49017,                0.33922,                0.31834,                0.10584,                 1.0483,                0.55151,                0.07323,               0.000515,               0.000515,               0.000515
-                     13,                  0.937,                0.59766,                0.07231,                0.47433,                0.36444,                0.33084,                0.11614,                 1.0312,                0.54815,                0.07148,             0.00034756,             0.00034756,             0.00034756
-                     14,                0.92741,                0.59386,                 0.0708,                0.51156,                 0.3575,                0.35702,                0.12368,                 1.0245,                0.54594,                0.07229,             0.00020907,             0.00020907,             0.00020907
-                     15,                0.92719,                  0.589,                0.07014,                0.49943,                0.37579,                0.35581,                0.12544,                 1.0155,                0.55248,                0.07159,             0.00010559,             0.00010559,             0.00010559
+                      1,                 1.5497,                 2.2674,                0.28447,                0.24339,                0.22509,                0.13462,                0.03922,                 1.1242,                0.62227,                0.10143,             0.00066536,             0.00066536,             0.00066536
+                      2,                 1.1803,                0.60481,                0.11765,                0.32704,                0.27049,                0.19714,                0.06209,                 1.0614,                0.60249,                0.08393,              0.0013176,              0.0013176,              0.0013176
+                      3,                   1.14,                0.61677,                0.11116,                0.33635,                0.27049,                0.21595,                0.06967,                 1.0293,                0.64317,                0.07703,              0.0019132,              0.0019132,              0.0019132
+                      4,                 1.1404,                0.60088,                0.10322,                0.34893,                0.28752,                0.22833,                0.07363,                  1.072,                0.57814,                0.08218,              0.0018109,              0.0018109,              0.0018109
+                      5,                 1.1194,                0.60135,                0.09949,                 0.3597,                0.28941,                0.22693,                0.06973,                 1.0799,                0.58191,                 0.0882,              0.0018109,              0.0018109,              0.0018109
+                      6,                 1.1082,                0.59931,                0.09781,                0.41637,                0.28815,                0.25351,                0.07136,                 1.0517,                0.57766,                0.07979,              0.0016724,              0.0016724,              0.0016724
+                      7,                 1.0907,                0.60556,                0.09507,                0.38273,                0.29634,                0.24896,                 0.0783,                 1.0606,                0.56403,                0.07779,               0.001505,               0.001505,               0.001505
+                      8,                 1.0736,                0.60437,                0.08787,                0.40881,                0.30454,                0.26645,                0.10237,                0.98352,                0.62085,                0.06834,              0.0013159,              0.0013159,              0.0013159
+                      9,                 1.0662,                0.60139,                0.08785,                0.44023,                 0.3124,                0.27003,                0.09425,                 1.0288,                0.57223,                0.07334,              0.0011135,              0.0011135,              0.0011135
+                     10,                 1.0418,                 0.6118,                0.08086,                0.46717,                0.32598,                0.29609,                0.09684,                 1.0305,                0.56291,                0.07175,             0.00090652,             0.00090652,             0.00090652
