{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"gpuType":"T4","authorship_tag":"ABX9TyOqTMJhGRnsZgl98HTdqavR"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"},"accelerator":"GPU"},"cells":[{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"collapsed":true,"id":"1zLtNAkFWH5h","executionInfo":{"status":"ok","timestamp":1779607867883,"user_tz":-330,"elapsed":8708,"user":{"displayName":"Krishna Verma","userId":"18291293214161594665"}},"outputId":"50af70ad-a037-4516-f9e2-40fe6ecfa767"},"outputs":[{"output_type":"stream","name":"stdout","text":["Collecting ultralytics\n"," Downloading ultralytics-8.4.53-py3-none-any.whl.metadata (39 kB)\n","Requirement already satisfied: numpy>=1.23.0 in /usr/local/lib/python3.12/dist-packages (from ultralytics) (2.0.2)\n","Requirement already satisfied: matplotlib>=3.3.0 in /usr/local/lib/python3.12/dist-packages (from ultralytics) 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(5.9.5)\n","Requirement already satisfied: polars>=0.20.0 in /usr/local/lib/python3.12/dist-packages (from ultralytics) (1.35.2)\n","Collecting ultralytics-thop>=2.0.18 (from ultralytics)\n"," Downloading ultralytics_thop-2.0.19-py3-none-any.whl.metadata (14 kB)\n","Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.12/dist-packages (from matplotlib>=3.3.0->ultralytics) (1.3.3)\n","Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.12/dist-packages (from matplotlib>=3.3.0->ultralytics) (0.12.1)\n","Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.12/dist-packages (from matplotlib>=3.3.0->ultralytics) (4.62.1)\n","Requirement already satisfied: kiwisolver>=1.3.1 in /usr/local/lib/python3.12/dist-packages (from matplotlib>=3.3.0->ultralytics) (1.5.0)\n","Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.12/dist-packages (from matplotlib>=3.3.0->ultralytics) (26.1)\n","Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.12/dist-packages (from matplotlib>=3.3.0->ultralytics) (3.3.2)\n","Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.12/dist-packages (from matplotlib>=3.3.0->ultralytics) (2.9.0.post0)\n","Requirement already satisfied: polars-runtime-32==1.35.2 in /usr/local/lib/python3.12/dist-packages (from polars>=0.20.0->ultralytics) (1.35.2)\n","Requirement already satisfied: charset_normalizer<4,>=2 in /usr/local/lib/python3.12/dist-packages (from requests>=2.23.0->ultralytics) (3.4.7)\n","Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.12/dist-packages (from requests>=2.23.0->ultralytics) (3.13)\n","Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.12/dist-packages (from requests>=2.23.0->ultralytics) (2.5.0)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.12/dist-packages (from requests>=2.23.0->ultralytics) (2026.4.22)\n","Requirement already satisfied: filelock in /usr/local/lib/python3.12/dist-packages (from torch>=1.8.0->ultralytics) (3.29.0)\n","Requirement already satisfied: typing-extensions>=4.10.0 in /usr/local/lib/python3.12/dist-packages (from torch>=1.8.0->ultralytics) (4.15.0)\n","Requirement already satisfied: setuptools in /usr/local/lib/python3.12/dist-packages (from torch>=1.8.0->ultralytics) (75.2.0)\n","Requirement already satisfied: sympy>=1.13.3 in /usr/local/lib/python3.12/dist-packages (from torch>=1.8.0->ultralytics) (1.14.0)\n","Requirement already satisfied: networkx>=2.5.1 in /usr/local/lib/python3.12/dist-packages (from torch>=1.8.0->ultralytics) (3.6.1)\n","Requirement already satisfied: jinja2 in /usr/local/lib/python3.12/dist-packages (from torch>=1.8.0->ultralytics) (3.1.6)\n","Requirement already satisfied: fsspec>=0.8.5 in /usr/local/lib/python3.12/dist-packages (from torch>=1.8.0->ultralytics) (2025.3.0)\n","Requirement already satisfied: cuda-bindings==12.9.4 in 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(1.3.0)\n","Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.12/dist-packages (from jinja2->torch>=1.8.0->ultralytics) (3.0.3)\n","Downloading ultralytics-8.4.53-py3-none-any.whl (1.3 MB)\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m33.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25hDownloading ultralytics_thop-2.0.19-py3-none-any.whl (28 kB)\n","Installing collected packages: ultralytics-thop, ultralytics\n","Successfully installed ultralytics-8.4.53 ultralytics-thop-2.0.19\n"]}],"source":["!pip install ultralytics"]},{"cell_type":"code","source":["from google.colab import drive\n","drive.mount('/content/drive')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"collapsed":true,"id":"orkGEp3NXWEv","executionInfo":{"status":"ok","timestamp":1779607889684,"user_tz":-330,"elapsed":20055,"user":{"displayName":"Krishna Verma","userId":"18291293214161594665"}},"outputId":"10f5033d-46ff-45ba-c87f-353a7d65d640"},"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive\n"]}]},{"cell_type":"code","source":["!pip install roboflow"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"collapsed":true,"id":"D7eEjQYoWndf","executionInfo":{"status":"ok","timestamp":1779599201448,"user_tz":-330,"elapsed":4267,"user":{"displayName":"Krishna Verma","userId":"18291293214161594665"}},"outputId":"0faea83b-f74c-467f-a203-cbf11df91166"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Requirement already satisfied: roboflow in /usr/local/lib/python3.12/dist-packages (1.3.8)\n","Requirement already satisfied: certifi in /usr/local/lib/python3.12/dist-packages (from roboflow) (2026.4.22)\n","Requirement already satisfied: idna==3.7 in /usr/local/lib/python3.12/dist-packages (from roboflow) (3.7)\n","Requirement already satisfied: cycler in /usr/local/lib/python3.12/dist-packages (from roboflow) (0.12.1)\n","Requirement already satisfied: kiwisolver>=1.3.1 in /usr/local/lib/python3.12/dist-packages (from roboflow) (1.5.0)\n","Requirement already satisfied: matplotlib in /usr/local/lib/python3.12/dist-packages (from roboflow) (3.10.0)\n","Requirement already satisfied: numpy>=1.18.5 in /usr/local/lib/python3.12/dist-packages (from roboflow) (2.0.2)\n","Requirement already satisfied: opencv-python-headless==4.10.0.84 in /usr/local/lib/python3.12/dist-packages (from roboflow) (4.10.0.84)\n","Requirement already satisfied: Pillow>=7.1.2 in /usr/local/lib/python3.12/dist-packages (from roboflow) (11.3.0)\n","Requirement already satisfied: pi-heif<2 in /usr/local/lib/python3.12/dist-packages (from roboflow) (1.3.0)\n","Requirement already satisfied: pillow-avif-plugin<2 in /usr/local/lib/python3.12/dist-packages (from roboflow) (1.5.5)\n","Requirement already satisfied: python-dateutil in /usr/local/lib/python3.12/dist-packages (from roboflow) (2.9.0.post0)\n","Requirement already