人脸表情识别系统

import cv2
import numpy as np
from keras.models import load_model

# 加载预训练的表情识别模型
model = load_model('emotion_recognition_model.h5')

# 定义表情标签
emotion_labels = ['Angry', 'Disgust', 'Fear', 'Happy', 'Sad', 'Surprise', 'Neutral']

# 打开摄像头
cap = cv2.VideoCapture(0)

while True:
    ret, frame = cap.read()
    if not ret:
        break

    # 转换为灰度图像
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # 检测人脸
    faces = cv2.CascadeClassifier('haarcascade_frontalface_default.xml').detectMultiScale(gray, 1.3, 5)

    for (x, y, w, h) in faces:
        roi_gray = gray[y:y+h, x:x+w]
        roi_color = frame[y:y+h, x:x+w]

        # 调整大小为模型输入尺寸
        roi_gray = cv2.resize(roi_gray, (48, 48), interpolation=cv2.INTER_AREA)
        roi_gray = roi_gray.astype('float') / 255.0
        roi_gray = np.expand_dims(roi_gray, axis=0)
        roi_gray = np.expand_dims(roi_gray, axis=-1)

        # 预测表情
        prediction = model.predict(roi_gray)[0]
        emotion_index = np.argmax(prediction)
        emotion = emotion_labels[emotion_index]

        # 绘制结果
        cv2.putText(frame, emotion, (x, y-10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 255, 0), 2)
        cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)

    cv2.imshow('Emotion Recognition', frame)

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()