百万点赞怎么来？Python批量制作抖音的卡点视频原来这么简单！

# opencv 用于剪辑视频
pip3 install opencv-python

# 分离BGM、合并视频和BGM
pip3 install ffmpeg

# 视频源
videoCapture = cv2.VideoCapture(soure_filename)

# 获取视频的帧率
fps = videoCapture.get(cv2.CAP_PROP_FPS)

# 获取视频的分辨率
img_size = (int(videoCapture.get(cv2.CAP_PROP_FRAME_WIDTH)),
                int(videoCapture.get(cv2.CAP_PROP_FRAME_HEIGHT)))

# 构建一个视频写入对象
video_writer = cv2.VideoWriter(output_filename, cv2.VideoWriter_fourcc('X', 'V', 'I', 'D'), fps, img_size)

# 开始帧和结束帧
start_frame = fps * start_time
end_frame = start_frame + peroid * fps

# 循环读取视频帧，只写入开始帧和结束帧之间的帧数据
while True:
      success, frame = videoCapture.read()  
      if success:
            i += 1
            if start_frame <= i <= end_frame:
                # 将截取到的画面写入“新视频”
                video_writer.write(frame)
      else:
            break
# 释放资源
videoCapture.release()

# 视频格式：MP4
fourcc = cv2.VideoWriter_fourcc('m', 'p', '4', 'v')

# 构建写入对象
video = cv2.VideoWriter(output_video_path, fourcc, fps, img_size)

# 每一张图片要写入的帧数目
total_count = math.ceil(fps / 2)

def resize_image(target_image_path, target_size):
    """
    调整图片大小，缺失的部分用黑色填充
    :param target_image_path: 图片路径
    :param target_size: 分辨率大小
    :return:
    """
    image = Image.open(target_image_path)

    iw, ih = image.size  # 原始图像的尺寸
    w, h = target_size  # 目标图像的尺寸
    scale = min(w / iw, h / ih)  # 转换的最小比例

    # 保证长或宽，至少一个符合目标图像的尺寸
    nw = int(iw * scale)
    nh = int(ih * scale)

    image = image.resize((nw, nh), Image.BICUBIC)  # 缩小图像
    # image.show()

    new_image = Image.new('RGB', target_size, (0, 0, 0, 0))  # 生成黑色图像

    # 将图像填充为中间图像，两侧为灰色的样式    
    new_image.paste(image, ((w - nw) // 2, (h - nh) // 2))  

    # 覆盖原图片
    new_image.save(target_image_path)

# 使用opencv读取图像
frame = cv2.imread(image_path)

# 直接缩放到指定大小
frame_suitable = cv2.resize(frame, (img_size[0], img_size[1]), interpolation=cv2.INTER_CUBIC)

# 把图片写进视频
# 重复写入多少次
count = 0
while count < total_count:
       video.write(frame_suitable)
       count += 1

ret, frame = cap.read()

while ret:
     # 文字在图中的坐标(注意:这里的坐标原点是图片左上角)
     x, y = img_size[0] - 200, img_size[1] - 50

     # 写入水印文字，文字颜色为白色
     cv2.putText(img=frame, text=mask_word,
                    org=(x, y), fontFace=cv2.FONT_HERSHEY_COMPLEX_SMALL,
                    fontScale=1, color=(255, 255, 255))

     video_writer.write(frame)
     ret, frame = cap.read()

# 删除源文件，并重命名临时文件
os.remove(video_path)
os.rename(video_temp_path, video_path)

print('水印添加完成~')
video_writer.release()
cap.release()

#获取视频的长度
cap = cv2.VideoCapture(video_path)

#帧率
fps = cap.get(cv2.CAP_PROP_FPS)

#总帧数
frame_count = cap.get(cv2.CAP_PROP_FRAME_COUNT)

#视频总时长-秒，这里做取整操作 【浮点类型】
time_count = math.floor(frame_count / fps)

print('帧率:%f,总帧数:%d' % (fps, frame_count))
print(time_count)

# 3.截取音频
# 为了简单，这里一般不会超过一分钟
bgm_temp_path = get_temp_path(bgm_path, 'temp_new')
os.system('ffmpeg -i %s -ss 00:00:00 -t 00:00:%d -acodec copy %s' % (bgm_path, time_count, bgm_temp_path))

#视频、音频合二为一
# 临时文件
video_temp_path = get_temp_path(video_path, 'temp')
os.system('ffmpeg -i %s  -i %s  -vcodec copy -acodec copy %s' % (video_path, bgm_path, video_temp_path))

# 删除源文件，重命令临时文件
os.remove(video_path)
os.rename(video_temp_path, video_path)