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   "cell_type": "code",
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of detected faces: 1\n",
      "face0.jpg is saved\n"
     ]
    }
   ],
   "source": [
    "# import required libraries\n",
    "import cv2\n",
    "\n",
    "# read the input image\n",
    "img = cv2.imread('data/UAM-Andrzej-Wójtowicz.jpg')\n",
    "\n",
    "# convert to grayscale of each frames\n",
    "gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
    "\n",
    "# read the haarcascade to detect the faces in an image\n",
    "face_cascade = cv2.CascadeClassifier('haarcascades/haarcascade_frontalface_default.xml')\n",
    "\n",
    "# detects faces in the input image\n",
    "faces = face_cascade.detectMultiScale(gray, 1.3, 4)\n",
    "print('Number of detected faces:', len(faces))\n",
    "\n",
    "# loop over all detected faces\n",
    "if len(faces) > 0:\n",
    "   for i, (x, y, w, h) in enumerate(faces):\n",
    "      # To draw a rectangle in a face\n",
    "      cv2.rectangle(img, (x, y), (x + w, y + h), (255, 255, 255), 2)\n",
    "      face = img[y:y + h, x:x + w]\n",
    "      cv2.imshow(\"Cropped Face\", face)\n",
    "      cv2.imwrite(f'face{i}.jpg', face)\n",
    "      print(f\"face{i}.jpg is saved\")\n",
    " \n",
    "# display the image with detected faces\n",
    "cv2.imshow(\"image\", img)"
   ]
  }
 ],
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