视频智能分析试用

import cv2
import tensorflow as tf

# 加载预训练的人脸检测模型
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')

# 加载自定义的人脸识别模型
model = tf.keras.models.load_model('face_recognition_model.h5')

cap = cv2.VideoCapture(0)

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

    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))

    for (x, y, w, h) in faces:
        roi_gray = gray[y:y+h, x:x+w]
        roi_gray = cv2.resize(roi_gray, (48, 48))
        roi_gray = roi_gray / 255.0
        roi_gray = tf.expand_dims(roi_gray, axis=0)
        roi_gray = tf.expand_dims(roi_gray, axis=-1)

        predictions = model.predict(roi_gray)
        label = tf.argmax(predictions, axis=1).numpy()[0]

        cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)
        cv2.putText(frame, f'Label: {label}', (x, y-10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (255, 0, 0), 2)

    cv2.imshow('Video', frame)

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

cap.release()
cv2.destroyAllWindows()