使用 FFMPEG 自动剪辑视频

log_level=error  #只打印错误logsrc_video=xxx  # 要剪辑的视频dst_video=yyy  # 要保存的视频start_time="00:00:10"  # 要开始剪辑的时间，格式为HH:MM:SS.ffffff。00:00:10表示从第10秒开始剪辑，直到结尾
ffmpeg.exe -v "${log_level}" -ss "${start_time}" -accurate_seek -i ${src_video} -codec copy -avoid_negative_ts 0 -y "${dst_video}"

import tracebackimport ffmpy3
def cut(src_video, dst_video, ss: str, t: str = '', replace=True, log_level='error', avoid_negative_ts=0):    """    :param src_video: 要剪辑的视频    :param dst_video: 保存剪辑好的视频    :param ss: 要开始剪辑的时间，格式为HH:MM:SS.ffffff    :param t: 要剪辑的时长，不加则直到结尾    :param replace: 保存时替换已存在的文件    :param log_level: ffmpeg输出log级别    :param avoid_negative_ts: 官网建议是1，但效果并不好，有7秒无法剪辑掉，所以设成0    :return:    """    log_levels = ['quiet', 'panic', 'fatal', 'error', 'warning', 'info', 'verbose', 'debug', 'trace']    assert log_level in log_levels, f'The log level must in {log_level}'
    try:        input_params = list()        input_params.extend(['-v', log_level])        input_params.extend(['-ss', ss])        if t:            input_params.extend(['-t', t])        input_params.append('-accurate_seek')
        out_params = list()        out_params.extend(['-codec', 'copy'])        out_params.extend(['-avoid_negative_ts', f'{avoid_negative_ts}'])        if replace:            out_params.append('-y')
        ff = ffmpy3.FFmpeg(            inputs={src_video: input_params},            outputs={dst_video: out_params}        )        print(f'==> 剪辑命令: {ff.cmd}')        ff.run()        print(f'==> 已完成 {src_video} 到 {dst_video} 的剪辑')    except ffmpy3.FFRuntimeError:        print(traceback.format_exc())

import jsonimport osimport subprocessimport timeimport traceback
import cv2  # pip install opencv-pythonimport ffmpy3  # pip install ffmpy3from skimage.metrics import structural_similarity as ssim  # pip install scikit-image

