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google.colab import drive\n","drive.mount('/content/drive')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"RTYBak1-o6mZ","executionInfo":{"status":"ok","timestamp":1739454054965,"user_tz":-60,"elapsed":29363,"user":{"displayName":"Alex Formigaro","userId":"13897391550055686349"}},"outputId":"57490b9c-8048-47a0-8d0e-10597d170d6c"},"execution_count":1,"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive\n"]}]},{"cell_type":"code","source":["from ultralytics import YOLO\n","# Assuming 'yolov8n.pt' is the pre-trained model you want to use or the path to your custom model.\n","model = YOLO('yolov8n.pt') # Create a YOLO model instance\n","dataset_path = '/content/drive/MyDrive/ArtBingo/PaintingDataset'\n","model.train(data=f\"{dataset_path}/data.yaml\", epochs=300, imgsz=1024, lr0=0.0005)\n"],"metadata":{"id":"ylN8T-hdLx1-","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1739461724763,"user_tz":-60,"elapsed":4281746,"user":{"displayName":"Alex Formigaro","userId":"13897391550055686349"}},"outputId":"be048d3a-bf2e-45ec-851c-78f0fdb6c348"},"execution_count":4,"outputs":[{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["Downloading https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8n.pt to 'yolov8n.pt'...\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["100%|██████████| 6.25M/6.25M [00:00<00:00, 121MB/s]\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["Ultralytics 8.3.75 🚀 Python-3.11.11 torch-2.5.1+cu124 CUDA:0 (Tesla T4, 15095MiB)\n","\u001b[34m\u001b[1mengine/trainer: \u001b[0mtask=detect, mode=train, model=yolov8n.pt, data=/content/drive/MyDrive/ArtBingo/PaintingDataset/data.yaml, epochs=300, time=None, patience=100, batch=16, imgsz=1024, save=True, save_period=-1, cache=False, device=None, workers=8, project=None, name=train, exist_ok=False, pretrained=True, optimizer=auto, verbose=True, seed=0, deterministic=True, single_cls=False, rect=False, cos_lr=False, close_mosaic=10, resume=False, amp=True, fraction=1.0, profile=False, freeze=None, multi_scale=False, overlap_mask=True, mask_ratio=4, dropout=0.0, val=True, split=val, save_json=False, save_hybrid=False, conf=None, iou=0.7, max_det=300, half=False, dnn=False, plots=True, source=None, vid_stride=1, stream_buffer=False, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, embed=None, show=False, save_frames=False, save_txt=False, save_conf=False, save_crop=False, show_labels=True, show_conf=True, show_boxes=True, line_width=None, format=torchscript, keras=False, optimize=False, int8=False, dynamic=False, simplify=True, opset=None, workspace=None, nms=False, lr0=0.0005, lrf=0.01, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=7.5, cls=0.5, dfl=1.5, pose=12.0, kobj=1.0, nbs=64, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, bgr=0.0, mosaic=1.0, mixup=0.0, copy_paste=0.0, copy_paste_mode=flip, auto_augment=randaugment, erasing=0.4, crop_fraction=1.0, cfg=None, tracker=botsort.yaml, save_dir=runs/detect/train\n","Downloading https://ultralytics.com/assets/Arial.ttf to '/root/.config/Ultralytics/Arial.ttf'...\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["100%|██████████| 755k/755k [00:00<00:00, 21.4MB/s]\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["Overriding model.yaml nc=80 with nc=90\n","\n"," from n params module arguments \n"," 0 -1 1 464 ultralytics.nn.modules.conv.Conv [3, 16, 3, 2] \n"," 1 -1 1 4672 ultralytics.nn.modules.conv.Conv [16, 32, 3, 2] \n"," 2 -1 1 7360 ultralytics.nn.modules.block.C2f [32, 32, 1, True] \n"," 3 -1 1 18560 ultralytics.nn.modules.conv.Conv [32, 64, 3, 2] \n"," 4 -1 2 49664 ultralytics.nn.modules.block.C2f [64, 64, 2, True] \n"," 5 -1 1 73984 ultralytics.nn.modules.conv.Conv [64, 128, 3, 2] \n"," 6 -1 2 197632 ultralytics.nn.modules.block.C2f [128, 128, 2, True] \n"," 7 -1 1 295424 ultralytics.nn.modules.conv.Conv [128, 256, 3, 2] \n"," 8 -1 1 460288 ultralytics.nn.modules.block.C2f [256, 256, 1, True] \n"," 9 -1 1 164608 ultralytics.nn.modules.block.SPPF [256, 256, 5] \n"," 10 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest'] \n"," 11 [-1, 6] 1 0 ultralytics.nn.modules.conv.Concat [1] \n"," 12 -1 1 148224 ultralytics.nn.modules.block.C2f [384, 128, 1] \n"," 13 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest'] \n"," 14 [-1, 4] 1 0 ultralytics.nn.modules.conv.Concat [1] \n"," 15 -1 1 37248 ultralytics.nn.modules.block.C2f [192, 64, 1] \n"," 16 -1 1 36992 ultralytics.nn.modules.conv.Conv [64, 64, 3, 2] \n"," 17 [-1, 12] 1 0 ultralytics.nn.modules.conv.Concat [1] \n"," 18 -1 1 123648 ultralytics.nn.modules.block.C2f [192, 128, 1] \n"," 19 -1 1 147712 ultralytics.nn.modules.conv.Conv [128, 128, 3, 2] \n"," 20 [-1, 9] 1 0 ultralytics.nn.modules.conv.Concat [1] \n"," 21 -1 1 493056 ultralytics.nn.modules.block.C2f [384, 256, 1] \n"," 22 [15, 18, 21] 1 989134 ultralytics.nn.modules.head.Detect [90, [64, 128, 256]] \n","Model summary: 225 layers, 3,248,670 parameters, 3,248,654 gradients, 9.3 GFLOPs\n","\n","Transferred 319/355 items from pretrained weights\n","\u001b[34m\u001b[1mTensorBoard: \u001b[0mStart with 'tensorboard --logdir runs/detect/train', view at http://localhost:6006/\n","Freezing layer 'model.22.dfl.conv.weight'\n","\u001b[34m\u001b[1mAMP: \u001b[0mrunning Automatic Mixed Precision (AMP) checks...\n","Downloading https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11n.pt to 'yolo11n.pt'...