yolo.ipynb

{"cells":[{"cell_type":"code","execution_count":10,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":7,"status":"ok","timestamp":1682055601615,"user":{"displayName":"Shubhankar Shandilya","userId":"01327132389198292390"},"user_tz":-330},"id":"AXY17OrTS-lP","outputId":"4fbb5f44-4c16-4948-d694-43816e3aa7d7"},"outputs":[{"name":"stdout","output_type":"stream","text":["Sat Mar 16 04:44:13 2024       \n","+---------------------------------------------------------------------------------------+\n","| NVIDIA-SMI 546.33                 Driver Version: 546.33       CUDA Version: 12.3     |\n","|-----------------------------------------+----------------------+----------------------+\n","| GPU  Name                     TCC/WDDM  | Bus-Id        Disp.A | Volatile Uncorr. ECC |\n","| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |\n","|                                         |                      |               MIG M. |\n","|=========================================+======================+======================|\n","|   0  NVIDIA GeForce RTX 4050 ...  WDDM  | 00000000:01:00.0 Off |                  N/A |\n","| N/A   46C    P4              11W /  40W |      0MiB /  6141MiB |      0%      Default |\n","|                                         |                      |                  N/A |\n","+-----------------------------------------+----------------------+----------------------+\n","                                                                                         \n","+---------------------------------------------------------------------------------------+\n","| Processes:                                                                            |\n","|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |\n","|        ID   ID                                                             Usage      |\n","|=======================================================================================|\n","|  No running processes found                                                           |\n","+---------------------------------------------------------------------------------------+\n","Collecting ultralytics\n","  Using cached ultralytics-8.1.28-py3-none-any.whl.metadata (40 kB)\n","Requirement already satisfied: matplotlib>=3.3.0 in c:\\users\\shash\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from ultralytics) (3.8.3)\n","Requirement already satisfied: opencv-python>=4.6.0 in c:\\users\\shash\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from ultralytics) (4.9.0.80)\n","Requirement already satisfied: pillow>=7.1.2 in c:\\users\\shash\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from ultralytics) (10.2.0)\n","Requirement already satisfied: pyyaml>=5.3.1 in c:\\users\\shash\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from ultralytics) (6.0.1)\n","Requirement already satisfied: requests>=2.23.0 in c:\\users\\shash\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from 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(2024.3.0)\n","Requirement already satisfied: colorama in c:\\users\\shash\\appdata\\roaming\\python\\python312\\site-packages (from tqdm>=4.64.0->ultralytics) (0.4.6)\n","Requirement already satisfied: six>=1.5 in c:\\users\\shash\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from python-dateutil>=2.7->matplotlib>=3.3.0->ultralytics) (1.16.0)\n","Requirement already satisfied: MarkupSafe>=2.0 in c:\\users\\shash\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from jinja2->torch>=1.8.0->ultralytics) (2.1.5)\n","Requirement already satisfied: mpmath>=0.19 in c:\\users\\shash\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from sympy->torch>=1.8.0->ultralytics) (1.3.0)\n","Using cached ultralytics-8.1.28-py3-none-any.whl (721 kB)\n","Using cached seaborn-0.13.2-py3-none-any.whl (294 kB)\n","Using cached thop-0.1.1.post2209072238-py3-none-any.whl (15 kB)\n","Using cached torchvision-0.17.1-cp312-cp312-win_amd64.whl (1.2 MB)\n","Installing collected packages: torchvision, thop, seaborn, ultralytics\n","Successfully installed seaborn-0.13.2 thop-0.1.1.post2209072238 torchvision-0.17.1 ultralytics-8.1.28\n"]}],"source":["!nvidia-smi\n","!pip install ultralytics\n","\n"]},{"cell_type":"code","execution_count":12,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":17553,"status":"ok","timestamp":1682075120658,"user":{"displayName":"Shubhankar Shandilya","userId":"01327132389198292390"},"user_tz":-330},"id":"PQ6RkiuB8rvS","outputId":"085d8dd4-d865-4832-84bb-f272fac4b6fb"},"outputs":[{"name":"stdout","output_type":"stream","text":["Ultralytics YOLOv8.1.28 🚀 Python-3.12.2 torch-2.2.1+cpu CPU (13th Gen Intel Core(TM) i5-13420H)\n","Setup complete ✅ (12 CPUs, 15.7 GB RAM, 228.5/476.1 