testing.ipynb

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    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[1], line 21\u001b[0m\n\u001b[0;32m     18\u001b[0m faces \u001b[38;5;241m=\u001b[39m faceCascade\u001b[38;5;241m.\u001b[39mdetectMultiScale(gray, \u001b[38;5;241m1.2\u001b[39m, \u001b[38;5;241m5\u001b[39m)\n\u001b[0;32m     20\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m (x, y, w, h) \u001b[38;5;129;01min\u001b[39;00m faces:\n\u001b[1;32m---> 21\u001b[0m     Id, conf \u001b[38;5;241m=\u001b[39m \u001b[43mrecognizer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpredict\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgray\u001b[49m\u001b[43m[\u001b[49m\u001b[43my\u001b[49m\u001b[43m:\u001b[49m\u001b[43my\u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43mh\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mx\u001b[49m\u001b[43m:\u001b[49m\u001b[43mx\u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43mw\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     23\u001b[0m     \u001b[38;5;66;03m# If confidence is above a certain threshold, consider the face identified\u001b[39;00m\n\u001b[0;32m     24\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m conf \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m50\u001b[39m:\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
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   "source": [
    "import cv2\n",
    "import numpy as np\n",
    "\n",
    "# Ensure you have the `cv2.face` module available\n",
    "recognizer = cv2.face.LBPHFaceRecognizer_create() \n",
    "recognizer.read('TrainingImageLabel/trainner.yml')\n",
    "\n",
    "cascadePath = \"haarcascade_frontalface_default.xml\"\n",
    "faceCascade = cv2.CascadeClassifier(cascadePath)\n",
    "font = cv2.FONT_HERSHEY_SIMPLEX\n",
    "\n",
    "# Start video capture\n",
    "cam = cv2.VideoCapture(0)\n",
    "\n",
    "while True:\n",
    "    ret, im = cam.read()\n",
    "    gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)\n",
    "    faces = faceCascade.detectMultiScale(gray, 1.2, 5)\n",
    "\n",
    "    for (x, y, w, h) in faces:\n",
    "        Id, conf = recognizer.predict(gray[y:y+h, x:x+w])\n",
    "\n",
    "        # If confidence is above a certain threshold, consider the face identified\n",
    "        if conf < 50:\n",
    "            cv2.putText(im, f\"ID: {Id} Conf: {round(100 - conf, 2)}%\", (x, y - 10), font, 0.8, (0, 255, 0), 2)\n",
    "        else:\n",
    "            Id = \"Unknown\"\n",
    "            cv2.putText(im, Id, (x, y - 10), font, 0.8, (0, 0, 255), 2)\n",
    "\n",
    "        # Draw a rectangle around the face\n",
    "        cv2.rectangle(im, (x, y), (x + w, y + h), (255, 0, 0), 2)\n",
    "\n",
    "    cv2.imshow('Face Recognition', im)\n",
    "    if cv2.waitKey(10) & 0xFF == ord('q'):\n",
    "        break\n",
    "\n",
    "# Release the camera and close all OpenCV windows\n",
    "cam.release()\n",
    "cv2.destroyAllWindows()\n"
   ]
  },
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   "source": []
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