{"cells":[{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":22480,"status":"ok","timestamp":1675269585564,"user":{"displayName":"marti Xooo","userId":"17000102553335328898"},"user_tz":-60},"id":"O-wrMg3ahVxy","outputId":"7f8d45e0-361c-4e5e-f6d9-4edb6a2b505f"},"outputs":[{"name":"stdout","output_type":"stream","text":["Mounted at /content/gdrive\n"]}],"source":["from google.colab import drive\n","drive.mount('/content/gdrive', force_remount=True)"]},{"cell_type":"code","execution_count":2,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":27,"status":"ok","timestamp":1675269585568,"user":{"displayName":"marti Xooo","userId":"17000102553335328898"},"user_tz":-60},"id":"TwwrZqPohp_p","outputId":"02bbfe66-a4a9-44fc-a9bf-f129791b6cd4"},"outputs":[{"name":"stdout","output_type":"stream","text":["/content/gdrive/MyDrive/WKO_PROJECT_NEW\n"]}],"source":["cd gdrive/MyDrive/WKO_PROJECT_NEW"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"background_save":true,"base_uri":"https://localhost:8080/"},"id":"V5t8Et8adgGW"},"outputs":[{"name":"stdout","output_type":"stream","text":["\u001b[34m\u001b[1mdetect: \u001b[0mweights=['yolov5/runs/train/exp16/weights/last.pt'], source=input.mp4, data=yolov5/data/coco128.yaml, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=, view_img=False, save_txt=False, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=yolov5/runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1\n","\u001b[31m\u001b[1mrequirements:\u001b[0m YOLOv5 requirements \"gitpython\" \"ipython\" not found, attempting AutoUpdate...\n","Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n","Collecting gitpython\n","  Downloading GitPython-3.1.30-py3-none-any.whl (184 kB)\n","     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 184.0/184.0 KB 4.9 MB/s eta 0:00:00\n","Requirement already satisfied: ipython in /usr/local/lib/python3.8/dist-packages (7.9.0)\n","Collecting gitdb\u003c5,\u003e=4.0.1\n","  Downloading gitdb-4.0.10-py3-none-any.whl (62 kB)\n","     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 62.7/62.7 KB 7.2 MB/s eta 0:00:00\n","Requirement already satisfied: pickleshare in /usr/local/lib/python3.8/dist-packages (from ipython) (0.7.5)\n","Requirement already satisfied: pygments in /usr/local/lib/python3.8/dist-packages (from ipython) (2.6.1)\n","Requirement already satisfied: prompt-toolkit\u003c2.1.0,\u003e=2.0.0 in /usr/local/lib/python3.8/dist-packages (from ipython) (2.0.10)\n","Requirement already satisfied: decorator in /usr/local/lib/python3.8/dist-packages (from ipython) (4.4.2)\n","Requirement already satisfied: backcall in /usr/local/lib/python3.8/dist-packages (from ipython) (0.2.0)\n","Requirement already satisfied: pexpect in /usr/local/lib/python3.8/dist-packages (from ipython) (4.8.0)\n","Collecting jedi\u003e=0.10\n","  Downloading jedi-0.18.2-py2.py3-none-any.whl (1.6 MB)\n","     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.6/1.6 MB 31.9 MB/s eta 0:00:00\n","Requirement already satisfied: setuptools\u003e=18.5 in /usr/local/lib/python3.8/dist-packages (from ipython) (57.4.0)\n","Requirement already satisfied: traitlets\u003e=4.2 in /usr/local/lib/python3.8/dist-packages (from ipython) (5.7.1)\n","Collecting smmap\u003c6,\u003e=3.0.1\n","  Downloading