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feat(app): 集成loguru日志系统并优化错误处理

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- 在app.py中引入loguru并配置日志轮转、异步输出等功能
- 添加全局日志初始化函数和程序启动/退出日志记录
- 将所有print语句替换为logger.info/error/debug/warning方法
- 在data_source.py中添加模型加载和视频打开的日志记录
- 在各个处理器中集成日志记录器实例并记录处理状态
- 修改处理器模块导入路径以符合相对导入规范
- 在requirements.txt中添加loguru依赖包
- 统一异常处理的日志记录方式，便于调试和监控
This commit is contained in:
zimoyin
2026-01-10 18:03:18 +08:00
parent c4e906e6f7
commit cdf228fe56
12 changed files with 61 additions and 29 deletions
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app.py
+22 -4
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@@ -1,4 +1,5 @@
import asyncio
from loguru import logger
from yolo_gs.pipeline.handler.DrawDirectionProcessor import DrawDirectionProcessor
from yolo_gs.pipeline.handler.DrawGraffitiProcessor import DrawGraffitiProcessor
@@ -12,8 +13,23 @@ import cv2
from yolo_gs.pipeline.data_source import video_yolo_iterator
from yolo_gs.pipeline.pipeline import Pipeline
def init_logger():
logger.add(
"logs/yolo_gs.log",
rotation="100 MB", # 原有配置：日志文件达100MB轮转
level="DEBUG", # 原有配置：记录DEBUG及以上级别
enqueue=True, # 开启异步输出（关键参数）
backtrace=True, # 记录完整异常堆栈（包括第三方库）
diagnose=True, # 显示异常时的变量值（便于调试，生产环境可设为False）
)
# ===================== 测试运行 =====================
if __name__ == "__main__":
init_logger()
logger.info("开始运行YOLO涂鸦车道检测系统")
# 1. 创建管道
pipeline = Pipeline()
@@ -25,12 +41,12 @@ if __name__ == "__main__":
pipeline.add_processor(DrawObjectBoxProcessor())
pipeline.add_processor(ResultLogger(name="结果日志器"))
# 4. 构建视频+YOLO跟踪迭代器（替换为你的视频路径，或0使用摄像头）
video_path = "123.mp4" # 或 0 (摄像头)
try:
logger.info(f"开始处理视频: {video_path}")
# 使用跟踪迭代器，可以获取对象ID
data_iter = video_yolo_iterator(video_path, model_path="yolo11s.pt",tracker="botsort.yaml", device="0")
data_iter = video_yolo_iterator(video_path, model_path="yolo11s.pt", tracker="botsort.yaml", device="0")
# 5. 运行管道，迭代处理数据
for processed_data in pipeline.run(data_iter):
@@ -40,8 +56,10 @@ if __name__ == "__main__":
# 直接显示经过管道处理后的帧，其中已经包含了绘制处理器的效果
cv2.imshow("YOLO Tracking Pipeline", frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
logger.info("用户请求退出程序")
break
except Exception as e:
print(f"运行出错: {e}")
logger.error(f"运行出错: {e}")
finally:
cv2.destroyAllWindows()
cv2.destroyAllWindows()
logger.info("程序结束运行")
pipeline/base_processor.py
+4
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@@ -1,3 +1,4 @@
from loguru import logger
from abc import ABC, abstractmethod
import asyncio
from .pipeline_data import PipelineData
@@ -7,6 +8,9 @@ class BaseProcessor(ABC):
"""所有处理器的抽象基类，定义统一的处理接口"""
def __init__(self, name: str):
self.name = name # 处理器名称（便于日志/调试）
# 初始化日志记录器
self.logger = logger
self.logger.debug(f"处理器 {self.name} 已初始化")
@abstractmethod
def process(self, data: PipelineData) -> PipelineData:
pipeline/data_source.py
+6 -1
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@@ -1,3 +1,4 @@
from loguru import logger
from typing import Iterator
import cv2
from ultralytics import YOLO
@@ -16,15 +17,18 @@ def video_yolo_iterator(video_path: str, model_path: str = "yolov8n.pt", tracker
"""
# 加载YOLO模型
model = YOLO(model_path)
logger.info(f"已加载YOLO模型: {model_path}")
