{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ec5da4a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import math\n",
    "import argparse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4dad4d0e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def highlightFace(net, frame, conf_threshold=0.7):\n",
    "    frameOpencvDnn=frame.copy()\n",
    "    frameHeight=frameOpencvDnn.shape[0]\n",
    "    frameWidth=frameOpencvDnn.shape[1]\n",
    "    blob=cv2.dnn.blobFromImage(frameOpencvDnn, 1.0, (300, 300), [104, 117, 123], True, False)\n",
    "    net.setInput(blob)\n",
    "    detections=net.forward()\n",
    "    faceBoxes=[]\n",
    "    for i in range(detections.shape[2]):\n",
    "        confidence=detections[0,0,i,2]\n",
    "        if confidence>conf_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"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c66d9705",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "\n",
    "# Manually handle args to avoid argparse conflict in notebooks\n",
    "image_path = None\n",
    "if len(sys.argv) > 1 and sys.argv[1] == \"--image\":\n",
    "    image_path = sys.argv[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "23f3f3bd",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a0a0146a",
   "metadata": {},
   "outputs": [],
   "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\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6babe782",
   "metadata": {},
   "outputs": [],
   "source": [
    "MODEL_MEAN_VALUES=(78.4263377603, 87.7689143744, 114.895847746)\n",
    "ageList=['(0-2)', '(4-6)', '(8-12)', '(15-20)', '(25-32)', '(38-43)', '(48-53)', '(60-100)']\n",
    "genderList=['Male','Female']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "a78c6ae1",
   "metadata": {},
   "outputs": [],
   "source": [
    "faceNet=cv2.dnn.readNet(faceModel,faceProto)\n",
    "ageNet=cv2.dnn.readNet(ageModel,ageProto)\n",
    "genderNet=cv2.dnn.readNet(genderModel,genderProto)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "dc17d6e7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gender: Female\n",
      "Age: 38-43 years\n"
     ]
    }
   ],
   "source": [
    "image_path = \"woman1.jpg\"  # or None for webcam\n",
    "video = cv2.VideoCapture(image_path if image_path else 0)\n",
    "padding=20\n",
    "while cv2.waitKey(1)<0 :\n",
    "    hasFrame,frame=video.read()\n",
    "    if not hasFrame:\n",
    "        cv2.waitKey()\n",
    "        break\n",
    "    \n",
    "    resultImg,faceBoxes=highlightFace(faceNet,frame)\n",
    "    if not faceBoxes:\n",
    "        print(\"No face detected\")\n",
    "\n",
    "    for faceBox in faceBoxes:\n",
    "        face=frame[max(0,faceBox[1]-padding):\n",
    "                   min(faceBox[3]+padding,frame.shape[0]-1),max(0,faceBox[0]-padding)\n",
    "                   :min(faceBox[2]+padding, frame.shape[1]-1)]\n",
    "\n",
    "        blob=cv2.dnn.blobFromImage(face, 1.0, (227,227), MODEL_MEAN_VALUES, swapRB=False)\n",
    "        genderNet.setInput(blob)\n",
    "        genderPreds=genderNet.forward()\n",
    "        gender=genderList[genderPreds[0].argmax()]\n",
    "        print(f'Gender: {gender}')\n",
    "\n",
    "        ageNet.setInput(blob)\n",
    "        agePreds=ageNet.forward()\n",
    "        age=ageList[agePreds[0].argmax()]\n",
    "        print(f'Age: {age[1:-1]} years')\n",
    "\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"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c4241cec",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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