Task4(B3).ipynb

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   "source": [
    "import cv2  \n",
    "import os\n",
    "os.chdir('/home/samrat/Desktop/SoC-FaceRecog/Age-and-Gender-Recognition-main/models')# The location of models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "121b946e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def detectFace(net,frame,confidence_threshold=0.7):\n",
    "    frameOpencvDNN=frame.copy()\n",
    "    #print(frameOpencvDNN.shape)\n",
    "    frameHeight=frameOpencvDNN.shape[0]\n",
    "    frameWidth=frameOpencvDNN.shape[1]\n",
    "    scale=1.0\n",
    "    size=(227,227)#Size of array required by cnn\n",
    "    blob=cv2.dnn.blobFromImage(frameOpencvDNN,scale,size,[124.96,115.97,106.13],swapRB=True,crop=False)\n",
    "    #SwapRB is for changing BGR to RGB\n",
    "    ######################################Pre-processing Done\n",
    "    net.setInput(blob)\n",
    "    detections=net.forward()#Process\n",
    "    #print(detections)\n",
    "    faceBoxes=[]\n",
    "    for i in range(detections.shape[2]):\n",
    "        confidence=detections[0,0,i,2]\n",
    "        if confidence>confidence_threshold:\n",
    "            x1=int(detections[0,0,i,3]*frameWidth)\n",
    "            y1=int(detections[0,0,i,4]*frameHeight)\n",
    "            x2=int(detections[0,0,i,5]*frameWidth)\n",
    "            y2=int(detections[0,0,i,6]*frameHeight)\n",
    "            faceBoxes.append([x1,y1,x2,y2])\n",
    "            cv2.rectangle(frameOpencvDNN,(x1,y1),(x2,y2),(0,255,0),int(round(frameHeight/150)),8)\n",
    "    return frameOpencvDNN,faceBoxes\n",
    "        \n",
    "    \n"
   ]
  },
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   "source": [
    "faceProto='opencv_face_detector.pbtxt'\n",
    "faceModel='opencv_face_detector_uint8.pb'\n",
    "ageProto='age_deploy.prototxt'\n",
    "ageModel='age_net.caffemodel'\n",
    "genderProto='gender_deploy.prototxt'\n",
    "genderModel='gender_net.caffemodel'\n",
    "\n",
    "genderList=['Male','Female']\n",
    "#genderList=['Dumb','Smart']\n",
    "#ageList=['(0-2)','(4-6)','(8-12)','(15-20)','(25-32)','(38-43)','(48-53)','(60-100)']\n",
    "ageList=[1,5,10,18,27,40,50,80]\n",
    "\n",
    "faceNet=cv2.dnn.readNet(faceModel,faceProto)\n",
    "ageNet=cv2.dnn.readNet(ageModel,ageProto)\n",
    "genderNet=cv2.dnn.readNet(genderModel,genderProto)\n",
    "\n",
    "video=cv2.VideoCapture(0)\n",
    "padding=20 #CNN\n",
    "while cv2.waitKey(10)<0:\n",
    "    hasFrame,frame=video.read()\n",
    "    if not hasFrame:\n",
    "        cv2.waitKey()\n",
    "        break\n",
    "        \n",
    "    resultImg,faceBoxes=detectFace(faceNet,frame,0.7)\n",
    "    \n",
    "    if not faceBoxes:\n",
    "        print(\"No face detected\")\n",
    "    \n",
    "    for faceBox in faceBoxes:\n",
    "        face=frame[max(0,faceBox[1]-padding):min(faceBox[3]+padding,frame.shape[0]-1),max(0,faceBox[0]-padding):min(faceBox[2]+padding, frame.shape[1]-1)]\n",
    "        blob=cv2.dnn.blobFromImage(face,1.0,(227,227),[124.96,115.97,106.13],swapRB=True,crop=False)\n",
    "        genderNet.setInput(blob)\n",
    "        genderPreds=genderNet.forward()\n",
    "        gender=genderList[genderPreds[0].argmax()]\n",
    "        \n",
    "        ageNet.setInput(blob)\n",
    "        agePreds=ageNet.forward()\n",
    "        age=0\n",
    "        for i in range(8):\n",
    "            age+=agePreds[0][i]*ageList[i]\n",
    "            #print(agePreds)\n",
    "            #print(age)\n",
    "        age=int(age) \n",
    "        print(age)\n",
    "        cv2.putText(resultImg,f'{gender},{age}',(faceBox[0],faceBox[1]-10),cv2.FONT_HERSHEY_SIMPLEX,0.8,(0,255,255),2,cv2.LINE_AA)\n",
    "        cv2.imshow(\"Detecting age and Gender\",resultImg)\n",
    "        \n",
    "    #Minor indentation bug in source code\n",
    "    if cv2.waitKey(33) & 0xFF == 13:#Enter key\n",
    "        break\n",
    "            \n",
    "cv2.destroyAllWindows()"
   ]
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   "cell_type": "code",
   "execution_count": null,
   "id": "38f91905",
   "metadata": {},
   "outputs": [],
   "source": []
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