# 打开视频
cap = cv2.VideoCapture(video_path)
if not cap.isOpened():
logger.error(f"无法打开视频: {video_path}")
raise ValueError(f"无法打开视频: {video_path}")
frame_idx = 0
try:
# 使用 model.track 替代 model 进行跟踪检测
results_stream = model.track(source=video_path, tracker=tracker, device=device, stream=True)
logger.info(f"已开始跟踪视频: {video_path}")
last_data = PipelineData()
for r in results_stream: # 迭代跟踪结果
@@ -67,6 +71,7 @@ def video_yolo_detect_iterator(video_path: str, model_path: str = "yolov8n.pt",
# 打开视频
cap = cv2.VideoCapture(video_path)
if not cap.isOpened():
logger.error(f"无法打开视频: {video_path}")
raise ValueError(f"无法打开视频: {video_path}")
frame_idx = 0
@@ -94,4 +99,4 @@ def video_yolo_detect_iterator(video_path: str, model_path: str = "yolov8n.pt",
frame_idx += 1
finally:
# 确保视频流关闭
cap.release()
cap.release()
pipeline/handler/DrawDirectionProcessor.py
+3 -3
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@@ -2,8 +2,8 @@ import cv2
import numpy as np
import math
from collections import deque
from yolo_gs.pipeline.base_processor import BaseProcessor
from yolo_gs.pipeline.pipeline_data import PipelineData
from ..base_processor import BaseProcessor
from ..pipeline_data import PipelineData
class DrawDirectionProcessor(BaseProcessor):
@@ -96,7 +96,7 @@ class DrawDirectionProcessor(BaseProcessor):
self._draw_track_info(vis, track_id, (center_x, center_y))
except Exception as e:
print(f"Error processing box: {e}")
self.logger.error(f"Error processing box: {e}")
continue
# 清理长时间未出现的track
pipeline/handler/DrawGraffitiProcessor.py
+2 -2
View File
@@ -1,8 +1,8 @@
import cv2
import numpy as np
import math
from yolo_gs.pipeline.base_processor import BaseProcessor
from yolo_gs.pipeline.pipeline_data import PipelineData
from ..base_processor import BaseProcessor
from ..pipeline_data import PipelineData
class DrawGraffitiProcessor(BaseProcessor):
pipeline/handler/DrawObjectBoxProcessor.py
+2 -2
View File
@@ -2,8 +2,8 @@ import cv2
import numpy as np
from dataclasses import dataclass, field
from typing import List, Optional, Set
from yolo_gs.pipeline.base_processor import BaseProcessor
from yolo_gs.pipeline.pipeline_data import PipelineData
from ..base_processor import BaseProcessor
from ..pipeline_data import PipelineData
@dataclass
pipeline/handler/GraffitiProcessor.py
+2 -2
View File
@@ -2,8 +2,8 @@ import numpy as np
import cv2
import math
from collections import deque, defaultdict
from yolo_gs.pipeline.base_processor import BaseProcessor
from yolo_gs.pipeline.pipeline_data import PipelineData
from ..base_processor import BaseProcessor
from ..pipeline_data import PipelineData
class GraffitiProcessor(BaseProcessor):
pipeline/handler/ResultLogger.py
+2 -2
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@@ -5,6 +5,6 @@ import numpy as np
class ResultLogger(BaseProcessor):
"""示例处理器：打印检测结果日志"""
def process(self, data: PipelineData) -> PipelineData:
print(f"\n【{self.name}】帧{data.frame_idx} - 检测到目标数: {len(data.current_result.boxes)}")
print(f"缓存帧数: {len(data.result_cache)}")
self.logger.info(f"【{self.name}】帧{data.frame_idx} - 检测到目标数: {len(data.current_result.boxes)}")
self.logger.info(f"缓存帧数: {len(data.result_cache)}")