satisfied: python-dotenv in /usr/local/lib/python3.12/dist-packages (from roboflow) (1.2.2)\n","Requirement already satisfied: requests in /usr/local/lib/python3.12/dist-packages (from roboflow) (2.32.4)\n","Requirement already satisfied: six in /usr/local/lib/python3.12/dist-packages (from roboflow) (1.17.0)\n","Requirement already satisfied: urllib3>=1.26.6 in /usr/local/lib/python3.12/dist-packages (from roboflow) (2.5.0)\n","Requirement already satisfied: tqdm>=4.41.0 in /usr/local/lib/python3.12/dist-packages (from roboflow) (4.67.3)\n","Requirement already satisfied: PyYAML>=5.3.1 in /usr/local/lib/python3.12/dist-packages (from roboflow) (6.0.3)\n","Requirement already satisfied: requests_toolbelt in /usr/local/lib/python3.12/dist-packages (from roboflow) (1.0.0)\n","Requirement already satisfied: filetype in /usr/local/lib/python3.12/dist-packages (from roboflow) (1.2.0)\n","Requirement already satisfied: typer>=0.12.0 in /usr/local/lib/python3.12/dist-packages (from roboflow) (0.24.2)\n","Requirement already satisfied: click>=8.2.1 in /usr/local/lib/python3.12/dist-packages (from typer>=0.12.0->roboflow) (8.3.3)\n","Requirement already satisfied: shellingham>=1.3.0 in /usr/local/lib/python3.12/dist-packages (from typer>=0.12.0->roboflow) (1.5.4)\n","Requirement already satisfied: rich>=12.3.0 in /usr/local/lib/python3.12/dist-packages (from typer>=0.12.0->roboflow) (13.9.4)\n","Requirement already satisfied: annotated-doc>=0.0.2 in /usr/local/lib/python3.12/dist-packages (from typer>=0.12.0->roboflow) (0.0.4)\n","Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.12/dist-packages (from matplotlib->roboflow) (1.3.3)\n","Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.12/dist-packages (from matplotlib->roboflow) (4.62.1)\n","Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.12/dist-packages (from matplotlib->roboflow) (26.1)\n","Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.12/dist-packages (from matplotlib->roboflow) (3.3.2)\n","Requirement already satisfied: charset_normalizer<4,>=2 in /usr/local/lib/python3.12/dist-packages (from requests->roboflow) (3.4.7)\n","Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.12/dist-packages (from rich>=12.3.0->typer>=0.12.0->roboflow) (4.0.0)\n","Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.12/dist-packages (from rich>=12.3.0->typer>=0.12.0->roboflow) (2.20.0)\n","Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.12/dist-packages (from markdown-it-py>=2.2.0->rich>=12.3.0->typer>=0.12.0->roboflow) (0.1.2)\n"]}]},{"cell_type":"code","source":["\n","from roboflow import Roboflow\n","rf = Roboflow(api_key=\"0gwtO7p9PJa39qtM9vUX\")\n","project = rf.workspace(\"yolo-and-car-accident-detection-xaltb\").project(\"accident-detection-77mha\")\n","version = project.version(1)\n","dataset = version.download(\"yolov8\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"collapsed":true,"id":"d1fodX3RXhdW","executionInfo":{"status":"ok","timestamp":1779599217030,"user_tz":-330,"elapsed":5911,"user":{"displayName":"Krishna Verma","userId":"18291293214161594665"}},"outputId":"19e0cebe-cc46-41a4-e67a-65acfd3f0f7f"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["loading Roboflow workspace...\n","loading Roboflow project...\n"]},{"output_type":"stream","name":"stderr","text":["Downloading Dataset Version Zip in Accident-Detection-1 to yolov8:: 100%|██████████| 33017/33017 [00:01<00:00, 31662.42it/s]"]},{"output_type":"stream","name":"stdout","text":["\n"]},{"output_type":"stream","name":"stderr","text":["\n","Extracting Dataset Version Zip to Accident-Detection-1 in yolov8:: 100%|██████████| 1180/1180 [00:00<00:00, 8520.14it/s]\n"]}]},{"cell_type":"code","source":["from ultralytics import YOLO\n","import shutil, os"],"metadata":{"id":"pC2Ej9XnXitW"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["model = YOLO(\"yolov8n.pt\")"],"metadata":{"collapsed":true,"id":"DYcByqc8XoyQ"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["\n","results = model.train(\n"," data=dataset.location + \"/data.yaml\",\n"," epochs=150,\n"," imgsz=800,\n"," batch=8,\n"," workers=2,\n"," device=0,\n",")\n","\n","print(\"Model Trained\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"collapsed":true,"id":"VYbmtt3qX1DZ","executionInfo":{"status":"ok","timestamp":1779602654413,"user_tz":-330,"elapsed":1914768,"user":{"displayName":"Krishna Verma","userId":"18291293214161594665"}},"outputId":"c9b71d88-cdcd-46e8-c6f8-502ccd0d91b0"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Ultralytics 8.4.53 🚀 Python-3.12.13 torch-2.10.0+cu128 CUDA:0 (Tesla T4, 14913MiB)\n","\u001b[34m\u001b[1mengine/trainer: \u001b[0magnostic_nms=False, amp=True, angle=1.0, augment=False, auto_augment=randaugment, batch=8, bgr=0.0, box=7.5, cache=False, cfg=None, classes=None, close_mosaic=10, cls=0.5, cls_pw=0.0, compile=False, conf=None, copy_paste=0.0, copy_paste_mode=flip, cos_lr=False, cutmix=0.0, data=/content/Accident-Detection-1/data.yaml, degrees=0.0, deterministic=True, device=0, dfl=1.5, dnn=False, dropout=0.0, dynamic=False, embed=None, end2end=None, epochs=150, erasing=0.4, exist_ok=False, fliplr=0.5, flipud=0.0, format=torchscript, fraction=1.0, freeze=None, half=False, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=800, int8=False, iou=0.7, keras=False, kobj=1.0, line_width=None, lr0=0.01, lrf=0.01, mask_ratio=4, max_det=300, mixup=0.0, mode=train, model=yolov8n.pt, momentum=0.937, mosaic=1.0, multi_scale=0.0, name=train-3, nbs=64, nms=False, opset=None, optimize=False, optimizer=auto, overlap_mask=True, patience=100, perspective=0.0, plots=True, pose=12.0, pretrained=True, profile=False, project=None, rect=False, resume=False, retina_masks=False, rle=1.0, save=True, save_conf=False, save_crop=False, save_dir=/content/runs/detect/train-3, save_frames=False, save_json=False, save_period=-1, save_txt=False, scale=0.5, seed=0, shear=0.0, show=False, show_boxes=True, show_conf=True, show_labels=True, simplify=True, single_cls=False, source=None, split=val, stream_buffer=False, task=detect, time=None, tracker=botsort.yaml, translate=0.1, val=True, verbose=True, vid_stride=1, visualize=False, warmup_bias_lr=0.1, warmup_epochs=3.0, warmup_momentum=0.8, weight_decay=0.0005, workers=2, workspace=None\n","Overriding model.yaml nc=80 with nc=1\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 751507 ultralytics.nn.modules.head.Detect [1, 16, None, [64, 128, 256]] \n","Model summary: 130 layers, 3,011,043 parameters, 3,011,027 gradients, 8.2 GFLOPs\n","\n","Transferred 319/355 items from pretrained weights\n","Freezing layer 'model.22.dfl.conv.weight'\n","\u001b[34m\u001b[1mAMP: \u001b[0mrunning Automatic Mixed Precision (AMP) checks...