GB disk)\n"]}],"source":["\n","from IPython import display\n","display.clear_output()\n","\n","import ultralytics\n","ultralytics.checks()"]},{"cell_type":"code","execution_count":13,"metadata":{"executionInfo":{"elapsed":518,"status":"ok","timestamp":1682075156174,"user":{"displayName":"Shubhankar Shandilya","userId":"01327132389198292390"},"user_tz":-330},"id":"BbzJv2ye81Ov"},"outputs":[],"source":["from ultralytics import YOLO\n","\n","from IPython.display import display, Image"]},{"cell_type":"code","execution_count":16,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":23581,"status":"ok","timestamp":1682075183393,"user":{"displayName":"Shubhankar Shandilya","userId":"01327132389198292390"},"user_tz":-330},"id":"S36_rNInDWSn","outputId":"cb0e6643-aa71-401b-e59d-4148b38d2dc7"},"outputs":[{"name":"stdout","output_type":"stream","text":["Collecting google-api-python-client\n","  Downloading google_api_python_client-2.122.0-py2.py3-none-any.whl.metadata (6.6 kB)\n","Collecting httplib2<1.dev0,>=0.15.0 (from google-api-python-client)\n","  Downloading 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---------------------------------------- 84.9/84.9 kB 1.2 MB/s eta 0:00:00\n","Installing collected packages: uritemplate, pyasn1, protobuf, httplib2, cachetools, rsa, pyasn1-modules, googleapis-common-protos, google-auth, google-auth-httplib2, google-api-core, google-api-python-client\n","Successfully installed cachetools-5.3.3 google-api-core-2.17.1 google-api-python-client-2.122.0 google-auth-2.28.2 google-auth-httplib2-0.2.0 googleapis-common-protos-1.63.0 httplib2-0.22.0 protobuf-4.25.3 pyasn1-0.5.1 pyasn1-modules-0.3.0 rsa-4.9 uritemplate-4.1.1\n"]},{"ename":"ModuleNotFoundError","evalue":"No module named 'google.colab'","output_type":"error","traceback":["\u001b[1;31m---------------------------------------------------------------------------\u001b[0m","\u001b[1;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)","Cell \u001b[1;32mIn[16], line 2\u001b[0m\n\u001b[0;32m      1\u001b[0m get_ipython()\u001b[38;5;241m.\u001b[39msystem(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mpip install google-api-python-client\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m----> 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mgoogle\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcolab\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m drive\n\u001b[0;32m      3\u001b[0m drive\u001b[38;5;241m.\u001b[39mmount(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m/content/drive\u001b[39m\u001b[38;5;124m'\u001b[39m)\n","\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'google.colab'"]}],"source":["import pydrive\n","from pydrive.auth import GoogleAuth\n","from pydrive.drive import GoogleDrive\n","\n","# Authenticate and create GoogleDrive instance\n","gauth = GoogleAuth()\n","gauth.LocalWebserverAuth()  # Opens a new window to authenticate\n","drive = GoogleDrive(gauth)\n","\n","# Mount Google Drive\n","drive.mount('/content/drive')\n"]},{"cell_type":"code","execution_count":17,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":487,"status":"ok","timestamp":1682055695557,"user":{"displayName":"Shubhankar Shandilya","userId":"01327132389198292390"},"user_tz":-330},"id":"RsuzB39AEHpQ","outputId":"1062d09e-0b6e-442b-99b6-6cfff6847d1f"},"outputs":[{"name":"stdout","output_type":"stream","text":[" Volume in drive C is Windows\n"," Volume Serial Number is 5213-8E1C\n","\n"," Directory of c:\\Roms\\smart\\Accident-Detection-Model\n","\n","16-03-2024  04:30    <DIR>          .\n","16-03-2024  04:28    <DIR>          ..\n","16-03-2024  04:30         7,056,616 Accident detection demo.mp4\n","16-03-2024  04:30    <DIR>          data\n","16-03-2024  04:30               435 data.yaml\n","16-03-2024  04:30             6,556 README.md\n","16-03-2024  04:30    <DIR>          runs\n","16-03-2024  04:30            49,063 yolo.ipynb\n","16-03-2024  04:30        22,573,363 yolov8s.pt\n","               5 File(s)     29,686,033 bytes\n","               4 Dir(s)  265,752,010,752 bytes free\n"]}],"source":["ls\n"]},{"cell_type":"code","execution_count":20,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":114827,"status":"ok","timestamp":1682075330434,"user":{"displayName":"Shubhankar Shandilya","userId":"01327132389198292390"},"user_tz":-330},"id":"onGbGuMvMMVz","outputId":"af6d921e-7652-482d-ac13-e02513327721"},"outputs":[{"name":"stdout","output_type":"stream","text":["C:\\Roms\\smart\\Accident-Detection-Model\n"]},{"name":"stderr","output_type":"stream","text":["C:\\Users\\shash\\AppData\\Roaming\\Python\\Python312\\site-packages\\IPython\\core\\magics\\osm.py:417: UserWarning: This is now an optional IPython functionality, setting dhist requires you to install the `pickleshare` library.