\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["100%|██████████| 5.35M/5.35M [00:00<00:00, 81.5MB/s]\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\u001b[34m\u001b[1mAMP: \u001b[0mchecks passed ✅\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\u001b[34m\u001b[1mtrain: \u001b[0mScanning /content/drive/MyDrive/ArtBingo/PaintingDataset/train/labels... 477 images, 3 backgrounds, 1 corrupt: 100%|██████████| 477/477 [02:59<00:00, 2.65it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\u001b[34m\u001b[1mtrain: \u001b[0mWARNING ⚠️ /content/drive/MyDrive/ArtBingo/PaintingDataset/train/images/PL1_37_86_Fnt_TR_T89II_jpg.rf.1c748ad95f4803618b2ae5a41179103d.jpg: ignoring corrupt image/label: non-normalized or out of bounds coordinates [ 1.0299]\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\u001b[34m\u001b[1mtrain: \u001b[0mNew cache created: /content/drive/MyDrive/ArtBingo/PaintingDataset/train/labels.cache\n","\u001b[34m\u001b[1malbumentations: \u001b[0mBlur(p=0.01, blur_limit=(3, 7)), MedianBlur(p=0.01, blur_limit=(3, 7)), ToGray(p=0.01, num_output_channels=3, method='weighted_average'), CLAHE(p=0.01, clip_limit=(1.0, 4.0), tile_grid_size=(8, 8))\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["/usr/local/lib/python3.11/dist-packages/albumentations/__init__.py:28: UserWarning: A new version of Albumentations is available: '2.0.4' (you have '2.0.3'). Upgrade using: pip install -U albumentations. To disable automatic update checks, set the environment variable NO_ALBUMENTATIONS_UPDATE to 1.\n"," check_for_updates()\n","\u001b[34m\u001b[1mval: \u001b[0mScanning /content/drive/MyDrive/ArtBingo/PaintingDataset/valid/labels... 46 images, 0 backgrounds, 0 corrupt: 100%|██████████| 46/46 [00:41<00:00, 1.12it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\u001b[34m\u001b[1mval: \u001b[0mNew cache created: /content/drive/MyDrive/ArtBingo/PaintingDataset/valid/labels.cache\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["Plotting labels to runs/detect/train/labels.jpg... \n","\u001b[34m\u001b[1moptimizer:\u001b[0m 'optimizer=auto' found, ignoring 'lr0=0.0005' and 'momentum=0.937' and determining best 'optimizer', 'lr0' and 'momentum' automatically... \n","\u001b[34m\u001b[1moptimizer:\u001b[0m AdamW(lr=0.000106, momentum=0.9) with parameter groups 57 weight(decay=0.0), 64 weight(decay=0.0005), 63 bias(decay=0.0)\n","\u001b[34m\u001b[1mTensorBoard: \u001b[0mmodel graph visualization added ✅\n","Image sizes 1024 train, 1024 val\n","Using 2 dataloader workers\n","Logging results to \u001b[1mruns/detect/train\u001b[0m\n","Starting training for 300 epochs...\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 1/300 10.3G 1.907 5.319 1.714 452 1024: 100%|██████████| 30/30 [00:40<00:00, 1.35s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.26it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0 0 0 0\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 2/300 8.54G 1.863 5.014 1.664 374 1024: 100%|██████████| 30/30 [00:37<00:00, 1.25s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:04<00:00, 2.34s/it]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.012 0.00204 0.00693 0.00333\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 3/300 8.88G 1.856 4.549 1.643 229 1024: 100%|██████████| 30/30 [00:37<00:00, 1.24s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.58it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.00648 0.0246 0.00998 0.0063\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 4/300 7.55G 1.842 4.098 1.61 327 1024: 100%|██████████| 30/30 [00:37<00:00, 1.26s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.67it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.0101 0.0632 0.0176 0.0102\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 5/300 9.06G 1.822 3.85 1.626 232 1024: 100%|██████████| 30/30 [00:38<00:00, 1.29s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.49it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.555 0.0244 0.02 0.00802\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 6/300 7.48G 1.783 3.621 1.611 328 1024: 100%|██████████| 30/30 [00:40<00:00, 1.36s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.53it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.591 0.0328 0.0363 0.0179\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 7/300 8.59G 1.804 3.474 1.593 240 1024: 100%|██████████| 30/30 [00:39<00:00, 1.31s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.45it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.676 0.0376 0.0484 0.026\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 8/300 8.89G 1.786 3.317 1.583 249 1024: 100%|██████████| 30/30 [00:37<00:00, 1.25s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.48it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.613 0.0517 0.0617 0.0313\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 9/300 8.63G 1.774 3.169 1.573 336 1024: 100%|██████████| 30/30 [00:37<00:00, 1.25s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.19it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.539 0.0676 0.0775 0.0423\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 10/300 9.72G 1.759 3.078 1.566 425 1024: 100%|██████████| 30/30 [00:36<00:00, 1.23s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.10it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.536 0.119 0.113 0.0664\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 11/300 9.05G 1.709 3.01 1.543 342 1024: 100%|██████████| 30/30 [00:37<00:00, 1.24s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.20it/s]\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.549 0.129 0.115 0.0731\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 12/300 9.62G 1.703 2.855 1.546 237 1024: 100%|██████████| 30/30 [00:40<00:00, 1.35s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.09it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.546 0.122 0.124 0.0776\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 13/300 8.31G 1.689 2.827 1.557 332 1024: 100%|██████████| 30/30 [00:36<00:00, 1.22s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.13it/s]\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.492 0.124 0.123 0.0765\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 14/300 9.42G 1.7 2.744 1.535 401 1024: 100%|██████████| 30/30 [00:37<00:00, 1.24s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.12it/s]\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.456 0.133 0.137 0.0859\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 15/300 8.77G 1.696 2.665 1.52 323 1024: 100%|██████████| 30/30 [00:38<00:00, 1.28s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.10it/s]\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.506 0.119 0.145 0.0908\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 16/300 7.03G 1.653 2.595 1.502 355 1024: 100%|██████████| 30/30 [00:36<00:00, 1.20s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.20it/s]\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.392 0.139 0.153 0.093\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 17/300 7.83G 1.648 2.541 1.491 202 1024: 100%|██████████| 30/30 [00:39<00:00, 1.31s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.22it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.443 0.122 0.156 0.0951\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 18/300 9.22G 1.644 2.479 1.489 354 1024: 100%|██████████| 30/30 [00:40<00:00, 1.34s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.51it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.41 0.149 0.158 0.0921\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 19/300 10G 1.625 2.429 1.485 486 1024: 100%|██████████| 30/30 [00:37<00:00, 1.24s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.42it/s]\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.369 0.172 0.159 0.0946\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 20/300 10.2G 1.634 2.391 1.48 269 1024: 100%|██████████| 30/30 [00:38<00:00, 1.29s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.52it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.401 0.166 0.151 0.0911\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 21/300 8.07G 1.604 2.389 1.475 416 1024: 100%|██████████| 30/30 [00:37<00:00, 1.27s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.53it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.406 0.161 0.143 0.0841\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 22/300 9.82G 1.614 2.293 1.449 277 1024: 100%|██████████| 30/30 [00:37<00:00, 1.26s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.39it/s]\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.555 0.134 0.145 0.0894\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 23/300 8.38G 1.594 2.304 1.462 285 1024: 100%|██████████| 30/30 [00:38<00:00, 1.27s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.17it/s]\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.424 0.144 0.149 0.0848\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 24/300 10.2G 1.631 2.267 1.473 257 1024: 100%|██████████| 30/30 [00:40<00:00, 1.35s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.70it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.424 0.152 0.152 0.0877\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 25/300 8.13G 1.589 2.229 1.443 353 1024: 100%|██████████| 30/30 [00:38<00:00, 1.27s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.54it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.502 0.142 0.156 0.0939\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 26/300 9.24G 1.569 2.124 1.424 411 1024: 100%|██████████| 30/30 [00:38<00:00, 1.30s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.56it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.482 0.141 0.146 0.0863\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 27/300 9.21G 1.542 2.122 1.427 344 1024: 100%|██████████| 30/30 [00:37<00:00, 1.24s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.57it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.495 0.152 0.148 0.089\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 28/300 10.1G 1.563 2.124 1.435 291 1024: 100%|██████████| 30/30 [00:38<00:00, 1.28s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.49it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.438 0.147 0.148 0.0888\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 29/300 9.15G 1.556 2.092 1.433 258 1024: 100%|██████████| 30/30 [00:38<00:00, 1.29s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.20it/s]\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.463 0.154 0.169 0.101\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 30/300 8.46G 1.512 2.026 1.414 404 1024: 100%|██████████| 30/30 [00:37<00:00, 1.25s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.56it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.497 0.152 0.167 0.0996\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 31/300 9.5G 1.546 2.053 1.43 398 1024: 100%|██████████| 