\n","\u001b[34m\u001b[1mAMP: \u001b[0mchecks passed ✅\n","\u001b[34m\u001b[1mtrain: \u001b[0mFast image access ✅ (ping: 0.0±0.0 ms, read: 1734.3±306.5 MB/s, size: 60.7 KB)\n","\u001b[K\u001b[34m\u001b[1mtrain: \u001b[0mScanning /content/Accident-Detection-1/train/labels.cache... 376 images, 0 backgrounds, 0 corrupt: 100% ━━━━━━━━━━━━ 376/376 98.6Mit/s 0.0s\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, method='weighted_average', num_output_channels=3), CLAHE(p=0.01, clip_limit=(1.0, 4.0), tile_grid_size=(8, 8))\n","\u001b[34m\u001b[1mval: \u001b[0mFast image access ✅ (ping: 0.0±0.0 ms, read: 458.6±124.5 MB/s, size: 76.4 KB)\n","\u001b[K\u001b[34m\u001b[1mval: \u001b[0mScanning /content/Accident-Detection-1/valid/labels.cache... 78 images, 0 backgrounds, 0 corrupt: 100% ━━━━━━━━━━━━ 78/78 3.7Mit/s 0.0s\n","\u001b[34m\u001b[1moptimizer:\u001b[0m 'optimizer=auto' found, ignoring 'lr0=0.01' and 'momentum=0.937' and determining best 'optimizer', 'lr0' and 'momentum' automatically... \n","\u001b[34m\u001b[1moptimizer:\u001b[0m AdamW(lr=0.002, momentum=0.9) with parameter groups 57 weight(decay=0.0), 64 weight(decay=0.0005), 63 bias(decay=0.0)\n","Plotting labels to /content/runs/detect/train-3/labels.jpg... \n","Image sizes 800 train, 800 val\n","Using 2 dataloader workers\n","Logging results to \u001b[1m/content/runs/detect/train-3\u001b[0m\n","Starting training for 150 epochs...\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 1/150 1.67G 1.161 2.737 1.542 8 800: 100% ━━━━━━━━━━━━ 47/47 3.6it/s 13.0s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.6it/s 1.1s\n"," all 78 87 0.606 0.264 0.456 0.213\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 2/150 1.97G 1.33 2.488 1.672 8 800: 100% ━━━━━━━━━━━━ 47/47 4.4it/s 10.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 2.7it/s 1.8s\n"," all 78 87 0.364 0.287 0.238 0.0876\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 3/150 1.97G 1.334 2.422 1.629 8 800: 100% ━━━━━━━━━━━━ 47/47 4.7it/s 9.9s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.2it/s 1.5s\n"," all 78 87 0.256 0.379 0.211 0.101\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 4/150 1.97G 1.406 2.267 1.729 8 800: 100% ━━━━━━━━━━━━ 47/47 4.5it/s 10.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.8it/s 0.9s\n"," all 78 87 0.204 0.299 0.172 0.0609\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 5/150 1.97G 1.441 2.208 1.726 8 800: 100% ━━━━━━━━━━━━ 47/47 3.9it/s 12.0s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.4it/s 1.1s\n"," all 78 87 0.171 0.276 0.133 0.0489\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 6/150 1.97G 1.411 2.071 1.711 8 800: 100% ━━━━━━━━━━━━ 47/47 4.2it/s 11.3s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.6it/s 1.1s\n"," all 78 87 0.32 0.391 0.265 0.119\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 7/150 1.97G 1.377 1.965 1.696 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.1it/s 1.0s\n"," all 78 87 0.268 0.46 0.232 0.101\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 8/150 1.97G 1.339 1.794 1.654 8 800: 100% ━━━━━━━━━━━━ 47/47 4.5it/s 10.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.3it/s 1.5s\n"," all 78 87 0.406 0.425 0.359 0.177\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 9/150 1.97G 1.332 1.732 1.644 8 800: 100% ━━━━━━━━━━━━ 47/47 4.9it/s 9.6s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.8it/s 0.9s\n"," all 78 87 0.476 0.506 0.42 0.193\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 10/150 1.97G 1.338 1.798 1.674 8 800: 100% ━━━━━━━━━━━━ 47/47 4.2it/s 11.2s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.4it/s 0.9s\n"," all 78 87 0.44 0.391 0.377 0.194\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 11/150 1.97G 1.317 1.698 1.642 8 800: 100% ━━━━━━━━━━━━ 47/47 4.2it/s 11.3s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.1it/s 1.2s\n"," all 78 87 0.579 0.241 0.34 0.184\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 12/150 1.97G 1.283 1.684 1.623 8 800: 100% ━━━━━━━━━━━━ 47/47 4.3it/s 11.0s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.1it/s 1.2s\n"," all 78 87 0.43 0.416 0.403 0.214\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 13/150 1.97G 1.268 1.548 1.594 8 800: 100% ━━━━━━━━━━━━ 47/47 4.3it/s 10.8s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.1it/s 1.6s\n"," all 78 87 0.498 0.402 0.383 0.179\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 14/150 1.97G 1.296 1.601 1.629 8 800: 100% ━━━━━━━━━━━━ 47/47 5.0it/s 9.3s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.2it/s 1.6s\n"," all 78 87 0.439 0.471 0.419 0.212\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 15/150 1.97G 1.266 1.601 1.592 8 800: 100% ━━━━━━━━━━━━ 47/47 4.3it/s 10.9s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.3it/s 0.8s\n"," all 78 87 0.491 0.465 0.467 0.258\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 16/150 1.97G 1.266 1.477 1.611 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.3it/s 0.8s\n"," all 78 87 0.484 0.506 0.461 0.215\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 17/150 1.97G 1.229 1.453 1.545 8 800: 100% ━━━━━━━━━━━━ 47/47 4.2it/s 11.2s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.0it/s 1.2s\n"," all 78 87 0.597 0.528 0.546 0.289\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 18/150 1.97G 1.175 1.376 1.522 8 800: 100% ━━━━━━━━━━━━ 47/47 4.2it/s 11.2s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.0it/s 1.2s\n"," all 78 87 0.546 0.667 0.582 0.309\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 19/150 1.97G 1.206 1.393 1.517 8 800: 100% ━━━━━━━━━━━━ 47/47 4.6it/s 10.1s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.3it/s 1.5s\n"," all 78 87 0.561 0.454 0.466 0.249\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 20/150 1.97G 1.196 1.372 1.537 8 800: 100% ━━━━━━━━━━━━ 47/47 4.8it/s 9.9s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.7it/s 0.9s\n"," all 78 87 0.695 0.391 0.5 0.257\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 21/150 1.97G 1.152 1.301 1.502 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.9it/s 1.0s\n"," all 78 87 0.691 0.506 0.56 0.284\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 22/150 1.97G 1.14 1.267 1.505 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.6it/s 0.8s\n"," all 78 87 0.845 0.483 0.638 0.369\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 23/150 1.97G 1.104 1.244 1.448 8 800: 100% ━━━━━━━━━━━━ 47/47 4.2it/s 11.2s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.2it/s 1.2s\n"," all 78 87 0.699 0.428 0.502 0.29\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 24/150 1.97G 1.095 1.198 1.46 8 800: 100% ━━━━━━━━━━━━ 47/47 4.7it/s 10.0s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 2.5it/s 2.0s\n"," all 78 87 0.474 0.673 0.542 0.304\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 25/150 1.97G 1.117 1.204 1.46 8 800: 100% ━━━━━━━━━━━━ 47/47 5.0it/s 9.