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from flask import Flask, request, jsonify | |
import cv2 | |
import speech_recognition as sr | |
from deepface import DeepFace | |
app = Flask(__name__) | |
def analyze_face(): | |
file = request.files['video'] | |
video_path = "uploaded_video.mp4" | |
file.save(video_path) | |
cap = cv2.VideoCapture(video_path) | |
emotions = [] | |
while True: | |
ret, frame = cap.read() | |
if not ret: | |
break | |
analysis = DeepFace.analyze(frame, actions=['emotion']) | |
emotions.append(analysis[0]['dominant_emotion']) | |
cap.release() | |
return jsonify({"emotions": emotions}) | |
def analyze_speech(): | |
file = request.files['audio'] | |
audio_path = "uploaded_audio.wav" | |
file.save(audio_path) | |
recognizer = sr.Recognizer() | |
with sr.AudioFile(audio_path) as source: | |
audio = recognizer.record(source) | |
text = recognizer.recognize_google(audio) | |
return jsonify({"transcribed_text": text}) | |
if __name__ == '__main__': | |
app.run(debug=True) | |