Face detection Using Media Pipe.ipynb

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     "text": [
      "Requirement already satisfied: mediapipe in c:\\users\\abhishek kumar\\anaconda3\\lib\\site-packages (0.8.6.2)\n",
      "Requirement already satisfied: opencv-python in c:\\users\\abhishek kumar\\anaconda3\\lib\\site-packages (4.5.2.52)\n",
      "Requirement already satisfied: absl-py in c:\\users\\abhishek kumar\\anaconda3\\lib\\site-packages (from mediapipe) (0.12.0)\n",
      "Requirement already satisfied: attrs>=19.1.0 in c:\\users\\abhishek kumar\\anaconda3\\lib\\site-packages (from mediapipe) (20.3.0)\n",
      "Requirement already satisfied: six in c:\\users\\abhishek kumar\\anaconda3\\lib\\site-packages (from mediapipe) (1.13.0)\n",
      "Requirement already satisfied: numpy in c:\\users\\abhishek kumar\\anaconda3\\lib\\site-packages (from mediapipe) (1.21.1)\n",
      "Requirement already satisfied: wheel in c:\\users\\abhishek kumar\\anaconda3\\lib\\site-packages (from mediapipe) (0.35.1)\n",
      "Requirement already satisfied: matplotlib in c:\\users\\abhishek kumar\\anaconda3\\lib\\site-packages (from mediapipe) (3.3.1)\n",
      "Requirement already satisfied: protobuf>=3.11.4 in c:\\users\\abhishek kumar\\anaconda3\\lib\\site-packages (from mediapipe) (3.17.0)\n",
      "Requirement already satisfied: opencv-contrib-python in c:\\users\\abhishek kumar\\anaconda3\\lib\\site-packages (from mediapipe) (4.5.3.56)\n",
      "Requirement already satisfied: cycler>=0.10 in c:\\users\\abhishek kumar\\anaconda3\\lib\\site-packages (from matplotlib->mediapipe) (0.10.0)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in c:\\users\\abhishek kumar\\anaconda3\\lib\\site-packages (from matplotlib->mediapipe) (1.3.0)\n",
      "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in c:\\users\\abhishek kumar\\anaconda3\\lib\\site-packages (from matplotlib->mediapipe) (2.4.7)\n",
      "Requirement already satisfied: pillow>=6.2.0 in c:\\users\\abhishek kumar\\anaconda3\\lib\\site-packages (from matplotlib->mediapipe) (8.0.1)\n",
      "Requirement already satisfied: python-dateutil>=2.1 in c:\\users\\abhishek kumar\\anaconda3\\lib\\site-packages (from matplotlib->mediapipe) (2.8.1)\n",
      "Requirement already satisfied: certifi>=2020.06.20 in c:\\users\\abhishek kumar\\anaconda3\\lib\\site-packages (from matplotlib->mediapipe) (2021.5.30)\n"
     ]
    }
   ],
   "source": [
    "!pip install mediapipe opencv-python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import mediapipe as mp\n",
    "import cv2\n",
    "import numpy as np\n",
    "import uuid\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "drawing_details = mp.solutions.drawing_utils\n",
    "hands_details = mp.solutions.hands"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Face detection Using Media Pipe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import mediapipe as mp\n",
    "mp_face_detection = mp.solutions.face_detection\n",
    "mp_drawing = mp.solutions.drawing_utils\n",
    "\n",
    "# For static images:\n",
    "IMAGE_FILES = []\n",
    "with mp_face_detection.FaceDetection(\n",
    "    model_selection=1, min_detection_confidence=0.5) as face_detection:\n",
    "  for idx, file in enumerate(IMAGE_FILES):\n",
    "    image = cv2.imread(file)\n",
    "    # Convert the BGR image to RGB and process it with MediaPipe Face Detection.\n",
    "    results = face_detection.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))\n",
    "\n",
    "    # Draw face detections of each face.\n",
    "    if not results.detections:\n",
    "      continue\n",
    "    annotated_image = image.copy()\n",
    "    for detection in results.detections:\n",
    "      print('Nose tip:')\n",
    "      print(mp_face_detection.get_key_point(\n",
    "          detection, mp_face_detection.FaceKeyPoint.NOSE_TIP))\n",
    "      mp_drawing.draw_detection(annotated_image, detection)\n",
    "    cv2.imwrite('/tmp/annotated_image' + str(idx) + '.png', annotated_image)\n",
    "\n",
    "# For webcam input:\n",
    "cap = cv2.VideoCapture(0)\n",
    "with mp_face_detection.FaceDetection(\n",
    "    model_selection=0, min_detection_confidence=0.5) as face_detection:\n",
    "  while cap.isOpened():\n",
    "    success, image = cap.read()\n",
    "    if not success:\n",
    "      print(\"Ignoring empty camera frame.\")\n",
    "      # If loading a video, use 'break' instead of 'continue'.\n",
    "      continue\n",
    "\n",
    "    # Flip the image horizontally for a later selfie-view display, and convert\n",
    "    # the BGR image to RGB.\n",
    "    image = cv2.cvtColor(cv2.flip(image, 1), cv2.COLOR_BGR2RGB)\n",
    "    # To improve performance, optionally mark the image as not writeable to\n",
    "    # pass by reference.\n",
    "    image.flags.writeable = False\n",
    "    results = face_detection.process(image)\n",
    "\n",
    "    # Draw the face detection annotations on the image.\n",
    "    image.flags.writeable = True\n",
    "    image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)\n",
    "    if results.detections:\n",
    "      for detection in results.detections:\n",
    "        mp_drawing.draw_detection(image, detection)\n",
    "    cv2.imshow('MediaPipe Face Detection', image)\n",
    "    if cv2.waitKey(5) & 0xFF == 27:\n",
    "      break\n",
    "cap.release()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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