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.3it/s 1.1s\n"," all 78 87 0.607 0.587 0.591 0.312\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 26/150 1.97G 1.038 1.131 1.4 8 800: 100% ━━━━━━━━━━━━ 47/47 4.2it/s 11.2s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.2it/s 1.0s\n"," all 78 87 0.506 0.695 0.568 0.327\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 27/150 1.97G 1.083 1.211 1.449 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.5it/s 0.8s\n"," all 78 87 0.499 0.699 0.553 0.326\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 28/150 1.97G 1.046 1.22 1.433 8 800: 100% ━━━━━━━━━━━━ 47/47 4.2it/s 11.3s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.5it/s 1.1s\n"," all 78 87 0.509 0.563 0.527 0.314\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 29/150 1.97G 1.084 1.162 1.479 8 800: 100% ━━━━━━━━━━━━ 47/47 4.4it/s 10.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 2.6it/s 1.9s\n"," all 78 87 0.561 0.575 0.539 0.311\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 30/150 1.97G 1.046 1.156 1.403 8 800: 100% ━━━━━━━━━━━━ 47/47 4.8it/s 9.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.7it/s 1.3s\n"," all 78 87 0.613 0.598 0.603 0.326\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 31/150 1.97G 1 1.05 1.357 8 800: 100% ━━━━━━━━━━━━ 47/47 4.5it/s 10.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.9it/s 1.3s\n"," all 78 87 0.666 0.664 0.683 0.406\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 32/150 1.97G 1.071 1.118 1.437 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.8s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.9it/s 0.7s\n"," all 78 87 0.618 0.595 0.603 0.366\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 33/150 1.97G 1.03 1.113 1.363 8 800: 100% ━━━━━━━━━━━━ 47/47 4.2it/s 11.3s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.3it/s 1.2s\n"," all 78 87 0.652 0.621 0.647 0.359\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 34/150 1.97G 1.03 1.076 1.399 8 800: 100% ━━━━━━━━━━━━ 47/47 4.2it/s 11.1s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.0it/s 1.3s\n"," all 78 87 0.598 0.69 0.612 0.385\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 35/150 1.97G 1.061 1.059 1.443 8 800: 100% ━━━━━━━━━━━━ 47/47 4.6it/s 10.2s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.4it/s 1.5s\n"," all 78 87 0.737 0.586 0.627 0.387\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 36/150 1.97G 1.016 1.074 1.384 8 800: 100% ━━━━━━━━━━━━ 47/47 4.8it/s 9.8s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.9it/s 0.8s\n"," all 78 87 0.586 0.618 0.549 0.327\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 37/150 1.97G 1.005 1.074 1.401 8 800: 100% ━━━━━━━━━━━━ 47/47 4.2it/s 11.3s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.2it/s 1.2s\n"," all 78 87 0.594 0.678 0.634 0.375\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 38/150 1.97G 1.023 1.116 1.376 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.8it/s 1.0s\n"," all 78 87 0.725 0.563 0.583 0.313\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 39/150 1.97G 0.9653 1.011 1.333 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.8s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.8it/s 0.9s\n"," all 78 87 0.669 0.667 0.68 0.429\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 40/150 1.97G 0.9416 0.9498 1.329 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.9it/s 1.3s\n"," all 78 87 0.646 0.586 0.541 0.341\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 41/150 1.97G 1.017 1.036 1.392 8 800: 100% ━━━━━━━━━━━━ 47/47 4.7it/s 10.0s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.0it/s 1.7s\n"," all 78 87 0.569 0.517 0.472 0.304\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 42/150 1.97G 0.9734 1.024 1.357 8 800: 100% ━━━━━━━━━━━━ 47/47 4.5it/s 10.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.1it/s 0.8s\n"," all 78 87 0.763 0.644 0.664 0.405\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 43/150 1.97G 0.9681 1.003 1.367 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.5it/s 1.1s\n"," all 78 87 0.74 0.655 0.679 0.408\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 44/150 1.97G 0.9058 0.9149 1.308 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.9it/s 0.8s\n"," all 78 87 0.649 0.621 0.584 0.362\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 45/150 1.97G 0.9561 0.9589 1.351 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.6s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.7it/s 1.1s\n"," all 78 87 0.659 0.666 0.677 0.44\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 46/150 1.97G 0.9033 0.9292 1.299 8 800: 100% ━━━━━━━━━━━━ 47/47 4.4it/s 10.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 2.7it/s 1.9s\n"," all 78 87 0.743 0.63 0.705 0.455\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 47/150 1.97G 0.8989 0.916 1.32 8 800: 100% ━━━━━━━━━━━━ 47/47 4.8it/s 9.8s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.4it/s 1.5s\n"," all 78 87 0.643 0.644 0.641 0.422\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 48/150 1.97G 0.9161 0.936 1.336 8 800: 100% ━━━━━━━━━━━━ 47/47 4.4it/s 10.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.3it/s 0.9s\n"," all 78 87 0.781 0.552 0.645 0.398\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 49/150 1.97G 0.9061 0.9097 1.321 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.6s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.9it/s 1.0s\n"," all 78 87 0.776 0.675 0.75 0.466\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 50/150 1.97G 0.9017 0.8843 1.302 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.8s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.4it/s 1.1s\n"," all 78 87 0.749 0.713 0.738 0.473\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 51/150 1.97G 0.8581 0.8821 1.259 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.8s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.7it/s 0.9s\n"," all 78 87 0.685 0.586 0.617 0.414\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 52/150 1.97G 0.8875 0.8783 1.302 8 800: 100% ━━━━━━━━━━━━ 47/47 4.5it/s 10.4s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.2it/s 1.6s\n"," all 78 87 0.756 