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refactor(webui): 优化视觉分析批次处理逻辑
- 提取 vision_batch_size 到单独变量,提高代码可读性
- 使用 vision_batch_size 替代多次调用 config(frames.get("vision_batch_size")
- 添加调试日志,记录批次数量和每批次的图片数量
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1
.github/workflows/dockerImageBuild.yml
vendored
1
.github/workflows/dockerImageBuild.yml
vendored
@ -3,6 +3,7 @@ name: build_docker
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on:
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release:
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types: [created] # 表示在创建新的 Release 时触发
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workflow_dispatch:
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jobs:
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build_docker:
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@ -55,7 +55,7 @@ class VisionAnalyzer:
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async def analyze_images(self,
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images: Union[List[str], List[PIL.Image.Image]],
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prompt: str,
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batch_size: int = 5) -> List[Dict]:
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batch_size: int) -> List[Dict]:
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"""批量分析多张图片"""
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try:
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# 加载图片
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@ -82,6 +82,8 @@ class VisionAnalyzer:
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results = []
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total_batches = (len(images) + batch_size - 1) // batch_size
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logger.debug(f"共 {total_batches} 个批次,每批次 {batch_size} 张图片")
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with tqdm(total=total_batches, desc="分析进度") as pbar:
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for i in range(0, len(images), batch_size):
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batch = images[i:i + batch_size]
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@ -417,11 +417,12 @@ def generate_script(tr, params):
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asyncio.set_event_loop(loop)
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# 执行异步分析
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vision_batch_size = st.session_state.get('vision_batch_size') or config.frames.get("vision_batch_size")
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results = loop.run_until_complete(
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analyzer.analyze_images(
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images=keyframe_files,
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prompt=config.app.get('vision_analysis_prompt'),
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batch_size=config.frames.get("vision_batch_size", st.session_state.get('vision_batch_size', 5))
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batch_size=vision_batch_size
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)
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)
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loop.close()
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@ -437,8 +438,8 @@ def generate_script(tr, params):
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if 'error' in result:
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logger.warning(f"批次 {result['batch_index']} 处理出现警告: {result['error']}")
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continue
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batch_files = get_batch_files(keyframe_files, result, config.frames.get("vision_batch_size", 5))
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# 获取当前批次的文件列表
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batch_files = get_batch_files(keyframe_files, result, vision_batch_size)
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logger.debug(f"批次 {result['batch_index']} 处理完成,共 {len(batch_files)} 张图片")
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logger.debug(batch_files)
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@ -477,7 +478,7 @@ def generate_script(tr, params):
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if 'error' in result:
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continue
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batch_files = get_batch_files(keyframe_files, result, config.frames.get("vision_batch_size", 5))
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batch_files = get_batch_files(keyframe_files, result, vision_batch_size)
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_, _, timestamp_range = get_batch_timestamps(batch_files, prev_batch_files)
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frame_content = {
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