30/30 [00:35<00:00, 1.20s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.55it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.487 0.142 0.162 0.0976\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances 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1.12it/s]\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.486 0.161 0.177 0.101\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 40/300 7.5G 1.443 1.826 1.374 300 1024: 100%|██████████| 30/30 [00:37<00:00, 1.25s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.26it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.536 0.152 0.174 0.0977\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 41/300 9.85G 1.429 1.779 1.357 361 1024: 100%|██████████| 30/30 [00:36<00:00, 1.22s/it]\n"," Class Images Instances Box(P R 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1.59it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.439 0.158 0.178 0.0999\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 47/300 8.56G 1.396 1.694 1.318 332 1024: 100%|██████████| 30/30 [00:37<00:00, 1.27s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.57it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.48 0.142 0.172 0.0982\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances 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cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 53/300 7.53G 1.354 1.587 1.294 239 1024: 100%|██████████| 30/30 [00:37<00:00, 1.24s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.55it/s]\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.498 0.168 0.19 0.102\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 54/300 9.07G 1.362 1.594 1.296 241 1024: 100%|██████████| 30/30 [00:38<00:00, 1.28s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.48it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.513 0.132 0.185 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1.47it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.466 0.149 0.17 0.103\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":[" 57/300 7.77G 1.362 1.548 1.287 244 1024: 100%|██████████| 30/30 [00:37<00:00, 1.26s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.65it/s]"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":[" all 46 1002 0.436 0.161 0.177 0.102\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances 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2/2 [00:01<00:00, 1.60it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.498 0.156 0.175 0.0985\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 106/300 9.88G 1.174 1.217 1.184 281 1024: 100%|██████████| 30/30 [00:38<00:00, 1.27s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.58it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.389 0.181 0.175 0.0982\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 107/300 7.8G 1.166 1.191 1.175 518 1024: 100%|██████████| 30/30 [00:37<00:00, 1.26s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 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0.104\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 110/300 7.25G 1.127 1.147 1.159 265 1024: 100%|██████████| 30/30 [00:38<00:00, 1.27s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.20it/s]\n"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.385 0.158 0.165 0.0915\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 111/300 8.95G 1.156 1.174 1.168 575 1024: 100%|██████████| 30/30 [00:36<00:00, 1.21s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.26it/s]\n"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.379 0.166 0.177 0.101\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances 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0.0997\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 117/300 8.13G 1.151 1.177 1.162 248 1024: 100%|██████████| 30/30 [00:36<00:00, 1.23s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.28it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.417 0.179 0.177 0.101\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 118/300 8.78G 1.127 1.136 1.155 242 1024: 100%|██████████| 30/30 [00:38<00:00, 1.28s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.18it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.429 0.171 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[00:01<00:00, 1.46it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.434 0.158 0.173 0.0991\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 140/300 10.2G 1.104 1.089 1.137 388 1024: 100%|██████████| 30/30 [00:38<00:00, 1.29s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.59it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.495 0.152 0.169 0.0973\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 141/300 9.16G 1.093 1.066 1.12 380 1024: 100%|██████████| 30/30 [00:38<00:00, 1.30s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.58it/s]\n"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.448 0.167 0.164 0.0937\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 142/300 7.7G 1.089 1.091 1.141 540 1024: 100%|██████████| 30/30 [00:39<00:00, 1.31s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.63it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.432 0.163 0.159 0.089\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 143/300 7.69G 1.088 1.065 1.13 349 1024: 100%|██████████| 30/30 [00:38<00:00, 1.28s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.73it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.412 