0.632 0.675 0.444\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 53/150 1.97G 0.8684 0.8269 1.293 8 800: 100% ━━━━━━━━━━━━ 47/47 4.7it/s 10.0s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.4it/s 1.1s\n"," all 78 87 0.8 0.688 0.685 0.47\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 54/150 1.97G 0.8898 0.8641 1.287 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.1it/s 0.8s\n"," all 78 87 0.559 0.685 0.591 0.38\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 55/150 1.97G 0.8769 0.8322 1.263 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.2it/s 1.2s\n"," all 78 87 0.692 0.644 0.658 0.44\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 56/150 1.97G 0.8617 0.8507 1.263 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.6s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.7it/s 1.1s\n"," all 78 87 0.649 0.574 0.553 0.331\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 57/150 1.97G 0.8607 0.84 1.248 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.9it/s 1.0s\n"," all 78 87 0.607 0.54 0.495 0.279\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 58/150 1.97G 0.8778 0.8323 1.268 8 800: 100% ━━━━━━━━━━━━ 47/47 4.6it/s 10.3s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.5it/s 1.4s\n"," all 78 87 0.688 0.634 0.664 0.434\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 59/150 1.97G 0.833 0.8218 1.236 8 800: 100% ━━━━━━━━━━━━ 47/47 4.5it/s 10.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.6it/s 0.9s\n"," all 78 87 0.777 0.602 0.651 0.412\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 60/150 1.97G 0.8037 0.7629 1.219 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.8s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.8it/s 1.0s\n"," all 78 87 0.793 0.655 0.701 0.451\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 61/150 1.97G 0.8857 0.8295 1.293 8 800: 100% ━━━━━━━━━━━━ 47/47 3.9it/s 11.9s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.0it/s 0.8s\n"," all 78 87 0.772 0.662 0.672 0.436\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 62/150 1.97G 0.8153 0.8186 1.242 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.6s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.2it/s 1.2s\n"," all 78 87 0.716 0.697 0.696 0.463\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 63/150 1.97G 0.7909 0.7625 1.219 8 800: 100% ━━━━━━━━━━━━ 47/47 4.2it/s 11.1s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.1it/s 1.6s\n"," all 78 87 0.773 0.666 0.685 0.453\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 64/150 1.97G 0.79 0.7618 1.219 8 800: 100% ━━━━━━━━━━━━ 47/47 4.7it/s 10.1s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.6it/s 1.4s\n"," all 78 87 0.693 0.649 0.648 0.447\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 65/150 1.97G 0.8105 0.7682 1.213 8 800: 100% ━━━━━━━━━━━━ 47/47 4.3it/s 10.8s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.7it/s 1.1s\n"," all 78 87 0.708 0.586 0.588 0.369\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 66/150 1.97G 0.7579 0.7187 1.195 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.8s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.4it/s 0.8s\n"," all 78 87 0.752 0.663 0.657 0.418\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 67/150 1.97G 0.7939 0.7092 1.226 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.0it/s 1.0s\n"," all 78 87 0.761 0.701 0.683 0.448\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 68/150 1.97G 0.7958 0.7574 1.219 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.4s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.2it/s 1.2s\n"," all 78 87 0.74 0.69 0.71 0.444\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 69/150 1.97G 0.7703 0.731 1.201 8 800: 100% ━━━━━━━━━━━━ 47/47 4.4it/s 10.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.1it/s 1.6s\n"," all 78 87 0.76 0.656 0.667 0.43\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 70/150 1.97G 0.8001 0.7232 1.232 8 800: 100% ━━━━━━━━━━━━ 47/47 4.7it/s 10.0s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.7it/s 1.1s\n"," all 78 87 0.75 0.644 0.692 0.436\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 71/150 1.97G 0.7785 0.7272 1.204 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.4s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.3it/s 0.8s\n"," all 78 87 0.755 0.667 0.672 0.449\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 72/150 1.97G 0.7901 0.7356 1.208 8 800: 100% ━━━━━━━━━━━━ 47/47 3.8it/s 12.3s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.5it/s 0.9s\n"," all 78 87 0.761 0.678 0.708 0.475\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 73/150 1.97G 0.7781 0.7344 1.19 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.7it/s 0.9s\n"," all 78 87 0.722 0.621 0.653 0.447\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 74/150 1.97G 0.7503 0.7172 1.176 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.5it/s 1.1s\n"," all 78 87 0.794 0.577 0.672 0.45\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 75/150 1.97G 0.7977 0.7265 1.214 8 800: 100% ━━━━━━━━━━━━ 47/47 4.5it/s 10.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 2.4it/s 2.0s\n"," all 78 87 0.799 0.655 0.69 0.431\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 76/150 1.97G 0.7835 0.7223 1.229 8 800: 100% ━━━━━━━━━━━━ 47/47 4.8it/s 9.8s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.4it/s 1.1s\n"," all 78 87 0.745 0.609 0.615 0.38\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 77/150 1.97G 0.7738 0.713 1.189 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.7it/s 0.9s\n"," all 78 87 0.827 0.644 0.696 0.481\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 78/150 1.97G 0.7348 0.721 1.175 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.0it/s 1.3s\n"," all 78 87 0.721 0.678 0.711 0.476\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 79/150 1.97G 0.7184 0.654 1.18 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.8s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.5it/s 0.9s\n"," all 78 87 0.705 0.678 0.694 0.472\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 80/150 1.97G 0.7599 0.72 1.22 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.2it/s 1.2s\n"," all 78 87 0.775 0.667 0.683 0.462\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 81/150 1.97G 0.7215 0.6744 1.166 8 800: 100% ━━━━━━━━━━━━ 47/47 4.4it/s 10.