facial landmarks detection

gistfile1.ipynb

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   "source": [
    "## install :\n",
    "\n",
    "```shell \n",
    "pip install numpy opencv-python dlib imutils matplotlib jupyter\n",
    "```\n",
    "\n",
    "## shape predictor\n",
    "\n",
    "download this shape predictor file: [link](https://raw.githubusercontent.com/italojs/facial-landmarks-recognition/master/shape_predictor_68_face_landmarks.dat)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from imutils import face_utils\n",
    "import dlib\n",
    "import cv2\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "p = \"shape_predictor_68_face_landmarks.dat\"\n",
    "detector = dlib.get_frontal_face_detector()\n",
    "predictor = dlib.shape_predictor(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "image = cv2.imread(\"./image2.jpg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n",
    "rects = detector(gray, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "rects"
   ]
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   "execution_count": null,
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   "outputs": [],
   "source": [
    "def color(num):\n",
    "    if num < 17:\n",
    "        return 'c'\n",
    "    if num < 22:\n",
    "        return 'b'\n",
    "    if num < 27:\n",
    "        return 'b'\n",
    "    if num < 31:\n",
    "        return 'g'\n",
    "    if num < 36:\n",
    "        return 'g'\n",
    "    if num < 42:\n",
    "        return 'k'\n",
    "    if num < 48:\n",
    "        return 'k'\n",
    "    if num < 61:\n",
    "        return 'r'\n",
    "    if num < 68:\n",
    "        return 'y'"
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   "source": [
    "im_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n",
    "plt.figure(figsize=(20,50))\n",
    "plt.imshow(im_rgb)\n",
    "\n",
    "for (i, rect) in enumerate(rects):\n",
    "    shape = predictor(gray, rect)\n",
    "    shape = face_utils.shape_to_np(shape)\n",
    "\n",
    "    for j, (x, y) in enumerate(shape):\n",
    "        plt.scatter([x], [y], c=color(j))\n",
    "        plt.text(x, y, str(j))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# landmark numbers \n",
    "\n",
    "| test | from |  to  |\n",
    "|:---- | ---- | ---- |\n",
    "| face |  0   |  16  |\n",
    "| eyebrow | 17 | 21 |\n",
    "| eyebrow | 22 | 26 |\n",
    "| nose-up | 27 | 30 | \n",
    "| nose-bot | 31 | 35 |\n",
    "| eye | 36 | 41 |\n",
    "| eye | 42 | 47 |\n",
    "| lip-out | 48 | 60 |\n",
    "| lip-in | 61 | 67 |"
   ]
  }
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