\n","  self.shell.db['dhist'] = compress_dhist(dhist)[-100:]\n"]},{"name":"stdout","output_type":"stream","text":["Ultralytics YOLOv8.1.28 🚀 Python-3.12.2 torch-2.2.1+cpu CPU (13th Gen Intel Core(TM) i5-13420H)\n","\u001b[34m\u001b[1mengine\\trainer: \u001b[0mtask=detect, mode=train, model=yolov8s.pt, data=data.yaml, epochs=1, time=None, patience=100, batch=16, imgsz=640, save=True, save_period=-1, cache=False, device=None, workers=8, project=None, name=train5, 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=False, opset=None, workspace=4, nms=False, lr0=0.01, 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, label_smoothing=0.0, 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, mosaic=1.0, mixup=0.0, copy_paste=0.0, auto_augment=randaugment, erasing=0.4, crop_fraction=1.0, cfg=None, tracker=botsort.yaml, save_dir=runs\\detect\\train5\n"]},{"name":"stderr","output_type":"stream","text":["Traceback (most recent call last):\n","  File \"C:\\Users\\shash\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\ultralytics\\engine\\trainer.py\", line 138, in __init__\n","    self.data = check_det_dataset(self.args.data)\n","                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n","  File \"C:\\Users\\shash\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\ultralytics\\data\\utils.py\", line 327, in check_det_dataset\n","    raise FileNotFoundError(m)\n","FileNotFoundError: \n","Dataset 'data.yaml' images not found ⚠️, missing path 'C:\\content\\drive\\MyDrive\\Accident Detection model\\data\\valid\\images'\n","Note dataset download directory is 'C:\\Roms\\smart\\Accident-Detection-Model\\datasets'. You can update this in 'C:\\Users\\shash\\AppData\\Roaming\\Ultralytics\\settings.yaml'\n","\n","The above exception was the direct cause of the following exception:\n","\n","Traceback (most recent call last):\n","  File \"<frozen runpy>\", line 198, in _run_module_as_main\n","  File \"<frozen runpy>\", line 88, in _run_code\n","  File \"C:\\Users\\shash\\AppData\\Local\\Programs\\Python\\Python312\\Scripts\\yolo.exe\\__main__.py\", line 7, in <module>\n","  File \"C:\\Users\\shash\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\ultralytics\\cfg\\__init__.py\", line 568, in entrypoint\n","    getattr(model, mode)(**overrides)  # default args from model\n","    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n","  File \"C:\\Users\\shash\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\ultralytics\\engine\\model.py\", line 636, in train\n","    self.trainer = (trainer or self._smart_load(\"trainer\"))(overrides=args, _callbacks=self.callbacks)\n","                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n","  File \"C:\\Users\\shash\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\ultralytics\\engine\\trainer.py\", line 142, in __init__\n","    raise RuntimeError(emojis(f\"Dataset '{clean_url(self.args.data)}' error ❌ {e}\")) from e\n","RuntimeError: Dataset 'data.yaml' error  \n","Dataset 'data.yaml' images not found , missing path 'C:\\content\\drive\\MyDrive\\Accident Detection model\\data\\valid\\images'\n","Note dataset download directory is 'C:\\Roms\\smart\\Accident-Detection-Model\\datasets'. You can update this in 'C:\\Users\\shash\\AppData\\Roaming\\Ultralytics\\settings.yaml'\n"]}],"source":["%cd C:\\Roms\\smart\\Accident-Detection-Model\n","!yolo task=detect mode=train model=yolov8s.pt data= data.yaml epochs=1 imgsz=640 plots=True"]},{"cell_type":"code","execution_count":21,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":19932,"status":"ok","timestamp":1682013490562,"user":{"displayName":"Shubhankar Shandilya","userId":"01327132389198292390"},"user_tz":-330},"id":"Q1Bp-ldxFaLf","outputId":"55d09109-8349-49d9-88b6-d81652839795"},"outputs":[{"name":"stderr","output_type":"stream","text":["Traceback (most recent call last):\n","  File \"<frozen runpy>\", line 198, in _run_module_as_main\n","  File \"<frozen runpy>\", line 88, in _run_code\n","  File \"C:\\Users\\shash\\AppData\\Local\\Programs\\Python\\Python312\\Scripts\\yolo.exe\\__main__.py\", line 7, in <module>\n","  File \"C:\\Users\\shash\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\ultralytics\\cfg\\__init__.py\", line 541, in entrypoint\n","    model = YOLO(model, task=task)\n","            ^^^^^^^^^^^^^^^^^^^^^^\n","  File \"C:\\Users\\shash\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\ultralytics\\models\\yolo\\model.py\", line 23, in __init__\n","    super().