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.2it/s 1.6s\n"," all 78 87 0.807 0.673 0.698 0.478\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 82/150 1.97G 0.7459 0.7009 1.179 8 800: 100% ━━━━━━━━━━━━ 47/47 4.6it/s 10.2s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.1it/s 1.0s\n"," all 78 87 0.787 0.644 0.685 0.457\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 83/150 1.97G 0.6908 0.6587 1.142 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.4s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.8it/s 1.0s\n"," all 78 87 0.78 0.651 0.693 0.471\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 84/150 1.97G 0.7008 0.6065 1.169 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.2it/s 1.2s\n"," all 78 87 0.729 0.724 0.702 0.45\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 85/150 1.97G 0.7357 0.6895 1.182 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.8s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.6it/s 0.9s\n"," all 78 87 0.768 0.621 0.668 0.438\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 86/150 1.97G 0.7464 0.6977 1.187 8 800: 100% ━━━━━━━━━━━━ 47/47 4.2it/s 11.1s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.4it/s 1.5s\n"," all 78 87 0.79 0.691 0.72 0.487\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 87/150 1.97G 0.7091 0.624 1.144 8 800: 100% ━━━━━━━━━━━━ 47/47 4.5it/s 10.4s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 2.9it/s 1.7s\n"," all 78 87 0.828 0.644 0.663 0.447\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 88/150 1.97G 0.6904 0.6372 1.144 8 800: 100% ━━━━━━━━━━━━ 47/47 4.4it/s 10.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.8it/s 0.9s\n"," all 78 87 0.807 0.627 0.686 0.462\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 89/150 1.97G 0.6982 0.6703 1.16 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.8s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.2it/s 0.8s\n"," all 78 87 0.79 0.655 0.68 0.45\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 90/150 1.97G 0.6646 0.5905 1.141 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.4s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.0it/s 1.2s\n"," all 78 87 0.849 0.586 0.67 0.447\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 91/150 1.97G 0.6976 0.6234 1.145 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.9it/s 1.3s\n"," all 78 87 0.759 0.688 0.705 0.479\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 92/150 1.97G 0.6776 0.6172 1.141 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.6s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.9it/s 1.0s\n"," all 78 87 0.801 0.69 0.702 0.478\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 93/150 1.97G 0.6701 0.5767 1.124 8 800: 100% ━━━━━━━━━━━━ 47/47 4.5it/s 10.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 2.5it/s 2.0s\n"," all 78 87 0.748 0.647 0.67 0.466\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 94/150 1.97G 0.7109 0.6156 1.158 8 800: 100% ━━━━━━━━━━━━ 47/47 4.6it/s 10.1s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.2it/s 1.2s\n"," all 78 87 0.717 0.613 0.687 0.485\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 95/150 1.97G 0.7056 0.6337 1.154 8 800: 100% ━━━━━━━━━━━━ 47/47 4.2it/s 11.2s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.9it/s 1.0s\n"," all 78 87 0.82 0.598 0.677 0.465\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 96/150 1.97G 0.6944 0.6222 1.161 8 800: 100% ━━━━━━━━━━━━ 47/47 4.2it/s 11.2s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.7it/s 1.4s\n"," all 78 87 0.837 0.598 0.673 0.474\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 97/150 1.97G 0.6715 0.6272 1.135 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.8s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.0it/s 1.0s\n"," all 78 87 0.743 0.632 0.672 0.48\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 98/150 1.97G 0.6941 0.6245 1.165 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.6it/s 1.4s\n"," all 78 87 0.742 0.632 0.685 0.463\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 99/150 1.97G 0.6426 0.5921 1.102 8 800: 100% ━━━━━━━━━━━━ 47/47 4.2it/s 11.1s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 2.8it/s 1.8s\n"," all 78 87 0.789 0.69 0.712 0.493\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 100/150 1.97G 0.6958 0.6021 1.152 8 800: 100% ━━━━━━━━━━━━ 47/47 4.7it/s 10.0s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.5it/s 1.4s\n"," all 78 87 0.819 0.609 0.677 0.466\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 101/150 1.97G 0.6736 0.5965 1.122 8 800: 100% ━━━━━━━━━━━━ 47/47 4.3it/s 11.0s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.0it/s 0.8s\n"," all 78 87 0.762 0.667 0.67 0.466\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 102/150 1.97G 0.6456 0.5706 1.129 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.7it/s 1.1s\n"," all 78 87 0.797 0.621 0.657 0.453\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 103/150 1.97G 0.6207 0.5382 1.101 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.6s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.1it/s 1.2s\n"," all 78 87 0.776 0.638 0.651 0.447\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 104/150 1.97G 0.6233 0.5568 1.115 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.5it/s 1.1s\n"," all 78 87 0.763 0.644 0.639 0.433\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 105/150 1.97G 0.6155 0.5465 1.093 8 800: 100% ━━━━━━━━━━━━ 47/47 4.4it/s 10.6s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 2.6it/s 1.9s\n"," all 78 87 0.774 0.667 0.66 0.45\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 106/150 1.97G 0.6155 0.5232 1.084 8 800: 100% ━━━━━━━━━━━━ 47/47 4.8it/s 9.8s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.0it/s 1.2s\n"," all 78 87 0.771 0.695 0.702 0.505\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 107/150 1.97G 0.6483 0.5748 1.131 8 800: 100% ━━━━━━━━━━━━ 47/47 4.2it/s 11.2s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.7it/s 1.1s\n"," all 78 87 0.765 0.655 0.661 0.47\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 108/150 1.97G 0.6302 0.5657 1.103 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.9it/s 1.3s\n"," all 78 87 0.707 0.678 0.664 0.462\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 109/150 1.97G 0.629 0.572 1.105 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.9s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.5it/s 1.1s\n"," all 78 87 0.732 0.722 0.699 0.466\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 110/150 1.97G 0.62 0.5793 1.121 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.9it/s 1.3s\n"," all 78 87 0.79 0.655 0.701 0.472\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 111/150 1.97G 0.635 0.5749 1.108 8 800: 100% ━━━━━━━━━━━━ 47/47 4.3it/s 