return data
pipeline/handler/RetrogradeProcessor.py
+3 -3
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@@ -1,7 +1,7 @@
import cv2
import numpy as np
from yolo_gs.pipeline.base_processor import BaseProcessor
from yolo_gs.pipeline.pipeline_data import PipelineData
from ..base_processor import BaseProcessor
from ..pipeline_data import PipelineData
import math
@@ -115,7 +115,7 @@ class RetrogradeProcessor(BaseProcessor):
# 输出逆行信息
for track_id, event in events_all0.items():
print(f"【逆行检测器】帧{self.frame_idx} - 检测到事件：{event} - 轨迹ID: {track_id}")
self.logger.info(f"【逆行检测器】帧{self.frame_idx} - 检测到事件：{event} - 轨迹ID: {track_id}")
# 更新事件历史
for track_id, event in frame_events.items():
pipeline/handler/graffiti_visualizer.py
+2 -2
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@@ -1,8 +1,8 @@
import numpy as np
import cv2
import math
from yolo_gs.pipeline.base_processor import BaseProcessor
from yolo_gs.pipeline.pipeline_data import PipelineData
from ..base_processor import BaseProcessor
from ..pipeline_data import PipelineData
class GraffitiVisualizer(BaseProcessor):
pipeline/pipeline.py
+11 -7
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@@ -1,3 +1,4 @@
from loguru import logger
from typing import List, Iterator
import asyncio
from .base_processor import BaseProcessor
@@ -10,16 +11,19 @@ class Pipeline:
def __init__(self):
self.processors: List[BaseProcessor] = [] # 同步处理器列表
self.async_processors: List[BaseProcessor] = [] # 异步处理器列表
# 初始化日志记录器
self.logger = logger
self.logger.debug("管道已初始化")
def add_processor(self, processor: BaseProcessor) -> None:
"""向管道添加同步处理器（按添加顺序执行）"""
self.processors.append(processor)
print(f"管道已添加同步处理器: {processor}")
self.logger.info(f"管道已添加同步处理器: {processor}")
def add_processor_async(self, processor: BaseProcessor) -> None:
"""向管道添加异步处理器（异步执行，不阻塞数据流）"""
self.async_processors.append(processor)
print(f"管道已添加异步处理器: {processor}")
self.logger.info(f"管道已添加异步处理器: {processor}")
def remove_processor(self, processor_name: str) -> bool:
"""移除指定名称的处理器"""
@@ -27,15 +31,15 @@ class Pipeline:
for idx, p in enumerate(self.processors):
if p.name == processor_name:
self.processors.pop(idx)
print(f"管道已移除同步处理器: {p}")
self.logger.info(f"管道已移除同步处理器: {p}")
return True
# 检查异步处理器列表
for idx, p in enumerate(self.async_processors):
if p.name == processor_name:
self.async_processors.pop(idx)
print(f"管道已移除异步处理器: {p}")
self.logger.info(f"管道已移除异步处理器: {p}")
return True
print(f"未找到处理器: {processor_name}")
self.logger.warning(f"未找到处理器: {processor_name}")
return False
def run(self, data_iterator: Iterator[PipelineData]) -> Iterator[PipelineData]:
@@ -61,7 +65,7 @@ class Pipeline:
data = processor.process(data)
yield data
except Exception as e:
print(f"同步处理器 {processor.name} 执行出错: {e}")
self.logger.error(f"同步处理器 {processor.name} 执行出错: {e}")
# 异步执行异步处理器，不阻塞数据流
if self.async_processors:
@@ -87,4 +91,4 @@ class Pipeline:
# 如果处理器不支持异步处理，则同步处理
processor.process(data)
except Exception as e:
print(f"异步处理器 {processor.name} 执行出错: {e}")
self.logger.error(f"异步处理器 {processor.name} 执行出错: {e}")
requirements.txt
+2 -1
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@@ -1 +1,2 @@
ultralytics>=8.3.249
ultralytics>=8.3.249
loguru>=0.7.3