face_recog.ipynb

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     "text": [
      "\n",
      " [INFO] Exiting Program and cleanup stuff\n"
     ]
    }
   ],
   "source": [
    "#Importing of all the important libraries required for the face recognition\n",
    "import cv2                                \n",
    "import numpy as np\n",
    "import os \n",
    "\n",
    "#Using of the LBPH Face recognizer technique for recognizing the faces in webcam through \n",
    "recognizer = cv2.face.LBPHFaceRecognizer_create()\n",
    "recognizer.read('trainer/trainer.yml')\n",
    "cascadePath = \"haarcascade_frontalface_default.xml\"\n",
    "faceCascade = cv2.CascadeClassifier(cascadePath);\n",
    "\n",
    "font = cv2.FONT_HERSHEY_SIMPLEX\n",
    "\n",
    "#iniciate id counter\n",
    "id = 0\n",
    "\n",
    "# names related to ids: example ==> Shiladitya: id=1,  etc\n",
    "names = ['None', 'Shiladitya','Tulip'] \n",
    "\n",
    "# Initialize and start realtime video capture\n",
    "cam = cv2.VideoCapture(0)\n",
    "cam.set(3, 640) # set video widht\n",
    "cam.set(4, 480) # set video height\n",
    "\n",
    "# Define min window size to be recognized as a face\n",
    "minW = 0.1*cam.get(3)\n",
    "minH = 0.1*cam.get(4)\n",
    "\n",
    "while True:\n",
    "\n",
    "    ret, img =cam.read()\n",
    "    img = cv2.flip(img, 1)\n",
    "\n",
    "    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)\n",
    "\n",
    "    faces = faceCascade.detectMultiScale( \n",
    "        gray,\n",
    "        scaleFactor = 1.2,\n",
    "        minNeighbors = 5,\n",
    "        minSize = (int(minW), int(minH)),\n",
    "       )\n",
    "\n",
    "    for(x,y,w,h) in faces:\n",
    "\n",
    "        cv2.rectangle(img, (x,y), (x+w,y+h), (0,255,0), 2)\n",
    "\n",
    "        id, confidence = recognizer.predict(gray[y:y+h,x:x+w])\n",
    "\n",
    "        # Check if confidence is less than 100 ==> \"0\" is perfect match \n",
    "        if (confidence < 100):\n",
    "            id = names[id]\n",
    "            confidence = \"  {0}%\".format(round(100 - confidence))\n",
    "        else:\n",
    "            id = \"unknown\"\n",
    "            confidence = \"  {0}%\".format(round(100 - confidence))\n",
    "        \n",
    "        cv2.putText(img, str(id), (x+5,y-5), font, 1, (255,255,255), 2)\n",
    "        cv2.putText(img, str(confidence), (x+5,y+h-5), font, 1, (255,255,0), 1)  \n",
    "    \n",
    "    cv2.imshow('camera',img) \n",
    "\n",
    "    k = cv2.waitKey(10) & 0xff # Press 'ESC' for exiting video\n",
    "    if k == 27:\n",
    "        break\n",
    "\n",
    "print(\"\\n [INFO] Exiting Program and cleanup stuff\")\n",
    "cam.release()\n",
    "cv2.destroyAllWindows()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": []
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