10.9s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 2.8it/s 1.8s\n"," all 78 87 0.804 0.655 0.693 0.484\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 112/150 1.97G 0.5908 0.5411 1.105 8 800: 100% ━━━━━━━━━━━━ 47/47 4.6it/s 10.1s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.5it/s 1.4s\n"," all 78 87 0.734 0.655 0.647 0.456\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 113/150 1.97G 0.6107 0.566 1.098 8 800: 100% ━━━━━━━━━━━━ 47/47 4.2it/s 11.2s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.5it/s 0.8s\n"," all 78 87 0.813 0.621 0.659 0.457\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 114/150 1.97G 0.652 0.569 1.108 8 800: 100% ━━━━━━━━━━━━ 47/47 3.9it/s 12.0s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.3it/s 0.8s\n"," all 78 87 0.815 0.632 0.649 0.446\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 115/150 1.97G 0.6023 0.5403 1.078 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.6s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.3it/s 0.9s\n"," all 78 87 0.741 0.659 0.637 0.442\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 116/150 1.97G 0.6026 0.5397 1.093 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.3it/s 1.1s\n"," all 78 87 0.719 0.644 0.641 0.438\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 117/150 1.97G 0.5961 0.525 1.09 8 800: 100% ━━━━━━━━━━━━ 47/47 4.2it/s 11.2s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 2.9it/s 1.7s\n"," all 78 87 0.862 0.655 0.702 0.483\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 118/150 1.97G 0.601 0.5637 1.106 8 800: 100% ━━━━━━━━━━━━ 47/47 4.4it/s 10.8s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.1it/s 1.6s\n"," all 78 87 0.742 0.713 0.716 0.5\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 119/150 1.97G 0.5794 0.5043 1.082 8 800: 100% ━━━━━━━━━━━━ 47/47 4.4it/s 10.6s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.5it/s 0.9s\n"," all 78 87 0.797 0.723 0.706 0.488\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 120/150 1.97G 0.5942 0.526 1.087 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.6s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.2it/s 1.2s\n"," all 78 87 0.808 0.701 0.689 0.482\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 121/150 1.97G 0.5694 0.5018 1.072 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.6s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.0it/s 1.2s\n"," all 78 87 0.814 0.653 0.683 0.477\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 122/150 1.97G 0.5593 0.4959 1.066 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.6s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.5it/s 1.1s\n"," all 78 87 0.763 0.667 0.668 0.468\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 123/150 1.97G 0.5395 0.4913 1.06 8 800: 100% ━━━━━━━━━━━━ 47/47 4.3it/s 10.8s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 2.9it/s 1.7s\n"," all 78 87 0.756 0.712 0.694 0.489\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 124/150 1.97G 0.5416 0.4653 1.05 8 800: 100% ━━━━━━━━━━━━ 47/47 4.9it/s 9.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.2it/s 1.2s\n"," all 78 87 0.814 0.632 0.68 0.485\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 125/150 1.97G 0.5743 0.4874 1.076 8 800: 100% ━━━━━━━━━━━━ 47/47 4.3it/s 11.0s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.2it/s 1.2s\n"," all 78 87 0.729 0.681 0.666 0.467\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 126/150 1.97G 0.5749 0.5108 1.079 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.1it/s 1.2s\n"," all 78 87 0.817 0.666 0.679 0.464\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 127/150 1.97G 0.5399 0.4738 1.053 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.6s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.2it/s 1.2s\n"," all 78 87 0.822 0.621 0.659 0.446\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 128/150 1.97G 0.5386 0.4711 1.068 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.2it/s 1.2s\n"," all 78 87 0.825 0.598 0.661 0.459\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 129/150 1.97G 0.5584 0.4862 1.062 8 800: 100% ━━━━━━━━━━━━ 47/47 4.7it/s 10.1s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.6it/s 1.4s\n"," all 78 87 0.749 0.678 0.672 0.457\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 130/150 1.97G 0.5484 0.4729 1.053 8 800: 100% ━━━━━━━━━━━━ 47/47 4.4it/s 10.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.1it/s 0.8s\n"," all 78 87 0.761 0.655 0.671 0.46\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 131/150 1.97G 0.5653 0.4804 1.051 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.3it/s 1.2s\n"," all 78 87 0.782 0.655 0.672 0.465\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 132/150 1.97G 0.54 0.4668 1.049 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.0it/s 1.3s\n"," all 78 87 0.745 0.701 0.694 0.482\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 133/150 1.97G 0.5446 0.4813 1.066 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.6s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.7it/s 1.3s\n"," all 78 87 0.8 0.701 0.688 0.476\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 134/150 1.97G 0.4969 0.4326 1.003 8 800: 100% ━━━━━━━━━━━━ 47/47 4.4it/s 10.6s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 2.7it/s 1.9s\n"," all 78 87 0.784 0.69 0.666 0.469\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 135/150 1.97G 0.5305 0.4687 1.054 8 800: 100% ━━━━━━━━━━━━ 47/47 4.6it/s 10.3s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.8it/s 1.3s\n"," all 78 87 0.787 0.69 0.683 0.481\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 136/150 1.97G 0.4919 0.4369 1.03 8 800: 100% ━━━━━━━━━━━━ 47/47 4.4it/s 10.