11.11视频审核推荐

import cv2
import tensorflow as tf

# 加载预训练模型
model = tf.keras.models.load_model('path_to_model.h5')

def preprocess_video(video_path):
    cap = cv2.VideoCapture(video_path)
    frames = []
    while cap.isOpened():
        ret, frame = cap.read()
        if not ret:
            break
        frames.append(frame)
    cap.release()
    return frames

def detect_objects(frames):
    results = []
    for frame in frames:
        img = cv2.resize(frame, (224, 224))  # 调整大小以适应模型输入
        img = img / 255.0  # 归一化
        img = tf.expand_dims(img, 0)  # 增加批次维度
        predictions = model.predict(img)
        results.append(predictions)
    return results

video_path = 'example.mp4'
frames = preprocess_video(video_path)
predictions = detect_objects(frames)

for pred in predictions:
    print(pred)