0.163 0.154 0.0897\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 144/300 9.59G 1.076 1.039 1.117 310 1024: 100%|██████████| 30/30 [00:40<00:00, 1.33s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.15it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.416 0.167 0.171 0.0989\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 145/300 8.42G 1.096 1.07 1.119 275 1024: 100%|██████████| 30/30 [00:39<00:00, 1.32s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.08it/s]\n"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.491 0.161 0.171 0.0989\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 146/300 10.4G 1.069 1.051 1.118 324 1024: 100%|██████████| 30/30 [00:39<00:00, 1.31s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.58it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.426 0.164 0.173 0.0986\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 147/300 8.98G 1.05 1.045 1.111 360 1024: 100%|██████████| 30/30 [00:38<00:00, 1.27s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.64it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.407 0.174 0.173 0.101\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 148/300 8.48G 1.066 1.055 1.119 293 1024: 100%|██████████| 30/30 [00:38<00:00, 1.27s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.73it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.425 0.164 0.175 0.102\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 149/300 8.37G 1.07 1.053 1.115 512 1024: 100%|██████████| 30/30 [00:38<00:00, 1.27s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.54it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.424 0.166 0.181 0.103\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 150/300 8.99G 1.055 1.039 1.113 296 1024: 100%|██████████| 30/30 [00:38<00:00, 1.27s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.46it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.415 0.172 0.177 0.103\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 151/300 9.24G 1.084 1.053 1.122 368 1024: 100%|██████████| 30/30 [00:38<00:00, 1.27s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.58it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.421 0.175 0.176 0.102\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 152/300 9.8G 1.068 1.039 1.112 476 1024: 100%|██████████| 30/30 [00:38<00:00, 1.27s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.84it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.398 0.161 0.17 0.0995\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 153/300 8.18G 1.067 1.022 1.1 441 1024: 100%|██████████| 30/30 [00:37<00:00, 1.27s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.58it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.451 0.153 0.168 0.0979\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 154/300 7.56G 1.058 1.056 1.12 223 1024: 100%|██████████| 30/30 [00:38<00:00, 1.27s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.57it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.408 0.158 0.165 0.095\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 155/300 8.04G 1.06 1.027 1.114 483 1024: 100%|██████████| 30/30 [00:37<00:00, 1.26s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.47it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.412 0.171 0.175 0.0979\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 156/300 11.6G 1.083 1.035 1.105 395 1024: 100%|██████████| 30/30 [00:38<00:00, 1.27s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.73it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.495 0.155 0.17 0.0971\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 157/300 9.6G 1.07 1.043 1.111 360 1024: 100%|██████████| 30/30 [00:37<00:00, 1.24s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.61it/s]\n"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.478 0.158 0.174 0.1\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 158/300 8.89G 1.047 1.017 1.101 373 1024: 100%|██████████| 30/30 [00:36<00:00, 1.22s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.80it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.504 0.14 0.172 0.0995\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 159/300 9.7G 1.055 1.037 1.113 310 1024: 100%|██████████| 30/30 [00:37<00:00, 1.25s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.23it/s]\n"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.459 0.151 0.173 0.0985\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 160/300 8.91G 1.053 1.009 1.106 271 1024: 100%|██████████| 30/30 [00:38<00:00, 1.27s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.20it/s]\n"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.434 0.15 0.176 0.103\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 161/300 8.97G 1.041 1.017 1.109 300 1024: 100%|██████████| 30/30 [00:38<00:00, 1.27s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.23it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.45 0.167 0.177 0.102\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 162/300 7.58G 1.056 1.02 1.107 316 1024: 100%|██████████| 30/30 [00:38<00:00, 1.29s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.61it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.405 0.161 0.168 0.0947\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 163/300 7.46G 1.065 1.02 1.11 246 1024: 100%|██████████| 30/30 [00:37<00:00, 1.24s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.70it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.433 0.181 0.174 0.1\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n"]},{"output_type":"stream","name":"stderr","text":[" 164/300 7.48G 1.036 0.9982 1.103 317 1024: 100%|██████████| 30/30 [00:37<00:00, 1.25s/it]\n"," Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.71it/s]"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.414 0.168 0.174 0.0985\n"]},{"output_type":"stream","name":"stderr","text":["\n"]},{"output_type":"stream","name":"stdout","text":["\u001b[34m\u001b[1mEarlyStopping: \u001b[0mTraining stopped early as no improvement observed in last 100 epochs. Best results observed at epoch 64, best model saved as best.pt.