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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: <ultralytics.utils.metrics.ConfusionMatrix object at 0x7c137838ad10>\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, 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'Chicken', 16: 'Child', 17: 'Clock', 18: 'Coffin', 19: 'Coin', 20: 'Cow', 21: '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: 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\u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.1/21.1 MB\u001b[0m \u001b[31m95.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25hDownloading ultralytics_thop-2.0.14-py3-none-any.whl (26 kB)\n","Installing collected packages: nvidia-nvjitlink-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, ultralytics-thop, ultralytics\n"," Attempting uninstall: nvidia-nvjitlink-cu12\n"," Found existing installation: nvidia-nvjitlink-cu12 12.5.82\n"," Uninstalling nvidia-nvjitlink-cu12-12.5.82:\n"," Successfully uninstalled nvidia-nvjitlink-cu12-12.5.82\n"," Attempting uninstall: nvidia-curand-cu12\n"," Found existing installation: nvidia-curand-cu12 10.3.6.82\n"," Uninstalling nvidia-curand-cu12-10.3.6.82:\n"," Successfully uninstalled nvidia-curand-cu12-10.3.6.82\n"," Attempting uninstall: nvidia-cufft-cu12\n"," 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='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"fbd9ab13b8044b4f9a908b7da629bbcc"}},"metadata":{}}]},{"cell_type":"code","source":["from huggingface_hub import HfApi\n","api = HfApi()\n","api.upload_file(\n"," path_or_fileobj=\"runs/detect/train/weights/best.pt\",\n"," path_in_repo=\"best.pt\",\n"," repo_id=\"wh1tel1ne/object.detection_thesis\",\n"," repo_type=\"model\"\n",")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":642},"id":"5QZKW98wDCG0","executionInfo":{"status":"error","timestamp":1739463033779,"user_tz":-60,"elapsed":1915,"user":{"displayName":"Alex Formigaro","userId":"13897391550055686349"}},"outputId":"f95208ad-a238-47dd-973d-0d2af39c7d6f"},"execution_count":9,"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.11/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n","The secret `HF_TOKEN` does not exist in your Colab secrets.\n","To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n","You will be able to reuse this secret in all of your notebooks.\n","Please note that authentication is recommended but still optional to access public models or datasets.\n"," warnings.warn(\n"]},{"output_type":"error","ename":"RepositoryNotFoundError","evalue":"404 Client Error. (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.","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mHTTPError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/usr/local/lib/python3.11/dist-packages/huggingface_hub/utils/_http.py\u001b[0m in \u001b[0;36mhf_raise_for_status\u001b[0;34m(response, endpoint_name)\u001b[0m\n\u001b[1;32m 405\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 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<ipython-input-9-356bc379f3c6>\u001b[0m in \u001b[0;36m<cell line: 0>\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 \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 \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 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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."]}]}]} |