__init__(model=model, task=task, verbose=verbose)\n","  File \"C:\\Users\\shash\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\ultralytics\\engine\\model.py\", line 142, in __init__\n","    self._load(model, task=task)\n","  File \"C:\\Users\\shash\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\ultralytics\\engine\\model.py\", line 229, in _load\n","    self.model, self.ckpt = attempt_load_one_weight(weights)\n","                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n","  File \"C:\\Users\\shash\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\ultralytics\\nn\\tasks.py\", line 788, in attempt_load_one_weight\n","    ckpt, weight = torch_safe_load(weight)  # load ckpt\n","                   ^^^^^^^^^^^^^^^^^^^^^^^\n","  File \"C:\\Users\\shash\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\ultralytics\\nn\\tasks.py\", line 714, in torch_safe_load\n","    ckpt = torch.load(file, map_location=\"cpu\")\n","           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n","  File \"C:\\Users\\shash\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\torch\\serialization.py\", line 998, in load\n","    with _open_file_like(f, 'rb') as opened_file:\n","         ^^^^^^^^^^^^^^^^^^^^^^^^\n","  File \"C:\\Users\\shash\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\torch\\serialization.py\", line 445, in _open_file_like\n","    return _open_file(name_or_buffer, mode)\n","           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n","  File \"C:\\Users\\shash\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\torch\\serialization.py\", line 426, in __init__\n","    super().__init__(open(name, mode))\n","                     ^^^^^^^^^^^^^^^^\n","FileNotFoundError: [Errno 2] No such file or directory: 'Accident-Detection-Model\\\\runs\\\\detect\\\\train\\\\weights\\\\best.pt'\n"]}],"source":["!yolo task=detect mode=val model=Accident-Detection-Model\\runs\\detect\\train\\weights\\best.pt data=data.yaml"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":13936,"status":"ok","timestamp":1682013520766,"user":{"displayName":"Shubhankar Shandilya","userId":"01327132389198292390"},"user_tz":-330},"id":"2GyRu-6NJRPU","outputId":"1be25396-fc64-4753-d3a8-40c42d7aa60c"},"outputs":[{"name":"stdout","output_type":"stream","text":["2023-04-20 17:58:29.829297: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n","To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n","2023-04-20 17:58:30.725857: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n","Ultralytics YOLOv8.0.20 🚀 Python-3.9.16 torch-2.0.0+cu118 CUDA:0 (Tesla T4, 15102MiB)\n","Model summary (fused): 168 layers, 11125971 parameters, 0 gradients, 28.4 GFLOPs\n","image 1/157 /content/drive/MyDrive/Accident Detection model/data/test/images/5_17_jpg.rf.0611b10e50517e4323c47fc36301167c.jpg: 640x640 16.3ms\n","image 2/157 /content/drive/MyDrive/Accident Detection model/data/test/images/5_22_jpg.rf.368e2a41bf84be83076f603939cbd052.jpg: 640x640 16.4ms\n","image 3/157 /content/drive/MyDrive/Accident Detection 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model/data/test/images/ezgif-frame-024_jpg.rf.d5ce065fc385ec4d85531516df55ad4d.jpg: 640x640 16.3ms\n","image 10/157 /content/drive/MyDrive/Accident Detection model/data/test/images/ezgif-frame-035_jpg.rf.e287c6b9e77c1c89d64748e6bab9a4c9.jpg: 640x640 16.3ms\n","image 11/157 /content/drive/MyDrive/Accident Detection model/data/test/images/ezgif-frame-044_jpg.rf.6de16d60931c4fd0294ec0113635c3f6.jpg: 640x640 1 Accident, 16.3ms\n","image 12/157 /content/drive/MyDrive/Accident Detection model/data/test/images/ezgif-frame-046_jpg.rf.58bafed15631d50fc538d4aac47211d8.jpg: 640x640 1 Accident, 13.7ms\n","image 13/157 /content/drive/MyDrive/Accident Detection model/data/test/images/ezgif-frame-047_jpg.rf.aa137abf5ade5c0f70d83a46c0f8879d.jpg: 640x640 1 Accident, 13.7ms\n","image 14/157 /content/drive/MyDrive/Accident Detection model/data/test/images/ezgif-frame-052_jpg.rf.90449e7817c3c3279974375779e138c5.jpg: 640x640 1 Accident, 13.6ms\n","image 15/157 /content/drive/MyDrive/Accident Detection model/data/test/images/ezgif-frame-066_jpg.rf.fdb8946d733e61a9a3d3844ec7e6c53b.jpg: 640x640 2 Accidents, 13.7ms\n","image 16/157 /content/drive/MyDrive/Accident Detection model/data/test/images/ezgif-frame-070_jpg.rf.4a86f52c6e8115022429b72eb85f2e23.jpg: 640x640 1 Accident, 13.6ms\n","image 17/157 /content/drive/MyDrive/Accident Detection model/data/test/images/ezgif-frame-084_jpg.rf.5baef21b0727b12e875ab4eabec219de.jpg: 640x640 13.6ms\n","image 18/157 /content/drive/MyDrive/Accident Detection model/data/test/images/ezgif-frame-084_jpg.rf.9135182ded36f2ee16fb64e99db8b5ab.jpg: 640x640 1 Accident, 13.6ms\n","image 19/157 /content/drive/MyDrive/Accident Detection model/data/test/images/ezgif-frame-086_jpg.rf.15736ae6f748ca1a3bdaacdfe2f3224e.jpg: 640x640 1 Accident, 13.6ms\n","image 20/157 /content/drive/MyDrive/Accident Detection