\n","To update EarlyStopping(patience=100) pass a new patience value, i.e. `patience=300` or use `patience=0` to disable EarlyStopping.\n","\n","164 epochs completed in 1.920 hours.\n","Optimizer stripped from runs/detect/train/weights/last.pt, 6.8MB\n","Optimizer stripped from runs/detect/train/weights/best.pt, 6.8MB\n","\n","Validating runs/detect/train/weights/best.pt...\n","Ultralytics 8.3.75 🚀 Python-3.11.11 torch-2.5.1+cu124 CUDA:0 (Tesla T4, 15095MiB)\n","Model summary (fused): 168 layers, 3,243,314 parameters, 0 gradients, 9.2 GFLOPs\n"]},{"output_type":"stream","name":"stderr","text":[" Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 2/2 [00:01<00:00, 1.72it/s]\n"]},{"output_type":"stream","name":"stdout","text":[" all 46 1002 0.534 0.141 0.18 0.108\n"," Basket 1 1 0.636 1 0.995 0.796\n"," Bird 6 15 0.749 0.398 0.373 0.183\n"," Boat 8 34 0.169 0.0588 0.0795 0.0329\n"," Book 3 31 0.23 0.0297 0.0615 0.0259\n"," Bridge 2 2 0 0 0.00992 0.00397\n"," Candle 3 4 1 0 0 0\n"," Cat 2 4 1 0 0 0\n"," Chair 4 4 1 0 0.641 0.386\n"," Clock 1 1 0 0 0 0\n"," Cow 1 1 1 0 0 0\n"," Cup 2 2 0 0 0 0\n"," Deer 1 2 1 0 0 0\n"," Dog 6 7 0.891 0.571 0.602 0.408\n"," Fish 2 23 0 0 0 0\n"," Flag 2 6 0.745 0.49 0.551 0.211\n"," Flower 9 167 0.231 0.024 0.0709 0.0382\n"," Food 1 4 0.59 0.75 0.836 0.654\n"," Fruit 4 39 0.314 0.205 0.192 0.1\n"," Gate 1 1 0 0 0 0\n"," Glass 3 3 0.362 0.667 0.723 0.543\n"," Goat 2 2 1 0 0 0\n"," Hat 10 28 0.443 0.256 0.219 0.0836\n"," Horse 5 10 0.662 0.3 0.342 0.15\n"," House 1 2 1 0 0 0\n"," Leaf 8 66 1 0 0.0777 0.0503\n"," Painting 1 3 0.416 0.277 0.238 0.152\n"," Person 36 417 0.542 0.185 0.253 0.109\n"," Plants 15 36 0 0 0.0164 0.00604\n"," Pyramid 1 1 0 0 0 0\n"," Rope 1 1 1 0 0.0107 0.00107\n"," Seashell 1 1 0 0 0 0\n"," Sheep 1 1 0 0 0 0\n"," Ship 6 9 0.563 0.111 0.487 0.196\n"," Tree 17 44 0.444 0.227 0.278 0.117\n"," Vase 3 5 0 0 0.0391 0.0234\n"," Waterfall 2 5 1 0 0 0\n"," Wave 1 7 1 0 0 0\n"," Wheel 2 2 1 0 0 0\n"," Windmill 1 1 1 0 0 0\n"," Window 6 10 0.364 0.1 0.1 0.0432\n","Speed: 0.7ms preprocess, 6.3ms inference, 0.0ms loss, 1.9ms postprocess per image\n","Results saved to \u001b[1mruns/detect/train\u001b[0m\n"]},{"output_type":"execute_result","data":{"text/plain":["ultralytics.utils.metrics.DetMetrics object with attributes:\n","\n","ap_class_index: array([ 0, 3, 4, 5, 7, 11, 12, 14, 17, 20, 23, 24, 25, 31, 32, 33, 34, 37, 38, 39, 40, 41, 43, 44, 48, 52, 55, 56, 58, 61, 62, 63, 64, 78, 80, 83, 84, 85, 86, 87])\n","box: ultralytics.utils.metrics.Metric object\n","confusion_matrix: \n","curves: ['Precision-Recall(B)', 'F1-Confidence(B)', 'Precision-Confidence(B)', 'Recall-Confidence(B)']\n","curves_results: [[array([ 0, 0.001001, 0.002002, 0.003003, 0.004004, 0.005005, 0.006006, 0.007007, 0.008008, 0.009009, 0.01001, 0.011011, 0.012012, 0.013013, 0.014014, 0.015015, 0.016016, 0.017017, 0.018018, 0.019019, 0.02002, 0.021021, 0.022022, 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'Cross', 22: 'Crown', 23: 'Cup', 24: 'Deer', 25: 'Dog', 26: 'Donkey', 27: 'Drum', 28: 'Duck', 29: 'Fence', 30: 'Fire', 31: 'Fish', 32: 'Flag', 33: 'Flower', 34: 'Food', 35: 'Fox', 36: 'Frog', 37: 'Fruit', 38: 'Gate', 39: 'Glass', 40: 'Goat', 41: 'Hat', 42: 'Helmet', 43: 'Horse', 44: 'House', 45: 'Insect', 46: 'Ladder', 47: 'Lamp', 48: 'Leaf', 49: 'Lion', 50: 'Lizard', 51: 'Monkey', 52: 'Painting', 53: 'Pan', 54: 'Pencil', 55: 'Person', 56: 'Plants', 57: 'Plate', 58: 'Pyramid', 59: 'Rabbit', 60: 'River', 61: 'Rope', 62: 'Seashell', 63: 'Sheep', 64: 'Ship', 65: 'Shoe', 66: 'Skull', 67: 'Snail', 68: 'Snake', 69: 'Spider', 70: 'Spoon', 71: 'Squirrel', 72: 'Stairs', 73: 'Star', 74: 'Table', 75: 'Tiger', 76: 'Tower', 77: 'Train', 78: 'Tree', 79: 'Umbrella', 80: 'Vase', 81: 'Violin', 82: 'Water lily', 83: 'Waterfall', 84: 'Wave', 85: 'Wheel', 86: 'Windmill', 87: 'Window', 88: 'Worm', 89: 'flo9w'}\n","plot: True\n","results_dict: {'metrics/precision(B)': 0.5337822897775981, 'metrics/recall(B)': 0.1412446261654392, 'metrics/mAP50(B)': 0.17989382825410455, 'metrics/mAP50-95(B)': 0.10787051223391281, 'fitness': 0.11507284383593198}\n","save_dir: PosixPath('runs/detect/train')\n","speed: {'preprocess': 0.6687750869391691, 'inference': 6.25370849998628, 'loss': 0.0005922391249876691, 'postprocess': 1.873007260873356}\n","task: 'detect'"]},"metadata":{},"execution_count":4}]},{"cell_type":"code","execution_count":3,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"f2I-VMD0ndbM","executionInfo":{"status":"ok","timestamp":1739454494945,"user_tz":-60,"elapsed":101869,"user":{"displayName":"Alex Formigaro","userId":"13897391550055686349"}},"outputId":"5f6e3a7a-8718-4ad7-d40a-ab76a5ab81ec"},"outputs":[{"output_type":"stream","name":"stdout","text":["Collecting ultralytics\n"," Downloading