Initial commit: WeChat bot project with AI chat, video export, and image upload scripts

video_to_frames.py

@@ -0,0 +1,166 @@
+#!/usr/bin/env python3
+"""
+视频切割脚本 - 将视频逐帧切割为图片
+支持扫描目录下所有视频文件，多进程并行处理，已切割的自动跳过
+"""
+
+import os
+import sys
+import cv2
+import argparse
+from multiprocessing import Pool, cpu_count
+from pathlib import Path
+
+# 支持的视频扩展名
+VIDEO_EXTENSIONS = {'.mp4', '.avi', '.mkv', '.mov', '.flv', '.wmv', '.webm', '.ts', '.m4v'}
+
+
+def scan_videos(root_path: str) -> list[str]:
+    """扫描目录下所有视频文件"""
+    videos = []
+    root = Path(root_path)
+    if root.is_file() and root.suffix.lower() in VIDEO_EXTENSIONS:
+        return [str(root)]
+    for p in sorted(root.rglob('*')):
+        if p.is_file() and p.suffix.lower() in VIDEO_EXTENSIONS:
+            videos.append(str(p))
+    return videos
+
+
+def extract_frames(video_path: str, output_dir: str = None) -> dict:
+    """
+    将单个视频按每秒1帧切割为图片
+
+    Args:
+        video_path: 视频文件路径
+        output_dir: 输出目录（默认在视频同目录下创建同名文件夹）
+
+    Returns:
+        处理结果字典
+    """
+    video_path = os.path.abspath(video_path)
+    video_name = Path(video_path).stem
+
+    if output_dir is None:
+        output_dir = os.path.join(os.path.dirname(video_path), video_name + '_frames')
+
+    # 已经切割过则跳过
+    if os.path.isdir(output_dir) and any(Path(output_dir).glob('*.jpg')):
+        existing = len(list(Path(output_dir).glob('*.jpg')))
+        return {
+            'video': video_path,
+            'status': 'skipped',
+            'reason': f'已存在，共 {existing} 张图片',
+            'output': output_dir,
+        }
+
+    os.makedirs(output_dir, exist_ok=True)
+
+    cap = cv2.VideoCapture(video_path)
+    if not cap.isOpened():
+        return {
+            'video': video_path,
+            'status': 'error',
+            'reason': '无法打开视频文件',
+            'output': output_dir,
+        }
+
+    fps = cap.get(cv2.CAP_PROP_FPS) or 25
+    total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+    duration = total_frames / fps if fps else 0
+
+    # 每秒取一帧：根据fps算出每隔多少帧取一帧
+    frame_interval = int(fps)
+    frame_idx = 0
+    saved = 0
+    while True:
+        ret, frame = cap.read()
+        if not ret:
+            break
+        if frame_idx % frame_interval == 0:
+            # 用视频名+时间戳命名：第01集_01m23s_456.jpg
+            sec = frame_idx / fps
+            mins = int(sec // 60)
+            secs = int(sec % 60)
+            ms = int((sec % 1) * 1000)
+            filename = os.path.join(output_dir, f'{video_name}_{mins:02d}m{secs:02d}s_{ms:03d}.jpg')
+            cv2.imwrite(filename, frame)
+            saved += 1
+        frame_idx += 1
+
+    cap.release()
+
+    return {
+        'video': video_path,
+        'status': 'done',
+        'frames_total': total_frames,
+        'frames_saved': saved,
+        'duration': f'{duration:.1f}s',
+        'fps': fps,
+        'output': output_dir,
+    }
+
+
+def _worker(args):
+    """多进程 worker 包装"""
+    video_path, output_dir = args
+    try:
+        return extract_frames(video_path, output_dir)
+    except Exception as e:
+        return {
+            'video': video_path,
+            'status': 'error',
+            'reason': str(e),
+        }
+
+
+def main(video_path, output=None, interval=1, jobs=None):
+    videos = scan_videos(video_path)
+    if not videos:
+        print(f'未在 {video_path} 中找到视频文件')
+        return
+
+    jobs = jobs or cpu_count()
+    print(f'找到 {len(videos)} 个视频，使用 {jobs} 个进程并行处理')
+
+    tasks = []
+    for v in videos:
+        if output:
+            video_name = Path(v).stem
+            out = os.path.join(output, video_name + '_frames')
+        else:
+            out = None
+        tasks.append((v, out))
+
+    done = 0
+    skipped = 0
+    errors = 0
+
+    with Pool(jobs) as pool:
+        for result in pool.imap_unordered(_worker, tasks):
+            status = result['status']
+            video = result['video']
+            if status == 'done':
+                done += 1
+                print(f'[完成] {video} -> {result["frames_saved"]}帧 '
+                      f'(总{result["frames_total"]}, {result["duration"]})')
+            elif status == 'skipped':
+                skipped += 1
+                print(f'[跳过] {video} ({result["reason"]})')
+            else:
+                errors += 1
+                print(f'[错误] {video} ({result["reason"]})')
+
+    print(f'\n处理完毕: 完成 {done}, 跳过 {skipped}, 错误 {errors}, 共 {len(videos)}')
+
+
+# ========== 运行设置（改这里）==========
+VIDEO_DIR = "./shipin"       # 视频文件或目录路径
+OUTPUT_DIR = None            # 输出目录，None 则在视频同目录
+INTERVAL = 1                 # 每隔 N 帧取一帧
+JOBS = None                  # 并行进程数，None 则用 CPU 核心数
+# ======================================
+
+
+if __name__ == '__main__':
+    main(VIDEO_DIR, OUTPUT_DIR, INTERVAL, JOBS)