model/data/test/images/ezgif-frame-087_jpg.rf.1b6dbb7410ebd5329288c8da6ae74d5f.jpg: 640x640 1 Accident, 13.7ms\n","image 21/157 /content/drive/MyDrive/Accident 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8.8ms\n","image 46/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test11_13_jpg.rf.5b3d3743a2f930e2e7f2c9aa4d099727.jpg: 640x640 8.7ms\n","image 47/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test11_14_jpg.rf.482dd40a3a63d62c4454d7655d0dbc90.jpg: 640x640 8.8ms\n","image 48/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test11_15_jpg.rf.152b04c4c1df866b8471700730d3f496.jpg: 640x640 1 Accident, 8.7ms\n","image 49/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test11_16_jpg.rf.f9d011236ccad66129797efd23e88cd9.jpg: 640x640 1 Accident, 8.7ms\n","image 50/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test11_1_jpg.rf.f3d75601693562e2c94ffb1a79a5b9fe.jpg: 640x640 8.4ms\n","image 51/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test11_2_jpg.rf.e9cf22765e58762c240a6928aa210769.jpg: 640x640 8.1ms\n","image 52/157 /content/drive/MyDrive/Accident Detection 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model/data/test/images/test13_7_jpg.rf.95660b942516301ae59f0f30e52fc96f.jpg: 640x640 10.0ms\n","image 96/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test13_8_jpg.rf.0b2cd98be7b43544655256cdf661cc03.jpg: 640x640 9.0ms\n","image 97/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test13_9_jpg.rf.cf9102f731d08c35faf3f63a6a398d26.jpg: 640x640 1 Accident, 7.8ms\n","image 98/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test14_1_jpg.rf.467775e5f482b94d6fbe9b7b2950ff14.jpg: 640x640 1 Accident, 7.8ms\n","image 99/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test14_22_jpg.rf.02016127fdb3b27a8f585ae94162d22b.jpg: 640x640 1 Accident, 10.1ms\n","image 100/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test14_23_jpg.rf.55e89eb098dcc7772d00bc70de712418.jpg: 640x640 1 Accident, 7.9ms\n","image 101/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test14_24_jpg.rf.97c541bb876d581f544ff042948656ae.jpg: 640x640 1 Accident, 8.4ms\n","image 102/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test14_25_jpg.rf.895670355bc65ee62339fb0a0f3ddbf6.jpg: 640x640 1 Accident, 7.6ms\n","image 103/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test14_2_jpg.rf.1a9a2cfb5e5459bbd06ae53e945bc6ce.jpg: 640x640 11.9ms\n","image 104/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test14_3_jpg.rf.bbceb2c028b8adf6637cd5e68111ec4f.jpg: 640x640 8.2ms\n","image 105/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test14_4_jpg.rf.a51a0d68b1b26db7c7032a24be553694.jpg: 640x640 11.4ms\n","image 106/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test14_5_jpg.rf.f7440c28f8a41c8efd456e184d1ded27.jpg: 640x640 1 Accident, 7.6ms\n","image 107/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test14_6_jpg.rf.57261b801996351d671df4a8c760e5d2.jpg: 640x640 7.7ms\n","image 108/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test14_7_jpg.rf.0154c3a808ef99b971f73addf9c161d9.jpg: 640x640 1 Accident, 9.8ms\n","image 109/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test14_8_jpg.rf.d0ec913b06a13cbc2202c7958ef0ca74.jpg: 640x640 1 Accident, 8.6ms\n","image 110/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test15_17_jpg.rf.0ceef0b6098d0a77415ceea30fcbc565.jpg: 640x640 1 Accident, 7.6ms\n","image 111/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test15_18_jpg.rf.1f5e18bc75c2f5317c0ac025c4b552b4.jpg: 640x640 1 Accident, 7.6ms\n","image 112/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test15_19_jpg.rf.840e51288b205fec5ad7d3221a7e8892.jpg: 640x640 1 Accident, 7.6ms\n","image 113/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test15_1_jpg.rf.e2318775097f7fc3da4ef1d38fa87a91.jpg: 640x640 7.6ms\n","image 114/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test15_20_jpg.rf.924a09978ca2b59d80f3ae55de242805.jpg: 640x640 1 Accident, 7.8ms\n","image 115/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test15_21_jpg.rf.f251b18f54fbf9078ca7e3f216f23420.jpg: 640x640 2 Accidents, 7.5ms\n","image 116/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test15_22_jpg.rf.5854de2847abebe0fd27cc76394f651b.jpg: 640x640 2 Accidents, 7.7ms\n","image 117/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test15_23_jpg.rf.fadb1d60261e072ac755f7bac4f73ac9.jpg: 640x640 2 Accidents, 7.5ms\n","image 118/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test15_24_jpg.rf.68faa9492675527a7e022fe5c895f2c6.jpg: 640x640 2 Accidents, 11.2ms\n","image 119/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test15_25_jpg.rf.9f4afd5113d42c8032ae24e066b0ac95.jpg: 640x640 2 Accidents, 7.9ms\n","image 