ultralytics-8.3.75-py3-none-any.whl.metadata (35 kB)\n","Requirement already satisfied: numpy<=2.1.1,>=1.23.0 in /usr/local/lib/python3.11/dist-packages (from 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Found existing installation: nvidia-cufft-cu12 11.2.3.61\n"," Uninstalling nvidia-cufft-cu12-11.2.3.61:\n"," Successfully uninstalled nvidia-cufft-cu12-11.2.3.61\n"," Attempting uninstall: nvidia-cuda-runtime-cu12\n"," Found existing installation: nvidia-cuda-runtime-cu12 12.5.82\n"," Uninstalling nvidia-cuda-runtime-cu12-12.5.82:\n"," Successfully uninstalled nvidia-cuda-runtime-cu12-12.5.82\n"," Attempting uninstall: nvidia-cuda-nvrtc-cu12\n"," Found existing installation: nvidia-cuda-nvrtc-cu12 12.5.82\n"," Uninstalling nvidia-cuda-nvrtc-cu12-12.5.82:\n"," Successfully uninstalled nvidia-cuda-nvrtc-cu12-12.5.82\n"," Attempting uninstall: nvidia-cuda-cupti-cu12\n"," Found existing installation: nvidia-cuda-cupti-cu12 12.5.82\n"," Uninstalling nvidia-cuda-cupti-cu12-12.5.82:\n"," Successfully uninstalled nvidia-cuda-cupti-cu12-12.5.82\n"," Attempting uninstall: nvidia-cublas-cu12\n"," Found existing installation: nvidia-cublas-cu12 12.5.3.2\n"," Uninstalling nvidia-cublas-cu12-12.5.3.2:\n"," Successfully uninstalled nvidia-cublas-cu12-12.5.3.2\n"," Attempting uninstall: nvidia-cusparse-cu12\n"," Found existing installation: nvidia-cusparse-cu12 12.5.1.3\n"," Uninstalling nvidia-cusparse-cu12-12.5.1.3:\n"," Successfully uninstalled nvidia-cusparse-cu12-12.5.1.3\n"," Attempting uninstall: nvidia-cudnn-cu12\n"," Found existing installation: nvidia-cudnn-cu12 9.3.0.75\n"," Uninstalling nvidia-cudnn-cu12-9.3.0.75:\n"," Successfully uninstalled nvidia-cudnn-cu12-9.3.0.75\n"," Attempting uninstall: nvidia-cusolver-cu12\n"," Found existing installation: nvidia-cusolver-cu12 11.6.3.83\n"," Uninstalling nvidia-cusolver-cu12-11.6.3.83:\n"," Successfully uninstalled nvidia-cusolver-cu12-11.6.3.83\n","Successfully installed nvidia-cublas-cu12-12.4.5.8 nvidia-cuda-cupti-cu12-12.4.127 nvidia-cuda-nvrtc-cu12-12.4.127 nvidia-cuda-runtime-cu12-12.4.127 nvidia-cudnn-cu12-9.1.0.70 nvidia-cufft-cu12-11.2.1.3 nvidia-curand-cu12-10.3.5.147 nvidia-cusolver-cu12-11.6.1.9 nvidia-cusparse-cu12-12.3.1.170 nvidia-nvjitlink-cu12-12.4.127 ultralytics-8.3.75 ultralytics-thop-2.0.14\n","Creating new Ultralytics Settings v0.0.6 file ✅ \n","View Ultralytics Settings with 'yolo settings' or at '/root/.config/Ultralytics/settings.json'\n","Update Settings with 'yolo settings key=value', i.e. 'yolo settings runs_dir=path/to/dir'. For help see https://docs.ultralytics.com/quickstart/#ultralytics-settings.\n"]}],"source":["!pip install ultralytics\n","from ultralytics import YOLO"]},{"source":["import locale\n","def getpreferredencoding(do_setlocale = True):\n"," return \"UTF-8\"\n","locale.getpreferredencoding = getpreferredencoding\n","!pip install huggingface_hub"],"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ci6OzGpoB724","executionInfo":{"status":"ok","timestamp":1739462268328,"user_tz":-60,"elapsed":3039,"user":{"displayName":"Alex Formigaro","userId":"13897391550055686349"}},"outputId":"b07fb2aa-7858-4ad9-fbc5-bddfb959379f"},"execution_count":7,"outputs":[{"output_type":"stream","name":"stdout","text":["Requirement already satisfied: huggingface_hub in /usr/local/lib/python3.11/dist-packages (0.28.1)\n","Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (3.17.0)\n","Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (2024.10.0)\n","Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (24.2)\n","Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (6.0.2)\n","Requirement already satisfied: requests in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (2.32.3)\n","Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (4.67.1)\n","Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (4.12.2)\n","Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.11/dist-packages (from requests->huggingface_hub) (3.4.1)\n","Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.11/dist-packages (from requests->huggingface_hub) (3.10)\n","Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.11/dist-packages (from requests->huggingface_hub) (2.3.0)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.11/dist-packages (from requests->huggingface_hub) (2025.1.31)\n"]}]},{"cell_type":"code","source":["from huggingface_hub import notebook_login\n","notebook_login()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":17,"referenced_widgets":["fbd9ab13b8044b4f9a908b7da629bbcc","5dce0a93262e442fa7cbf674bd6d6374","30ef31d6346b474b915730c8b623a1c8","ecc28d24c29f4414a36d427355b16f96","4f986948f1bc46dfa8c7ddd118a332c5","d87c5de2a0e544fbbce8209cfb88ecc0","1d4d13ef223f46299dd2a6d8e47cffb4","0b480cd3a463474581cb2e4803b37c10","486f2502f86d4a119b77a95b2af50762","879461ed6587434ca066ee11188818b3","8c7973c09bdd4a91b6cb39fd571cc252","9d426c21bce8492ea243d9885d2a0cf5","02a48209311447bca4a58073017410f3","f290906e130e4650b8c63ed86a0df69f","d366c8a627294d2a989b24399a0788de","33653579edef40d7b6b26f1bdf276b3e","08e02191d83b40c1aee1692bc92a0b73","787d73d585f846e7a549bc2606263db6","7ff95c8d3f644b76865194666aa09524","50451b7099db49ab890ee98ddfa69ca4"]},"id":"oDHmjuJOCNuT","executionInfo":{"status":"ok","timestamp":1739462351397,"user_tz":-60,"elapsed":282,"user":{"displayName":"Alex Formigaro","userId":"13897391550055686349"}},"outputId":"b02fe51c-688c-4bc6-b576-1d718423972f"},"execution_count":8,"outputs":[{"output_type":"display_data","data":{"text/plain":["VBox(children=(HTML(value='