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 5.8it/s 0.9s\n"," all 78 87 0.779 0.678 0.709 0.493\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 137/150 1.97G 0.5301 0.4657 1.052 8 800: 100% ━━━━━━━━━━━━ 47/47 3.9it/s 12.0s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.3it/s 0.8s\n"," all 78 87 0.783 0.678 0.711 0.506\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 138/150 1.97G 0.5131 0.4766 1.044 8 800: 100% ━━━━━━━━━━━━ 47/47 4.0it/s 11.7s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.9it/s 1.0s\n"," all 78 87 0.762 0.698 0.705 0.492\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 139/150 1.97G 0.5222 0.4453 1.037 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.6s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.5it/s 1.1s\n"," all 78 87 0.797 0.667 0.711 0.503\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 140/150 1.97G 0.4984 0.4409 1.03 8 800: 100% ━━━━━━━━━━━━ 47/47 4.3it/s 10.9s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 2.7it/s 1.9s\n"," all 78 87 0.733 0.713 0.706 0.5\n","Closing dataloader mosaic\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, method='weighted_average', num_output_channels=3), CLAHE(p=0.01, clip_limit=(1.0, 4.0), tile_grid_size=(8, 8))\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 141/150 1.97G 0.4264 0.3545 0.9821 8 800: 100% ━━━━━━━━━━━━ 47/47 3.9it/s 11.9s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.8it/s 1.3s\n"," all 78 87 0.761 0.694 0.689 0.485\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 142/150 1.97G 0.4225 0.3563 0.9639 8 800: 100% ━━━━━━━━━━━━ 47/47 4.7it/s 9.9s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.4it/s 0.8s\n"," all 78 87 0.759 0.686 0.687 0.483\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 143/150 1.97G 0.409 0.3275 0.9685 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.3it/s 0.8s\n"," all 78 87 0.75 0.701 0.694 0.484\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 144/150 1.97G 0.3926 0.3135 0.9416 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.3s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.4it/s 0.8s\n"," all 78 87 0.796 0.678 0.692 0.48\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 145/150 1.97G 0.3834 0.2989 0.9443 8 800: 100% ━━━━━━━━━━━━ 47/47 4.3it/s 10.9s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.0it/s 1.2s\n"," all 78 87 0.834 0.678 0.706 0.493\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 146/150 1.97G 0.3931 0.3037 0.9475 8 800: 100% ━━━━━━━━━━━━ 47/47 4.9it/s 9.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.1it/s 1.2s\n"," all 78 87 0.856 0.681 0.711 0.51\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 147/150 1.97G 0.3816 0.2994 0.9512 8 800: 100% ━━━━━━━━━━━━ 47/47 4.5it/s 10.4s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.3it/s 0.8s\n"," all 78 87 0.841 0.655 0.712 0.514\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 148/150 1.97G 0.3751 0.3008 0.9558 8 800: 100% ━━━━━━━━━━━━ 47/47 4.1it/s 11.5s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 6.4it/s 0.8s\n"," all 78 87 0.837 0.648 0.708 0.511\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 149/150 1.97G 0.372 0.307 0.9323 8 800: 100% ━━━━━━━━━━━━ 47/47 4.2it/s 11.1s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 4.4it/s 1.1s\n"," all 78 87 0.794 0.678 0.712 0.514\n","\n"," Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size\n","\u001b[K 150/150 1.97G 0.3655 0.2941 0.9306 8 800: 100% ━━━━━━━━━━━━ 47/47 4.6it/s 10.2s\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 3.1it/s 1.6s\n"," all 78 87 0.797 0.667 0.713 0.512\n","\n","150 epochs completed in 0.529 hours.\n","Optimizer stripped from /content/runs/detect/train-3/weights/last.pt, 6.3MB\n","Optimizer stripped from /content/runs/detect/train-3/weights/best.pt, 6.3MB\n","\n","Validating /content/runs/detect/train-3/weights/best.pt...\n","Ultralytics 8.4.53 🚀 Python-3.12.13 torch-2.10.0+cu128 CUDA:0 (Tesla T4, 14913MiB)\n","Model summary (fused): 73 layers, 3,005,843 parameters, 0 gradients, 8.1 GFLOPs\n","\u001b[K Class Images Instances Box(P R mAP50 mAP50-95): 100% ━━━━━━━━━━━━ 5/5 1.9it/s 2.6s\n"," all 78 87 0.841 0.655 0.712 0.515\n","Speed: 0.6ms preprocess, 6.2ms inference, 0.0ms loss, 9.0ms postprocess per image\n","Results saved to \u001b[1m/content/runs/detect/train-3\u001b[0m\n","Model Trained\n"]}]},{"cell_type":"code","source":["# CREATE FOLDER TO SAVE MODELS\n","# -----------------------------------\n","\n","os.makedirs(\"saved_models\", exist_ok=True)\n","\n","# -----------------------------------\n","# SAVE BEST AND LAST WEIGHTS\n","# -----------------------------------\n","\n","shutil.copy(\n"," \"runs/detect/accident_detection_model/weights/best.pt\",\n"," \"saved_models/accident_best.pt\"\n",")\n","\n","shutil.copy(\n"," \"runs/detect/accident_detection_model/weights/last.pt\",\n"," \"saved_models/accident_last.pt\"\n",")\n","\n","print(\"Accident Detection Weights Saved Successfully!\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":654},"id":"yVCP3abnX1up","executionInfo":{"status":"error","timestamp":1779602696564,"user_tz":-330,"elapsed":35,"user":{"displayName":"Krishna Verma","userId":"18291293214161594665"}},"outputId":"8e47b61e-0870-4bc6-867f-b557bfa32e9f"},"execution_count":null,"outputs":[{"output_type":"error","ename":"FileNotFoundError","evalue":"[Errno 2] No such file or directory: 'runs/detect/accident_detection_model/weights/best.pt'","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)","\u001b[0;32m/tmp/ipykernel_4219/544648585.py\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0;31m# -----------------------------------\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m shutil.copy(\n\u001b[0m\u001b[1;32m 11\u001b[0m \u001b[0;34m\"runs/detect/accident_detection_model/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 12\u001b[0m \u001b[0;34m\"saved_models/accident_best.pt\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/lib/python3.12/shutil.py\u001b[0m in \u001b[0;36mcopy\u001b[0;34m(src, dst, follow_symlinks)\u001b[0m\n\u001b[1;32m 433\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0misdir\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdst\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[1;32m 434\u001b[0m \u001b[0mdst\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdst\u001b[0m\u001b[0;34m,\u001b[0m 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\u001b[0mfsrc\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 261\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[1;32m 262\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdst\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'wb'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mfdst\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'runs/detect/accident_detection_model/weights/best.pt'"]}]},{"cell_type":"code","source":["from ultralytics import YOLO\n","from IPython.display import Image, display\n","import os"],"metadata":{"id":"OxkP4olN5Yna","executionInfo":{"status":"ok","timestamp":1779607912347,"user_tz":-330,"elapsed":11850,"user":{"displayName":"Krishna Verma","userId":"18291293214161594665"}},"outputId":"87511d07-5929-41d1-8581-f93fc4f3c6d3","colab":{"base_uri":"https://localhost:8080/"}},"execution_count":3,"outputs":[{"output_type":"stream","name":"stdout","text":["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"]}]},{"cell_type":"code","source":[],"metadata":{"id":"e6UCGCaE5ZuE"},"execution_count":null,"outputs":[]}]}