Delete video_worker.py

src/chat/utils/video_worker.py

@@ -1,75 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-视频帧提取工作函数 - 用于多进程
-这个模块专门用于子进程，避免重复加载主框架
-"""
-
-import cv2
-import base64
-import io
-import numpy as np
-from PIL import Image
-from typing import List, Tuple
-
-
-def extract_frames_worker(video_path: str, max_frames: int, frame_quality: int, max_image_size: int) -> List[Tuple[str, float]]:
-    """在子进程中提取视频帧的工作函数"""
-    frames = []
-    try:
-        cap = cv2.VideoCapture(video_path)
-        fps = cap.get(cv2.CAP_PROP_FPS)
-        total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
-        duration = total_frames / fps if fps > 0 else 0
-        
-        # 使用numpy优化帧间隔计算
-        if duration > 0:
-            frame_interval = max(1, int(duration / max_frames * fps))
-        else:
-            frame_interval = 30  # 默认间隔
-            
-        # 使用numpy计算目标帧位置
-        target_frames = np.arange(0, min(max_frames, total_frames // frame_interval + 1)) * frame_interval
-        target_frames = target_frames[target_frames < total_frames].astype(int)
-        
-        for target_frame in target_frames:
-            # 跳转到目标帧
-            cap.set(cv2.CAP_PROP_POS_FRAMES, target_frame)
-            ret, frame = cap.read()
-            if not ret:
-                continue
-                
-            # 使用numpy优化图像处理
-            frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
-            
-            # 转换为PIL图像并使用numpy进行尺寸计算
-            height, width = frame_rgb.shape[:2]
-            max_dim = max(height, width)
-            
-            if max_dim > max_image_size:
-                # 使用numpy计算缩放比例
-                ratio = max_image_size / max_dim
-                new_width = int(width * ratio)
-                new_height = int(height * ratio)
-                
-                # 使用opencv进行高效缩放
-                frame_resized = cv2.resize(frame_rgb, (new_width, new_height), interpolation=cv2.INTER_LANCZOS4)
-                pil_image = Image.fromarray(frame_resized)
-            else:
-                pil_image = Image.fromarray(frame_rgb)
-            
-            # 转换为base64
-            buffer = io.BytesIO()
-            pil_image.save(buffer, format='JPEG', quality=frame_quality)
-            frame_base64 = base64.b64encode(buffer.getvalue()).decode('utf-8')
-            
-            # 计算时间戳
-            timestamp = target_frame / fps if fps > 0 else 0
-            frames.append((frame_base64, timestamp))
-        
-        cap.release()
-        return frames
-        
-    except Exception as e:
-        # 在子进程中不能使用logger，返回错误信息
-        return [("ERROR", str(e))]