406\u001b[0;31m \u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mraise_for_status\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 407\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mHTTPError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.11/dist-packages/requests/models.py\u001b[0m in \u001b[0;36mraise_for_status\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1023\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mhttp_error_msg\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1024\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mHTTPError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhttp_error_msg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1025\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mHTTPError\u001b[0m: 404 Client Error: Not Found for url: https://huggingface.co/api/models/wh1tel1ne/object.detection_thesis/preupload/main","\nThe above exception was the direct cause of the following exception:\n","\u001b[0;31mRepositoryNotFoundError\u001b[0m Traceback (most recent call last)","\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mhuggingface_hub\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mHfApi\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0mapi\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mHfApi\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m api.upload_file(\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0mpath_or_fileobj\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"runs/detect/train/weights/best.pt\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mpath_in_repo\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"best.pt\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.11/dist-packages/huggingface_hub/utils/_validators.py\u001b[0m in \u001b[0;36m_inner_fn\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 112\u001b[0m \u001b[0mkwargs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msmoothly_deprecate_use_auth_token\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn_name\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhas_token\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mhas_token\u001b[0m\u001b[0;34m,\u001b[0m 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call the function normally\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1524\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1525\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1526\u001b[0m \u001b[0m_inner\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_future_compatible\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m \u001b[0;31m# type: ignore\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.11/dist-packages/huggingface_hub/hf_api.py\u001b[0m in \u001b[0;36mupload_file\u001b[0;34m(self, path_or_fileobj, path_in_repo, repo_id, token, repo_type, revision, commit_message, commit_description, create_pr, parent_commit, run_as_future)\u001b[0m\n\u001b[1;32m 4403\u001b[0m )\n\u001b[1;32m 4404\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4405\u001b[0;31m commit_info = self.create_commit(\n\u001b[0m\u001b[1;32m 4406\u001b[0m \u001b[0mrepo_id\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mrepo_id\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4407\u001b[0m \u001b[0mrepo_type\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mrepo_type\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.11/dist-packages/huggingface_hub/utils/_validators.py\u001b[0m in \u001b[0;36m_inner_fn\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 112\u001b[0m \u001b[0mkwargs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msmoothly_deprecate_use_auth_token\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn_name\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhas_token\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mhas_token\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 113\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 114\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 115\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 116\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0m_inner_fn\u001b[0m \u001b[0;31m# type: ignore\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.11/dist-packages/huggingface_hub/hf_api.py\u001b[0m in \u001b[0;36m_inner\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1522\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1523\u001b[0m \u001b[0;31m# Otherwise, call the function normally\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1524\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1525\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1526\u001b[0m \u001b[0m_inner\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_future_compatible\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m 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(Request ID: Root=1-67ae1978-2b09a0c83b724dc3373b40dc;2e958dc1-dd6e-4664-ae2d-74346bcd54a5)\n\nRepository Not Found for url: https://huggingface.co/api/models/wh1tel1ne/object.detection_thesis/preupload/main.\nPlease make sure you specified the correct `repo_id` and `repo_type`.\nIf you are trying to access a private or gated repo, make sure you are authenticated.\nNote: Creating a commit assumes that the repo already exists on the Huggingface Hub. Please use `create_repo` if it's not the case."]}]}]}