{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1992223c",
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   "source": [
    "import cv2\n",
    "import numpy as np\n",
    "from keras.models import load_model\n",
    "\n",
    "# Load model\n",
    "model = load_model(\"load's path\")\n",
    "\n",
    "# Emotion labels (adjust if needed)\n",
    "emotion_labels = {\n",
    "    0: \"Angry\",\n",
    "    1: \"Happy\",\n",
    "    2: \"Neutral\",\n",
    "    3: \"Sad\",\n",
    "    4: \"Surprised\"\n",
    "}\n",
    "\n",
    "# Load face detector\n",
    "face_cascade = cv2.CascadeClassifier(\"path\")\n",
    "\n",
    "# Open webcam\n",
    "cap = cv2.VideoCapture(0)\n",
    "\n",
    "while True:\n",
    "    ret, frame = cap.read()\n",
    "    if not ret:\n",
    "        break\n",
    "\n",
    "    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\n",
    "    faces = face_cascade.detectMultiScale(\n",
    "        gray, scaleFactor=1.3, minNeighbors=5\n",
    "    )\n",
    "\n",
    "    for (x, y, w, h) in faces:\n",
    "        face = gray[y:y+h, x:x+w]\n",
    "        face = cv2.resize(face, (48, 48))\n",
    "        face = face / 255.0\n",
    "        face = face.reshape(1, 48, 48, 1)\n",
    "\n",
    "        prediction = model.predict(face, verbose=0)\n",
    "        emotion = emotion_labels[np.argmax(prediction)]\n",
    "\n",
    "        # Draw rectangle and label\n",
    "        cv2.rectangle(frame, (x,y), (x+w,y+h), (0,255,0), 2)\n",
    "        cv2.putText(\n",
    "            frame,\n",
    "            emotion,\n",
    "            (x, y-10),\n",
    "            cv2.FONT_HERSHEY_SIMPLEX,\n",
    "            0.9,\n",
    "            (0,255,0),\n",
    "            2\n",
    "        )\n",
    "\n",
    "    cv2.imshow(\"Real-Time Emotion Detection\", frame)\n",
    "\n",
    "    if cv2.waitKey(1) & 0xFF == ord('q'):\n",
    "        break\n",
    "\n",
    "\n",
    "cv2.destroyAllWindows()\n",
    "cap.release()"
   ]
  }
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