run-time-ppe-detection.ipynb

{
 "cells": [
  {
   "cell_type": "code",
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   "id": "1727a918-665e-4f57-920e-9c0796add3d6",
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    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'cv2'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[1], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mos\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01multralytics\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m YOLO\n\u001b[1;32m      4\u001b[0m \u001b[38;5;66;03m# Load the trained YOLOv8 model\u001b[39;00m\n\u001b[1;32m      5\u001b[0m model \u001b[38;5;241m=\u001b[39m YOLO(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mruns/detect/train/weights/best.pt\u001b[39m\u001b[38;5;124m\"\u001b[39m)  \u001b[38;5;66;03m# Replace with your trained model's path\u001b[39;00m\n",
      "File \u001b[0;32m/opt/anaconda3/lib/python3.12/site-packages/ultralytics/__init__.py:10\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[38;5;66;03m# Set ENV Variables (place before imports)\u001b[39;00m\n\u001b[1;32m      8\u001b[0m os\u001b[38;5;241m.\u001b[39menviron[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mOMP_NUM_THREADS\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m1\u001b[39m\u001b[38;5;124m\"\u001b[39m  \u001b[38;5;66;03m# reduce CPU utilization during training\u001b[39;00m\n\u001b[0;32m---> 10\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01multralytics\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdata\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mexplorer\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mexplorer\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Explorer\n\u001b[1;32m     11\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01multralytics\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mmodels\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m NAS, RTDETR, SAM, YOLO, FastSAM, YOLOWorld\n\u001b[1;32m     12\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01multralytics\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m ASSETS, SETTINGS\n",
      "File \u001b[0;32m/opt/anaconda3/lib/python3.12/site-packages/ultralytics/data/__init__.py:3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# Ultralytics YOLO 🚀, AGPL-3.0 license\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbase\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m BaseDataset\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbuild\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m build_dataloader, build_grounding, build_yolo_dataset, load_inference_source\n\u001b[1;32m      5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdataset\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m (\n\u001b[1;32m      6\u001b[0m     ClassificationDataset,\n\u001b[1;32m      7\u001b[0m     GroundingDataset,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     11\u001b[0m     YOLOMultiModalDataset,\n\u001b[1;32m     12\u001b[0m )\n",
      "File \u001b[0;32m/opt/anaconda3/lib/python3.12/site-packages/ultralytics/data/base.py:12\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mpathlib\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Path\n\u001b[1;32m     10\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtyping\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Optional\n\u001b[0;32m---> 12\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mcv2\u001b[39;00m\n\u001b[1;32m     13\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnp\u001b[39;00m\n\u001b[1;32m     14\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpsutil\u001b[39;00m\n",
      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'cv2'"
     ]
    }
   ],
   "source": [
    "import os\n",
    "from ultralytics import YOLO\n",
    "\n",
    "# Load the trained YOLOv8 model\n",
    "model = YOLO(\"runs/detect/train/weights/best.pt\")  # Replace with your trained model's path\n",
    "\n",
    "# Open the camera\n",
    "cap = cv2.VideoCapture(0)  # 0 is typically the default camera; change if you have multiple cameras\n",
    "\n",
    "# Check if the camera opened successfully\n",
    "if not cap.isOpened():\n",
    "    print(\"Error: Could not open camera.\")\n",
    "    exit()\n",
    "\n",
    "# Loop to continuously get frames from the camera\n",
    "while True:\n",
    "    ret, frame = cap.read()\n",
    "    \n",
    "    if not ret:\n",
    "        print(\"Error: Failed to capture image\")\n",
    "        break\n",
    "    \n",
    "    # Use YOLO model to detect objects in the frame\n",
    "    results = model(frame)\n",
    "    \n",
    "    # Display the results on the frame\n",
    "    annotated_frame = results[0].plot()  # Draws bounding boxes and labels on the image\n",
    "    \n",
    "    # Show the frame with detection\n",
    "    cv2.imshow(\"YOLOv8 Detection\", annotated_frame)\n",
    "    \n",
    "    # Press 'q' to exit the loop\n",
    "    if cv2.waitKey(1) & 0xFF == ord('q'):\n",
    "        break\n",
    "\n",
    "# Release the camera and close all OpenCV windows\n",
    "cap.release()\n",
    "cv2.destroyAllWindows()"
   ]
  },
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   "id": "6b3e9438-e172-4296-8668-e26103e74286",
   "metadata": {},
   "outputs": [],
   "source": []
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