120/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test15_26_jpg.rf.b636eb64d2a2ab23fcfdaa19472e7f25.jpg: 640x640 2 Accidents, 11.1ms\n","image 121/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test15_28_jpg.rf.2aa21c2d862f56be24e359c2f374e181.jpg: 640x640 2 Accidents, 7.6ms\n","image 122/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test15_29_jpg.rf.dfe1c5bf59b7168eb4ddb6464a1f2afd.jpg: 640x640 2 Accidents, 8.0ms\n","image 123/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test15_30_jpg.rf.e5d2eedcf0c9ee390c583beea6a1ff51.jpg: 640x640 2 Accidents, 7.5ms\n","image 124/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test15_31_jpg.rf.01612eabf8bb23f659233410ff5099c0.jpg: 640x640 3 Accidents, 7.9ms\n","image 125/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test16_10_jpg.rf.44c2cd60fc1aa6841d966605aa349a56.jpg: 640x640 11.3ms\n","image 126/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test16_11_jpg.rf.bc37395ae2f0b5323049ad89cb9289e2.jpg: 640x640 11.9ms\n","image 127/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test16_12_jpg.rf.2cbe8ce56d7c5bf432956e1d99d08932.jpg: 640x640 8.5ms\n","image 128/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test16_13_jpg.rf.782735c88123a4c0e3c439029333a641.jpg: 640x640 8.0ms\n","image 129/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test16_14_jpg.rf.e98ff1bc47765b87475a36f033745c8b.jpg: 640x640 8.4ms\n","image 130/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test16_15_jpg.rf.487bb2b62798595fb0cac2eda981898a.jpg: 640x640 7.8ms\n","image 131/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test16_16_jpg.rf.904a32c8bc8b59b3d7c9c48a3b85ee2e.jpg: 640x640 7.7ms\n","image 132/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test16_17_jpg.rf.16549350ade6b4f07a1b36667e7f6d28.jpg: 640x640 7.5ms\n","image 133/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test16_18_jpg.rf.50346db360a11d3ddd1d7f85e1028bae.jpg: 640x640 7.6ms\n","image 134/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test16_1_jpg.rf.12ccad2e9bd4a31186708363287c86a5.jpg: 640x640 1 Accident, 11.1ms\n","image 135/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test16_2_jpg.rf.7a6019e14144ff1b81cc228e454eab6c.jpg: 640x640 1 Accident, 7.6ms\n","image 136/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test16_3_jpg.rf.81f0510b1103c621e08ae2d09449ac8a.jpg: 640x640 1 Accident, 7.6ms\n","image 137/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test16_4_jpg.rf.08d12120a25dd05f0ed76a95ee18a9e4.jpg: 640x640 1 Accident, 7.7ms\n","image 138/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test16_5_jpg.rf.b3e7f55da57447895abbe4da4a4d514d.jpg: 640x640 1 Accident, 7.6ms\n","image 139/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test16_6_jpg.rf.23e276a56e5eed75361916d2afde645f.jpg: 640x640 7.8ms\n","image 140/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test16_7_jpg.rf.e8a7c7ed01279378385873988e67d0c4.jpg: 640x640 7.5ms\n","image 141/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test16_8_jpg.rf.71c5b71edc746cbcb2311e4b9cbe7f00.jpg: 640x640 7.5ms\n","image 142/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test17_1_jpg.rf.06c83a3f8f04ade8343d86cd85ef7681.jpg: 640x640 8.2ms\n","image 143/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test18_13_jpg.rf.951fac25793f169165a174acb5e51473.jpg: 640x640 8.2ms\n","image 144/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test1_11_jpg.rf.a8148c15ad1d6668dab0f5a06320451e.jpg: 640x640 8.2ms\n","image 145/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test1_12_jpg.rf.b84ee5beb8025d0ba19362a07e66b987.jpg: 640x640 8.2ms\n","image 146/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test1_4_jpg.rf.808144fe00104728a45b52a1ec0c325b.jpg: 640x640 8.2ms\n","image 147/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test1_7_jpg.rf.127fca67140359be57bba6ed3e3a9fcf.jpg: 640x640 8.2ms\n","image 148/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test1_8_jpg.rf.cbed179d7eaa80f8dc9fd99a5a68cc2f.jpg: 640x640 8.2ms\n","image 149/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test1_9_jpg.rf.5a402754e81959648fcadf87718d4f50.jpg: 640x640 8.2ms\n","image 150/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test20_11_jpg.rf.4c2e51a1a229cd8d1eff898c7ef3aada.jpg: 640x640 8.2ms\n","image 151/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test20_12_jpg.rf.5a6d1faffcac3baf8defb69c1c8afa33.jpg: 640x640 8.2ms\n","image 152/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test20_14_jpg.rf.1979e8c9312b05584bfc7f621ece4217.jpg: 640x640 8.3ms\n","image 153/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test20_1_jpg.rf.6ba33cd73ba2004b536f0c75b1a741ec.jpg: 640x640 8.3ms\n","image 