+                     11,                0.96927,                0.62946,                0.07411,                 0.4804,                0.30643,                 0.3055,                 0.1083,                0.99054,                0.58824,                0.07042,             0.00070407,             0.00070407,             0.00070407
+                     12,                0.95092,                 0.6289,                0.07061,                 0.4509,                0.32535,                0.30573,                 0.1088,                 0.9967,                0.57468,                0.06895,               0.000515,               0.000515,               0.000515
+                     13,                0.92896,                0.63624,                0.07293,                0.49009,                0.33607,                0.32666,                0.11176,                 0.9828,                0.57947,                0.06714,             0.00034756,             0.00034756,             0.00034756
+                     14,                0.92902,                 0.6223,                0.06689,                0.52218,                0.34237,                0.34553,                0.11931,                0.98539,                0.57472,                0.06631,             0.00020907,             0.00020907,             0.00020907
+                     15,                0.93361,                 0.6076,                0.06983,                0.51684,                0.34802,                0.34478,                0.12382,                0.97202,                0.57292,                0.06454,             0.00010559,             0.00010559,             0.00010559
diff --git a/runs/detect/detr_full_frz_train/results.png b/runs/detect/detr_full_frz_train/results.png
diff --git a/runs/detect/detr_full_frz_train/train_batch0.jpg b/runs/detect/detr_full_frz_train/train_batch0.jpg
diff --git a/runs/detect/detr_full_frz_train/train_batch1.jpg b/runs/detect/detr_full_frz_train/train_batch1.jpg
diff --git a/runs/detect/detr_full_frz_train/train_batch2.jpg b/runs/detect/detr_full_frz_train/train_batch2.jpg
diff --git a/runs/detect/detr_full_frz_train/train_batch5090.jpg b/runs/detect/detr_full_frz_train/train_batch5090.jpg
diff --git a/runs/detect/detr_full_frz_train/train_batch5091.jpg b/runs/detect/detr_full_frz_train/train_batch5091.jpg
diff --git a/runs/detect/detr_full_frz_train/train_batch5092.jpg b/runs/detect/detr_full_frz_train/train_batch5092.jpg
diff --git a/runs/detect/detr_full_frz_train/val_batch0_labels.jpg b/runs/detect/detr_full_frz_train/val_batch0_labels.jpg
diff --git a/runs/detect/detr_full_frz_train/val_batch0_pred.jpg b/runs/detect/detr_full_frz_train/val_batch0_pred.jpg
diff --git a/runs/detect/detr_full_frz_train/val_batch1_labels.jpg b/runs/detect/detr_full_frz_train/val_batch1_labels.jpg
diff --git a/runs/detect/detr_full_frz_train/val_batch1_pred.jpg b/runs/detect/detr_full_frz_train/val_batch1_pred.jpg
diff --git a/runs/detect/detr_full_frz_train/val_batch2_labels.jpg b/runs/detect/detr_full_frz_train/val_batch2_labels.jpg
diff --git a/runs/detect/detr_full_frz_train/val_batch2_pred.jpg b/runs/detect/detr_full_frz_train/val_batch2_pred.jpg
diff --git a/runs/detect/tune/best_hyperparameters.yaml b/runs/detect/tune/best_hyperparameters.yaml
@@ -1,29 +1,29 @@
-# 10/10 iterations complete ✅ (6026.62s)
+# 10/10 iterations complete ✅ (6161.49s)
 # Results saved to runs/detect/tune
-# Best fitness=0.21296 observed at iteration 13
-# Best fitness metrics are None
-# Best fitness model is None
+# Best fitness=0.04748 observed at iteration 9
+# Best fitness metrics are {'metrics/precision(B)': 0.28852, 'metrics/recall(B)': 0.17654, 'metrics/mAP50(B)': 0.12588, 'metrics/mAP50-95(B)': 0.03877, 'val/box_loss': 2.86873, 'val/cls_loss': 2.61389, 'val/dfl_loss': 1.80456, 'fitness': 0.04748}
+# Best fitness model is runs/detect/yolo_tile_transfer_tune
 # Best fitness hyperparameters are printed below.
 
-lr0: 0.00922
-lrf: 0.00476
-momentum: 0.76651
-weight_decay: 0.00033
-warmup_epochs: 3.07826
-warmup_momentum: 0.42203
-box: 7.68833
-cls: 0.85391
-dfl: 1.2677
-hsv_h: 0.01624
-hsv_s: 0.57581
-hsv_v: 0.52604
-degrees: 0.0
-translate: 0.10523
-scale: 0.50879
+lr0: 0.00754
+lrf: 0.00696
+momentum: 0.96521
+weight_decay: 0.00056
+warmup_epochs: 3.12176
+warmup_momentum: 0.81623
+box: 8.02944
+cls: 0.51959
+dfl: 2.24648
+hsv_h: 0.1
+hsv_s: 0.70333
+hsv_v: 0.363
+degrees: 15.0
+translate: 0.09045
+scale: 0.5842
 shear: 0.0
 perspective: 0.0
 flipud: 0.0
-fliplr: 0.46826
-mosaic: 0.85228
+fliplr: 0.5
+mosaic: 0.93019
 mixup: 0.0
 copy_paste: 0.0
diff --git a/runs/detect/tune/tune_fitness.png b/runs/detect/tune/tune_fitness.png