feat: 本地视觉分析模块 - 运动检测、人体检测、亮度检测，自动判断是否需要大模型
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+103
-17
@@ -6,6 +6,7 @@ import time
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import datetime
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from camera import CameraCapture
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from analyzer import ImageAnalyzer
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from local_analyzer import LocalAnalyzer
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from database import db
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from config import config_mgr
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@@ -15,15 +16,19 @@ class VisionScheduler:
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def __init__(self):
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self.camera = CameraCapture()
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self.analyzer = ImageAnalyzer()
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self.vision_analyzer = ImageAnalyzer() # 大模型分析器
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self.local_analyzer = LocalAnalyzer() # 本地分析器
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self.running = False
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self.timer = None
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self.prev_image_path = None # 保存前一张图片路径
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# 统计
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self.capture_count = 0
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self.last_capture_time = None
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self.last_analyze_time = None
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self.errors = []
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self.model_calls = 0 # 大模型调用次数
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self.local_analyses = 0 # 本地分析次数
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def start(self):
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"""启动定时拍照"""
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@@ -94,33 +99,88 @@ class VisionScheduler:
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self._schedule_next()
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def _analyze_task(self, image_id, image_path):
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"""分析任务"""
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"""分析任务 - 先本地分析，再决定是否调用大模型"""
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try:
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result = self.analyzer.analyze(image_path)
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self.local_analyses += 1
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if result['success']:
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# 记录事件
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for event in result['events']:
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# 1. 本地快速分析
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local_result = self.local_analyzer.analyze(image_path, self.prev_image_path)
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# 保存当前图片路径供下次对比
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self.prev_image_path = image_path
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if local_result['success']:
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# 记录本地检测到的事件
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for event in local_result['events']:
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db.add_event(
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image_id,
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event['event_type'],
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event['event_type'] + '(本地)',
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event['description'],
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event['confidence']
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)
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# 标记已分析
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db.mark_image_analyzed(image_id)
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# 2. 判断是否需要大模型分析
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if local_result['need_model'] and config_mgr.get('auto_analyze', True):
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print(f"[Scheduler] Local analysis triggered model call for image {image_id}")
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self._call_vision_api(image_id, image_path)
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else:
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# 不需要大模型，直接标记已分析
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db.mark_image_analyzed(image_id)
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print(f"[Scheduler] Local analysis sufficient for image {image_id}")
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print(f" - Motion: {local_result['metrics'].get('motion_ratio', 0):.2%}")
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print(f" - Human: {local_result['metrics'].get('human_count', 0)}")
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print(f" - Need model: {local_result['need_model']}")
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self.last_analyze_time = datetime.datetime.now().isoformat()
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else:
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self.errors.append({
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'time': datetime.datetime.now().isoformat(),
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'error': f"分析失败: {result['error']}"
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'error': f"本地分析失败: {local_result['error']}"
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})
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# 本地分析失败，尝试直接调用大模型
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if config_mgr.get('auto_analyze', True):
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self._call_vision_api(image_id, image_path)
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except Exception as e:
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self.errors.append({
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'time': datetime.datetime.now().isoformat(),
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'error': str(e)
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})
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def _call_vision_api(self, image_id, image_path):
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"""调用大模型 Vision API"""
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try:
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self.model_calls += 1
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print(f"[Scheduler] Calling Vision API for image {image_id}")
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result = self.vision_analyzer.analyze(image_path)
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if result['success']:
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for event in result['events']:
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db.add_event(
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image_id,
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event['event_type'] + '(AI)',
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event['description'],
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event['confidence']
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)
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db.mark_image_analyzed(image_id)
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print(f"[Scheduler] Vision API analysis complete for image {image_id}")
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else:
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print(f"[Scheduler] Vision API failed: {result['error']}")
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self.errors.append({
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'time': datetime.datetime.now().isoformat(),
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'error': f"Vision API失败: {result['error']}"
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})
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# 即使失败也标记已分析（避免重复调用）
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db.mark_image_analyzed(image_id)
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except Exception as e:
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print(f"[Scheduler] Vision API exception: {e}")
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self.errors.append({
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'time': datetime.datetime.now().isoformat(),
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'error': str(e)
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})
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def capture_now(self):
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"""立即拍照"""
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result = self.camera.capture()
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@@ -157,20 +217,43 @@ class VisionScheduler:
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if not image:
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return {'success': False, 'error': '图片不存在'}
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result = self.analyzer.analyze(image['path'])
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# 获取前一张图片
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prev_images = db.get_images(limit=1, offset=1)
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prev_path = prev_images[0]['path'] if prev_images else None
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if result['success']:
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for event in result['events']:
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# 先本地分析
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local_result = self.local_analyzer.analyze(image['path'], prev_path)
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if local_result['success']:
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# 记录本地事件
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for event in local_result['events']:
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db.add_event(
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image_id,
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event['event_type'],
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event['event_type'] + '(本地)',
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event['description'],
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event['confidence']
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)
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db.mark_image_analyzed(image_id)
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self.last_analyze_time = datetime.datetime.now().isoformat()
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# 再调用大模型（强制调用，用户手动点击）
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vision_result = self.vision_analyzer.analyze(image['path'])
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if vision_result['success']:
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for event in vision_result['events']:
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db.add_event(
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image_id,
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event['event_type'] + '(AI)',
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event['description'],
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event['confidence']
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)
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db.mark_image_analyzed(image_id)
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self.last_analyze_time = datetime.datetime.now().isoformat()
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return {'success': True, 'events': local_result['events'] + vision_result['events']}
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else:
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db.mark_image_analyzed(image_id)
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return {'success': True, 'events': local_result['events'], 'vision_error': vision_result['error']}
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return local_result
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return result
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except Exception as e:
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return {'success': False, 'error': str(e)}
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@@ -206,6 +289,9 @@ class VisionScheduler:
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'capture_count': self.capture_count,
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'last_capture_time': self.last_capture_time,
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'last_analyze_time': self.last_analyze_time,
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'model_calls': self.model_calls,
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'local_analyses': self.local_analyses,
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'local_stats': self.local_analyzer.get_stats(),
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'recent_errors': self.errors[-5:] if self.errors else []
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}
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