154/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test20_2_jpg.rf.7747a4bd0ed4ebd13512006a1d0914a2.jpg: 640x640 8.2ms\n","image 155/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test20_4_jpg.rf.39071409c8173a628a325ac53b5e23e4.jpg: 640x640 8.3ms\n","image 156/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test20_5_jpg.rf.9e52fd538ef5b320fbad59916145458c.jpg: 640x640 8.1ms\n","image 157/157 /content/drive/MyDrive/Accident Detection model/data/test/images/test20_7_jpg.rf.8e5181d8842c81404d7f03fcd6c7ac25.jpg: 640x640 12.9ms\n","Speed: 0.5ms pre-process, 9.5ms inference, 1.7ms postprocess per image at shape (1, 3, 640, 640)\n"]}],"source":["!yolo task=detect mode=predict model=runs/detect/train/weights/best.pt conf=0.25 source=data/test/images"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":12217,"status":"ok","timestamp":1682069039133,"user":{"displayName":"Shubhankar Shandilya","userId":"01327132389198292390"},"user_tz":-330},"id":"JbeWz4MlL7qB","outputId":"55a1cf3b-61a2-4fa3-c1cc-5d81866824a7"},"outputs":[{"name":"stdout","output_type":"stream","text":["2023-04-21 09:23:50.634575: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n","To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n","2023-04-21 09:23:51.465151: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n","Ultralytics YOLOv8.0.20 🚀 Python-3.9.16 torch-2.0.0+cu118 CUDA:0 (Tesla T4, 15102MiB)\n","Model summary (fused): 168 layers, 11125971 parameters, 0 gradients, 28.4 GFLOPs\n","image 1/1 /content/drive/MyDrive/Accident Detection model/data/testing1.jpg: 640x640 1 Accident, 16.3ms\n","Speed: 0.9ms pre-process, 16.3ms inference, 114.2ms postprocess per image at shape (1, 3, 640, 640)\n"]}],"source":["!yolo task=detect mode=predict model=runs/detect/train/weights/best.pt source=\"/content/drive/MyDrive/Accident Detection model/data/testing1.jpg\""]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3772,"status":"ok","timestamp":1682075461476,"user":{"displayName":"Shubhankar Shandilya","userId":"01327132389198292390"},"user_tz":-330},"id":"pTHGkHaLQqp8","outputId":"cc740bb6-5b4f-4fe0-ba8c-127f05980019"},"outputs":[{"name":"stdout","output_type":"stream","text":["Traceback (most recent call last):\n","  File \"/usr/local/bin/yolo\", line 8, in <module>\n","    sys.exit(entrypoint())\n","  File \"/usr/local/lib/python3.9/dist-packages/ultralytics/yolo/cfg/__init__.py\", line 212, in entrypoint\n","    raise argument_error(a)\n","SyntaxError: '-thresh' is not a valid YOLO argument.\n","\n","    YOLOv8 'yolo' CLI commands use the following syntax:\n","\n","        yolo TASK MODE ARGS\n","\n","        Where   TASK (optional) is one of [detect, segment, classify]\n","                MODE (required) is one of [train, val, predict, export]\n","                ARGS (optional) are any number of custom 'arg=value' pairs like 'imgsz=320' that override defaults.\n","                    See all ARGS at https://docs.ultralytics.com/cfg or with 'yolo cfg'\n","\n","    1. Train a detection model for 10 epochs with an initial learning_rate of 0.01\n","        yolo detect train data=coco128.yaml model=yolov8n.pt epochs=10 lr0=0.01\n","\n","    2. Predict a YouTube video using a pretrained segmentation model at image size 320:\n","        yolo segment predict model=yolov8n-seg.pt source='https://youtu.be/Zgi9g1ksQHc' imgsz=320\n","\n","    3. Val a pretrained detection model at batch-size 1 and image size 640:\n","        yolo detect val model=yolov8n.pt data=coco128.yaml batch=1 imgsz=640\n","\n","    4. Export a YOLOv8n classification model to ONNX format at image size 224 by 128 (no TASK required)\n","        yolo export model=yolov8n-cls.pt format=onnx imgsz=224,128\n","\n","    5. Run special commands:\n","        yolo help\n","        yolo checks\n","        yolo version\n","        yolo settings\n","        yolo copy-cfg\n","        yolo cfg\n","\n","    Docs: https://docs.ultralytics.com/cli\n","    Community: https://community.ultralytics.com\n","    GitHub: https://github.com/ultralytics/ultralytics\n","    \n","No accident detected\n"]}],"source":["!yolo task=detect mode=predict model=runs/detect/train/weights/best.pt source=\"/content/drive/MyDrive/Accident Detection model/data/testing1.jpg\" -thresh 0.01 | grep \"ACCIDENT\" && echo \"Accident is present\" || echo \"No accident detected\"\n"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":374},"executionInfo":{"elapsed":1996,"status":"error","timestamp":1682069746131,"user":{"displayName":"Shubhankar Shandilya","userId":"01327132389198292390"},"user_tz":-330},"id":"g8ugQqunQ8m7","outputId":"1aa393b3-c509-4f85-8b65-9111cc470a66"},"outputs":[{"ename":"error","evalue":"ignored","output_type":"error","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31merror\u001b[0m                                     