128 lines
4.1 KiB
Python
128 lines
4.1 KiB
Python
"""
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视频帧提取工具模块
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提供基于帧索引的精确帧提取功能
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"""
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import cv2
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import base64
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import os
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from io import BytesIO
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# ---帧提取核心功能---
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def extract_frame_by_index(video_path, frame_index, force_rate=0):
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"""
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从视频中提取指定帧索引的图像
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Args:
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video_path: 视频文件路径
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frame_index: 目标帧索引（基于 force_rate 后的帧序列）
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force_rate: 强制帧率，0 表示使用原始帧率
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Returns:
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dict: {success, data (base64 JPEG), width, height} 或 {success, error}
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"""
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try:
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cap = cv2.VideoCapture(video_path)
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if not cap.isOpened():
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return {"success": False, "error": "无法打开视频文件"}
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# 获取原始视频属性
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original_fps = cap.get(cv2.CAP_PROP_FPS)
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total_original_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
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if original_fps <= 0:
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cap.release()
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return {"success": False, "error": "无法获取视频帧率"}
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# 计算实际要读取的原始帧位置
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if force_rate > 0 and force_rate != original_fps:
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# force_rate 会改变帧采样：从原始帧中按比例抽取
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# 帧索引 i 对应的原始帧位置 = i * (original_fps / force_rate)
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actual_frame_pos = int(frame_index * (original_fps / force_rate))
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else:
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actual_frame_pos = frame_index
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# 边界检查
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if actual_frame_pos >= total_original_frames:
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actual_frame_pos = total_original_frames - 1
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if actual_frame_pos < 0:
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actual_frame_pos = 0
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# 定位并读取帧
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cap.set(cv2.CAP_PROP_POS_FRAMES, actual_frame_pos)
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ret, frame = cap.read()
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cap.release()
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if not ret or frame is None:
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return {"success": False, "error": f"无法读取帧 {frame_index}"}
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# BGR 转 RGB
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frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
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# 编码为 JPEG（降低质量加快传输）
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encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), 60]
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_, buffer = cv2.imencode('.jpg', cv2.cvtColor(frame_rgb, cv2.COLOR_RGB2BGR), encode_param)
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# Base64 编码
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base64_data = base64.b64encode(buffer).decode('utf-8')
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return {
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"success": True,
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"data": base64_data,
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"width": frame.shape[1],
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"height": frame.shape[0],
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"frame_index": frame_index,
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"actual_frame_pos": actual_frame_pos
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}
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except Exception as e:
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return {"success": False, "error": str(e)}
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def get_video_frame_info(video_path, force_rate=0):
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"""
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获取视频帧相关信息
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Args:
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video_path: 视频文件路径
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force_rate: 强制帧率
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Returns:
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dict: {success, original_fps, force_fps, total_frames, duration}
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"""
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try:
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cap = cv2.VideoCapture(video_path)
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if not cap.isOpened():
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return {"success": False, "error": "无法打开视频文件"}
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original_fps = cap.get(cv2.CAP_PROP_FPS)
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total_original_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
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cap.release()
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if original_fps <= 0:
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return {"success": False, "error": "无法获取视频帧率"}
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duration = total_original_frames / original_fps
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# 计算 force_rate 后的实际帧数
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if force_rate > 0:
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actual_fps = force_rate
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actual_total_frames = int(duration * force_rate)
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else:
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actual_fps = original_fps
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actual_total_frames = total_original_frames
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return {
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"success": True,
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"original_fps": original_fps,
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"actual_fps": actual_fps,
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"original_total_frames": total_original_frames,
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"actual_total_frames": actual_total_frames,
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"duration": duration
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}
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except Exception as e:
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return {"success": False, "error": str(e)}
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