smmap-5.0.0-py3-none-any.whl (24 kB)\n","Requirement already satisfied: parso\u003c0.9.0,\u003e=0.8.0 in /usr/local/lib/python3.8/dist-packages (from jedi\u003e=0.10-\u003eipython) (0.8.3)\n","Requirement already satisfied: six\u003e=1.9.0 in /usr/local/lib/python3.8/dist-packages (from prompt-toolkit\u003c2.1.0,\u003e=2.0.0-\u003eipython) (1.15.0)\n","Requirement already satisfied: wcwidth in /usr/local/lib/python3.8/dist-packages (from prompt-toolkit\u003c2.1.0,\u003e=2.0.0-\u003eipython) (0.2.5)\n","Requirement already satisfied: ptyprocess\u003e=0.5 in /usr/local/lib/python3.8/dist-packages (from pexpect-\u003eipython) (0.7.0)\n","Installing collected packages: smmap, jedi, gitdb, gitpython\n","Successfully installed gitdb-4.0.10 gitpython-3.1.30 jedi-0.18.2 smmap-5.0.0\n","\n","\u001b[31m\u001b[1mrequirements:\u001b[0m 2 packages updated per /content/gdrive/MyDrive/WKO_PROJECT_NEW/yolov5/requirements.txt\n","\u001b[31m\u001b[1mrequirements:\u001b[0m ⚠️ \u001b[1mRestart runtime or rerun command for updates to take effect\u001b[0m\n","\n","YOLOv5 🚀 v7.0-72-g064365d Python-3.8.10 torch-1.13.1+cu116 CPU\n","\n","Fusing layers... \n","YOLOv5s summary: 157 layers, 7018216 parameters, 0 gradients\n","video 1/1 (1/452) /content/gdrive/MyDrive/WKO_PROJECT_NEW/input.mp4: 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/content/gdrive/MyDrive/WKO_PROJECT_NEW/input.mp4: 384x640 1 no_mask, 6 masks, 237.6ms\n","video 1/1 (430/452) /content/gdrive/MyDrive/WKO_PROJECT_NEW/input.mp4: 384x640 1 no_mask, 6 masks, 245.6ms\n","video 1/1 (431/452) /content/gdrive/MyDrive/WKO_PROJECT_NEW/input.mp4: 384x640 1 no_mask, 6 masks, 227.9ms\n","video 1/1 (432/452) /content/gdrive/MyDrive/WKO_PROJECT_NEW/input.mp4: 384x640 1 no_mask, 7 masks, 226.1ms\n","video 1/1 (433/452) /content/gdrive/MyDrive/WKO_PROJECT_NEW/input.mp4: 384x640 1 no_mask, 4 masks, 225.0ms\n","video 1/1 (434/452) /content/gdrive/MyDrive/WKO_PROJECT_NEW/input.mp4: 384x640 1 no_mask, 4 masks, 234.9ms\n","video 1/1 (435/452) /content/gdrive/MyDrive/WKO_PROJECT_NEW/input.mp4: 384x640 1 no_mask, 4 masks, 220.4ms\n","video 1/1 (436/452) /content/gdrive/MyDrive/WKO_PROJECT_NEW/input.mp4: 384x640 1 no_mask, 6 masks, 234.0ms\n","video 1/1 (437/452) /content/gdrive/MyDrive/WKO_PROJECT_NEW/input.mp4: 384x640 1 no_mask, 5 masks, 224.6ms\n","video 1/1 (438/452) /content/gdrive/MyDrive/WKO_PROJECT_NEW/input.mp4: 384x640 1 no_mask, 5 masks, 233.5ms\n","video 1/1 (439/452) /content/gdrive/MyDrive/WKO_PROJECT_NEW/input.mp4: 384x640 1 no_mask, 7 masks, 225.0ms\n","video 1/1 (440/452) /content/gdrive/MyDrive/WKO_PROJECT_NEW/input.mp4: 384x640 1 no_mask, 7 masks, 237.1ms\n","video 1/1 (441/452) /content/gdrive/MyDrive/WKO_PROJECT_NEW/input.mp4: 384x640 1 no_mask, 8 masks, 229.4ms\n","video 1/1 (442/452) /content/gdrive/MyDrive/WKO_PROJECT_NEW/input.mp4: 384x640 2 no_masks, 7 masks, 223.0ms\n","video 1/1 (443/452) /content/gdrive/MyDrive/WKO_PROJECT_NEW/input.mp4: 384x640 3 no_masks, 7 masks, 222.0ms\n","video 1/1 (444/452) /content/gdrive/MyDrive/WKO_PROJECT_NEW/input.mp4: 384x640 2 no_masks, 8 masks, 235.3ms\n","video 1/1 (445/452) /content/gdrive/MyDrive/WKO_PROJECT_NEW/input.mp4: 384x640 2 no_masks, 7 masks, 228.1ms\n","Speed: 0.9ms pre-process, 232.7ms inference, 0.8ms NMS per image at shape (1, 3, 