class VideoCut:    white_cat = 'captures/white_cat.jpg'  # 比对模板图片1    black_cat = 'captures/black_cat.jpg'  # 比对模板图片2    white_cat_location = ((742, 2), (934, 116))  # 指定图片的比对区域    black_cat_location = ((698, 801), (975, 916))  # 指定图片的比对区域    white_cat_wh = (192, 114)  # 比对区域的宽度    black_cat_wh = (277, 115)  # 比对区域的宽度
    class Video:        def __init__(self, name, json_result_str):            self.name = name            data = json.loads(json_result_str).get('streams')[0]            self.width = data.get('width')            self.height = data.get('height')            self.frame_rate_str = data.get('r_frame_rate')            self.frame_rate = eval(self.frame_rate_str)            self.duration_ts = data.get('duration_ts')            self.duration = float(data.get('duration'))            self.total_frames = data.get('nb_frames')
        def __str__(self):            return f'\tname: {self.name}\n' \                   f'\twidth: {self.width}, height: {self.height}\n' \                   f'\tframes: {self.total_frames}\n' \                   f'\tframe_rate: {self.frame_rate}帧/秒\n' \                   f'\tduration: {self.duration}秒'
    @staticmethod    def crop(img_path_or_obj, roi: [list, tuple] = None):        img = cv2.imread(img_path_or_obj) if isinstance(img_path_or_obj, str) else img_path_or_obj        if roi:            (min_x, min_y), (max_x, max_y) = roi            img = img[min_y: max_y, min_x: max_x]        return img
    @staticmethod    def parse_video_info(video, ffprobe_path=r'H:\ffmpeg\bin\ffprobe.exe'):        """不输出log，并返回json"""        command = f'{ffprobe_path} -v quiet -print_format json -show_format -show_streams "{video}"'        value = subprocess.check_output(command)        return VideoCut.Video(video, value)
    @staticmethod    def cut(src_video, dst_video, ss: str, t: str = '', replace=True, log_level='error', avoid_negative_ts=0):        """        :param src_video: 要剪辑的视频        :param dst_video: 保存剪辑好的视频        :param ss: 要开始剪辑的时间，格式为HH:MM:SS.ffffff        :param t: 要剪辑的时长，不加则直到结尾        :param replace: 保存时替换已存在的文件        :param log_level: ffmpeg输出log级别        :param avoid_negative_ts: 官网建议是1，但效果并不好，有7秒无法剪辑掉，所以设成0        :return:        """        log_levels = ['quiet', 'panic', 'fatal', 'error', 'warning', 'info', 'verbose', 'debug', 'trace']        assert log_level in log_levels, f'The log level must in {log_level}'
        try:            input_params = list()            input_params.extend(['-v', log_level])            input_params.extend(['-ss', ss])            if t:                input_params.extend(['-t', t])            input_params.append('-accurate_seek')
            out_params = list()            out_params.extend(['-codec', 'copy'])            out_params.extend(['-avoid_negative_ts', f'{avoid_negative_ts}'])            if replace:                out_params.append('-y')
            ff = ffmpy3.FFmpeg(                inputs={                    src_video: input_params},                outputs={dst_video: out_params}            )            print(f'==> 剪辑命令: {ff.cmd}')            ff.run()            print(f'==> 已完成 {src_video} 到 {dst_video} 的剪辑')        except ffmpy3.FFRuntimeError:            print(traceback.format_exc())            pass
    @staticmethod    def read_video(video, video_info=None):        """解析出要剪辑的时长"""        video_info = VideoCut.parse_video_info(video) if video_info is None else video_info        vc = cv2.VideoCapture(video)        if vc.isOpened():            assert int(video_info.total_frames) == vc.get(cv2.CAP_PROP_FRAME_COUNT)            cn = 0            ret = True            t1 = time.time()            num = 0            while ret:                ret, img = vc.read()                if not ret:                    break                num += 1                if VideoCut.skip(img)[0]:                    cn += 1                    if cn == 1:                        print(f'==> 检测到跳过帧：{cn}', end=' ', flush=True)                    else:                        print(f'{cn}', end=' ', flush=True)                else:                    print('')                    break            t2 = time.time()            ss, ss_str = None, '00:00:00:0'            if num != 0 and cn != 0:                ss = round(cn / video_info.frame_rate, 6)                ss_cp = ss                ms = str(ss).split('.')[1] if str(ss).split('.')[1] else '0'                h = int(ss / 3600)                h = str(h).rjust(2, '0')                ss = ss % 3600                m = int(ss / 60)                m = str(m).rjust(2, '0')                s = int(ss % 60)                s = str(s).rjust(2, '0') + '.' + ms                ss_str = f'{h}:{m}:{s}'                print(f'==> 已检测开始帧: {num}，共须跳过{cn}帧，即跳过{ss_cp}秒->{ss_str}， 检测耗时：{t2 - t1}秒')            else:                print(f'==> 无法检测开始帧和跳过帧，检测耗时：{t2 - t1}秒')            vc.release()            return ss, ss_str
    @staticmethod    def skip(img_path_or_obj, save_path=None, w_score=0.9, h_score=0.9, print_flag=False):        black_cat_img = VideoCut.crop(img_path_or_obj, roi=VideoCut.black_cat_location)        white_cat_img = VideoCut.crop(img_path_or_obj, roi=VideoCut.white_cat_location)        base_black_cat_img = VideoCut.crop(VideoCut.black_cat)        base_white_cat_img = VideoCut.crop(VideoCut.white_cat)        assert black_cat_img.shape[:2][::-1] == VideoCut.black_cat_wh        assert white_cat_img.shape[:2][::-1] == VideoCut.white_cat_wh        assert base_black_cat_img.shape[:2][::-1] == VideoCut.black_cat_wh        assert base_white_cat_img.shape[:2][::-1] == VideoCut.white_cat_wh
        white_score = ssim(base_white_cat_img, white_cat_img, multichannel=True)        black_score = ssim(base_black_cat_img, black_cat_img, multichannel=True)        if print_flag:            print(f'{img_path_or_obj}, white score: {white_score}, black score: {black_score}')
        if save_path:            name = os.path.split(img_path_or_obj)[1]            img = VideoCut.read_img(img_path_or_obj)            (min_x, min_y), (max_x, max_y) = VideoCut.white_cat_location            img[min_y: max_y, min_x: max_x] = white_cat_img            cv2.putText(img, f'score: {white_score}', (max_x, max_y), cv2.FONT_HERSHEY_COMPLEX, 2.0, (100, 200, 200), 4)
            (min_x, min_y), (max_x, max_y) = VideoCut.black_cat_location            img[min_y: max_y, min_x: max_x] = black_cat_img            cv2.putText(img, f'score: {black_score}', (max_x, min_y), cv2.FONT_HERSHEY_COMPLEX, 2.0, (100, 200, 200), 4)            cv2.imwrite(save_path + '\\' + name, img)        wr, br = white_score >= w_score, black_score >= h_score        return any([wr, br]), white_score, black_score, white_score >= w_score, black_score >= h_score
    @staticmethod    def auto_cut(src_video, dst_video, wait=0, t: str = '', replace=True, log_level='error'):        """自动精准剪辑视频"""        if wait > 0:            print(f'==> 先睡{wait}秒后再剪辑视频')            time.sleep(wait)
        if os.path.exists(src_video):            video_info = VideoCut.parse_video_info(src_video)            print(f'==> 原始视频信息如下：')            print(video_info)            ss, ss_str = VideoCut.read_video(src_video)            if ss:                VideoCut.cut(src_video, dst_video, ss_str, t, replace, log_level)                video_info = VideoCut.parse_video_info(dst_video)                print(f'==> 剪辑视频信息如下：')                print(video_info)        else:            print(f'==> 要剪辑的视频{src_video}不存在')

if __name__ == '__main__':    VideoCut.auto_cut(r'xxx.mp4', r'yyy.mp4')