Python源码实现短视频一键剪辑功能 自动识别关键片段的Python源码支持

opencv

scenedetect

moviepy

# 示例：使用opencv提取视频帧
import cv2

def extract_frames(video_path, output_dir, frame_interval=30):
    """
    从视频中提取帧
    :param video_path: 视频路径
    :param output_dir: 帧输出目录
    :param frame_interval: 帧提取间隔 (每隔多少帧提取一帧)
    """
    vidcap = cv2.VideoCapture(video_path)
    success, image = vidcap.read()
    count = 0
    frame_num = 0
    while success:
        if frame_num % frame_interval == 0:
            cv2.imwrite(f"{output_dir}/frame_{count}.jpg", image)  # save frame as JPEG file
            count += 1
        success, image = vidcap.read()
        frame_num += 1
    print(f"提取了 {count} 帧.")

# 示例：使用moviepy进行视频剪辑
from moviepy.editor import VideoFileClip, concatenate_videoclips

def cut_video(input_path, output_path, start_time, end_time):
    """
    剪切视频片段
    :param input_path: 视频路径
    :param output_path: 剪切后视频路径
    :param start_time: 开始时间 (秒)
    :param end_time: 结束时间 (秒)
    """
    video = VideoFileClip(input_path)
    clip = video.subclip(start_time, end_time)
    clip.write_videofile(output_path, codec="libx264")

# 示例：简单的帧差法运动检测
import cv2
import numpy as np

def motion_detection(video_path, threshold=20):
    """
    使用帧差法进行运动检测
    :param video_path: 视频路径
    :param threshold: 运动阈值
    :return: 包含运动的片段时间戳列表
    """
    cap = cv2.VideoCapture(video_path)
    ret, frame1 = cap.read()
    ret, frame2 = cap.read()
    motion_timestamps = []
    frame_num = 1

    while ret:
        diff = cv2.absdiff(frame1, frame2)
        gray = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY)
        blur = cv2.GaussianBlur(gray, (5, 5), 0)
        _, thresh = cv2.threshold(blur, threshold, 255, cv2.THRESH_BINARY)
        dilated = cv2.dilate(thresh, None, iterations=3)
        contours, _ = cv2.findContours(dilated, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

        for contour in contours:
            (x, y, w, h) = cv2.boundingRect(contour)
            if cv2.contourArea(contour) < 700: # 过滤掉小的运动
                continue
            # 记录包含运动的时间戳
            motion_timestamps.append(frame_num / cap.get(cv2.CAP_PROP_FPS))
            break # 只需要检测到一次运动就记录

        frame1 = frame2
        ret, frame2 = cap.read()
        frame_num += 1

    cap.release()
    cv2.destroyAllWindows()
    return motion_timestamps

librosa

# 示例：使用librosa进行音频分析
import librosa
import numpy as np

def audio_analysis(audio_path, threshold=0.1):
    """
    使用librosa进行音频分析，检测音量突变
    :param audio_path: 音频路径
    :param threshold: 音量突变阈值
    :return: 音量突变的时间戳列表
    """
    y, sr = librosa.load(audio_path)
    rms = librosa.feature.rms(y=y)[0]
    volume_changes = []

    for i in range(1, len(rms)):
        change = abs(rms[i] - rms[i-1])
        if change > threshold:
            volume_changes.append(librosa.frames_to_time(i, sr=sr))

    return volume_changes