cv2 提取帧图片

我不是女神ヾ 2023-02-11 07:18 7阅读 0赞

提取帧图片，并根据当前时间命名，效果如下：  
![时间段命名][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzM4Njg5Mzk1_size_16_color_FFFFFF_t_70_pic_center]

import cv2
    import os
    from datetime import datetime, timedelta
    
    root_path = 'D:/2root_data/video/'
    files = os.listdir(root_path)
    
    for file in files:
        if file.endswith('.mp4'):
            video_path = root_path + file
            cap = cv2.VideoCapture(video_path)
            now = datetime.now()
    
            fps = int(cap.get(cv2.CAP_PROP_FPS))
            size = (int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)),int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)))
            frame_all = cap.get(cv2.CAP_PROP_FRAME_COUNT)
            print(f'视频时长：{frame_all/fps/60:.1f} 分钟')
            print(f'视频尺寸：{size}')
    
            success, frame  = cap.read()
            # 视频的当前帧
            i = 0
            # 帧率
            timeF = 60
            while success:
                if i % timeF == 0:
                    dt = str(now+timedelta(seconds=i//timeF)).replace(' ', '_').replace('-', '_').replace(':', '_').replace('.', '_')[:-3]
                    floder = root_path + 'image'
                    if not os.path.exists(floder):
                        os.makedirs(floder)
                    newname = floder + '/'  + dt + '.jpg'
                    cv2.imwrite(newname, frame)
                    print(f'保存图片：{newname}')
                i += 1
                # 获取下一帧
                success, frame = cap.read()
            cap.release()

*  下一步改进：根据某几个时间段抽取图片，截取荣耀时刻  
    ![根据某几个时间段抽取图片][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzM4Njg5Mzk1_size_16_color_FFFFFF_t_70_pic_center 1]

> 注意：如果要抽取的图片数量非常多，print 往往增加很多倍的耗时，严重影响效率  
> 由于我 抽取的图片数量不多 且 电脑配置不高 ，加上print 防止CPU一直占满，以缓解电脑卡死状况

import cv2
    import os
    import pandas as pd
    from datetime import datetime,timedelta
    
    def save2frames(video, start_end_time_list):
        video_path = root_path + video
        cap = cv2.VideoCapture(video_path)
        now = datetime.now()
        FPS = int(cap.get(cv2.CAP_PROP_FPS))
        size = (int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)),int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)))
        frame_all = cap.get(cv2.CAP_PROP_FRAME_COUNT)
        print(f'视频时长：{frame_all/FPS/60:.1f} 分钟')
        print(f'视频尺寸：{size}')
    
        success, frame = cap.read()
        i = 0  #一个视频里的第几帧
        index = 0 #第几组起始时间
        timeF = 60 # 帧率
        ID, start_time, end_time = start_end_time_list[index]
    
        while success:
            if i >= start_time * FPS:
                if i % timeF == 0:
                    dt = str(now+timedelta(seconds=i//timeF)).replace(' ', '_').replace('-', '_').replace(':', '_').replace('.', '_')[:-3]
                    floder = root_path + 'image'
                    if not os.path.exists(floder):
                        os.makedirs(floder)
                    newname = floder + '/' + dt + '_' + str(index) +'.jpg'
                    cv2.imwrite(newname, frame)
            success, frame = cap.read() #获取下一帧
            i +=1
            # 加上print() 输出图片会变慢，但是CPU占用没有那么高
            print(start_time * FPS, (end_time + 1) * FPS, i)
            if i == (end_time + 1) * FPS:
                index += 1
                if index == len(start_end_time_list):
                    break
                ID, start_time, end_time = start_end_time_list[index]
        cap.release()
    
    def get_seconds(time):
        h, m, s = [int(t) for t in time.split(':')]
        return h*60*60 + m*60 + s
    
    if __name__ == "__main__":
        # 如果读取csv，格式都为字符串 则不用astype进行转换
        # df = pd.read_csv('C:/Users/Desktop/test.csv', encoding='gb18030')
        df = pd.ExcelFile('C:/Users/Desktop/test.xlsx').parse()
        root_path = 'D:/2root_data/video/'
        files = os.listdir(root_path)
        for video, group in df.groupby('视频名称'):
            start_end_time_list = sorted(list(zip(list(group['ID']),
                                    [get_seconds(i)for i in list(group['开始时间'].astype('str'))],
                                    [get_seconds(i)for i in list(group['结束时间'].astype('str'))])), key=lambda y: y)
            print(start_end_time_list)
            save2frames(video, start_end_time_list)

[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzM4Njg5Mzk1_size_16_color_FFFFFF_t_70_pic_center]: https://img-blog.csdnimg.cn/20200522102710562.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzM4Njg5Mzk1,size_16,color_FFFFFF,t_70#pic_center
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzM4Njg5Mzk1_size_16_color_FFFFFF_t_70_pic_center 1]: https://img-blog.csdnimg.cn/20200522102843517.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzM4Njg5Mzk1,size_16,color_FFFFFF,t_70#pic_center