Traceback (most recent call last)","\u001b[0;32m<ipython-input-13-474ad9d4c1da>\u001b[0m in \u001b[0;36m<cell line: 49>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     47\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     48\u001b[0m \u001b[0;31m# Get the number of objects detected\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 49\u001b[0;31m \u001b[0mnum_objects\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdetect_objects\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutput_image\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel_path\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     50\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     51\u001b[0m \u001b[0;31m# Set a threshold for the number of objects\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m<ipython-input-13-474ad9d4c1da>\u001b[0m in \u001b[0;36mdetect_objects\u001b[0;34m(image, model_path, conf_thres)\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mdetect_objects\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mimage\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel_path\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconf_thres\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0.4\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      7\u001b[0m     \u001b[0;31m# Load the model\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 8\u001b[0;31m     \u001b[0mnet\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcv2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdnn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreadNet\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel_path\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      9\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     10\u001b[0m     \u001b[0;31m# Get the names of the output layers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31merror\u001b[0m: OpenCV(4.7.0) /io/opencv/modules/dnn/src/dnn_read.cpp:52: error: (-2:Unspecified error) Cannot determine an origin framework of files: /content/drive/MyDrive/Accident Detection model/runs/detect/train/weights/best.pt in function 'readNet'\n"]}],"source":["import cv2\n","\n","import torch\n","import cv2\n","\n","def detect_objects(image, model_path, conf_thres=0.4):\n","    # Load the model\n","    net = cv2.dnn.readNet(model_path)\n","\n","    # Get the names of the output layers\n","    layer_names = net.getLayerNames()\n","    output_layers = [layer_names[i[0] - 1] for i in net.getUnconnectedOutLayers()]\n","\n","    # Resize the image and normalize pixel values to [0, 1]\n","    blob = cv2.dnn.blobFromImage(image, 1/255, (416, 416), swapRB=True, crop=False)\n","\n","    # Set the input of the network\n","    net.setInput(blob)\n","\n","    # Forward pass through the network\n","    outputs = net.forward(output_layers)\n","\n","    # Parse the outputs and get the class IDs, confidences and bounding boxes\n","    class_ids, confidences, boxes = [], [], []\n","    for output in outputs:\n","        for detection in output:\n","            scores = detection[5:]\n","            class_id = np.argmax(scores)\n","            confidence = scores[class_id]\n","            if confidence > conf_thres:\n","                center_x, center_y, width, height = detection[:4] * np.array([image.shape[1], image.shape[0], image.shape[1], image.shape[0]])\n","                x, y = int(center_x - width/2), int(center_y - height/2)\n","                w, h = int(width), int(height)\n","                class_ids.append(class_id)\n","                confidences.append(float(confidence))\n","                boxes.append([x, y, w, h])\n","\n","    # Return the class IDs, confidences and bounding boxes\n","    return class_ids, confidences, boxes\n","\n","\n","# Load the output image\n","output_image = cv2.imread(\"/content/drive/MyDrive/Accident Detection model/runs/detect/predict2/testing1.jpg\")\n","\n","# Set the path to your YOLO model\n","model_path = \"/content/drive/MyDrive/Accident Detection model/runs/detect/train/weights/best.pt\"\n","\n","# Get the number of objects detected\n","num_objects = len(detect_objects(output_image, model_path))\n","\n","# Set a threshold for the number of objects\n","if num_objects > 0:\n","    message = \"Accident detected!\"\n","else:\n","    message = \"No accidents detected.\"\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"RkfHXDnheU3j"},"outputs":[],"source":[]}],"metadata":{"accelerator":"GPU","colab":{"authorship_tag":"ABX9TyMT2f5ozLK1kTD8LjhiD8X8","provenance":[]},"gpuClass":"standard","kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.12.2"}},"nbformat":4,"nbformat_minor":0}