640, 640)\n","Results saved to \u001b[1myolov5/runs/detect/exp5\u001b[0m\n"]}],"source":["! python3 yolov5/detect.py --source input.mp4 --weights yolov5/runs/train/exp16/weights/last.pt"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"1HWeIZG32VSh"},"outputs":[],"source":["! python3 yolov5/detect.py --source oxf.mp4 --weights yolov5/runs/train/exp16/weights/last.pt"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"N_Ahmnn52XlM"},"outputs":[],"source":["! python3 yolov5/detect.py --source oxf2.mp4 --weights yolov5/runs/train/exp16/weights/last.pt"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":8059,"status":"ok","timestamp":1675114361886,"user":{"displayName":"marti Xooo","userId":"17000102553335328898"},"user_tz":-60},"id":"NE-eA9FohsAK","outputId":"b5a8e9a5-b9a0-4120-df06-d0dafcbd1783"},"outputs":[{"name":"stdout","output_type":"stream","text":["\u001b[34m\u001b[1mdetect: \u001b[0mweights=['yolov5/runs/train/exp8/weights/last.pt'], source=mask_dataset/images/maksssksksss788.png, data=yolov5/data/coco128.yaml, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=, view_img=False, save_txt=False, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=yolov5/runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1\n","YOLOv5 🚀 v7.0-72-g064365d Python-3.8.10 torch-1.13.1+cu116 CPU\n","\n","Fusing layers... \n","YOLOv5s summary: 157 layers, 7018216 parameters, 0 gradients\n","image 1/1 /content/gdrive/MyDrive/WKO_PROJECT_NEW/mask_dataset/images/maksssksksss788.png: 448x640 5 1s, 500.2ms\n","Speed: 1.1ms pre-process, 500.2ms inference, 1.7ms NMS per image at shape (1, 3, 640, 640)\n","Results saved to \u001b[1myolov5/runs/detect/exp2\u001b[0m\n"]}],"source":["! python3 yolov5/detect.py --source mask_dataset/images/maksssksksss788.png --weights yolov5/runs/train/exp8/weights/last.pt"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":6974,"status":"ok","timestamp":1675114931890,"user":{"displayName":"marti Xooo","userId":"17000102553335328898"},"user_tz":-60},"id":"kePati08oR6J","outputId":"8b0c5856-4794-4051-d895-f7d88a2cf129"},"outputs":[{"name":"stdout","output_type":"stream","text":["\u001b[34m\u001b[1mdetect: \u001b[0mweights=['yolov5/runs/train/exp8/weights/best.pt'], source=mask_dataset/images/maksssksksss787.png, data=yolov5/data/coco128.yaml, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=, view_img=False, save_txt=False, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=yolov5/runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1\n","YOLOv5 🚀 v7.0-72-g064365d Python-3.8.10 torch-1.13.1+cu116 CPU\n","\n","Fusing layers... \n","YOLOv5s summary: 157 layers, 7018216 parameters, 0 gradients\n","image 1/1 /content/gdrive/MyDrive/WKO_PROJECT_NEW/mask_dataset/images/maksssksksss787.png: 480x640 3 1s, 300.6ms\n","Speed: 1.1ms pre-process, 300.6ms inference, 1.3ms NMS per image at shape (1, 3, 640, 640)\n","Results saved to \u001b[1myolov5/runs/detect/exp3\u001b[0m\n"]}],"source":["! python3 yolov5/detect.py --source mask_dataset/images/maksssksksss787.png --weights yolov5/runs/train/exp8/weights/best.pt"]}],"metadata":{"colab":{"authorship_tag":"ABX9TyOlJGT9fwPaEIvolcpQ7hPL","name":"","version":""},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"name":"python"}},"nbformat":4,"nbformat_minor":0}