Computer_Vision_Face_Detection.ipynb

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  {
   "cell_type": "markdown",
   "id": "c40aea48",
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   "source": [
    "# Face Detection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e9728d80",
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4035b647",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the cascade\n",
    "face_cascade = cv2.CascadeClassifier('aman.xml')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "125a6b94",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "< cv2.CascadeClassifier 000002B4511334B0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "face_cascade"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "73fdc46d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# To capture video from webcam.\n",
    "cap = cv2.VideoCapture(0)\n",
    "while True:\n",
    "    # Read the frame\n",
    "    _, img = cap.read()\n",
    "\n",
    "    # Convert to grayscale\n",
    "    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
    "\n",
    "    # Detect the faces\n",
    "    faces = face_cascade.detectMultiScale(gray, 1.1, 4)\n",
    "\n",
    "    # Draw the rectangle around each face\n",
    "    for (x, y, w, h) in faces:\n",
    "        cv2.rectangle(img, (x, y), (x + w, y + h), (50, 50, 4), 10)\n",
    "\n",
    "    # Display\n",
    "    cv2.imshow('img', img)\n",
    "\n",
    "    # Stop if escape key is pressed\n",
    "    k = cv2.waitKey(30) & 0xff\n",
    "    if k == 27:\n",
    "        break\n",
    "\n",
    "# Release the VideoCapture object\n",
    "cap.release()"
   ]
  }
 ],
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