08:54:50.464 [INFO] - 待测试业务名称: @ main.py:15 in 08:54:50.464 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 08:54:50.464 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 08:54:50.659 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 08:54:50.659 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 08:54:50.660 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:195 in checkFile 08:54:50.660 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:195 in checkFile 08:54:50.660 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:195 in checkFile 08:54:50.660 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:195 in checkFile 08:54:50.661 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:195 in checkFile 08:54:50.661 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:195 in checkFile 08:54:50.661 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 08:54:50.688 [INFO] - select_device YOLOv5 🚀 2025-9-17 torch 2.0.0+cu117 CUDA:0 (NVIDIA GeForce RTX 3090, 24258.625MB) @ torchHelper.py:106 in select_device 08:54:50.689 [INFO] - step 2: 取得参数配置 @ Bussiness_Seg.py:73 in run 08:54:50.848 [INFO] - step 3: 情况 1 - 成功载入 det model trt [./weights/illParking/yolov5_3090_fp16.engine] @ Bussiness_Seg.py:83 in run 08:54:50.874 [INFO] - 加载 stdcModel 模型: ./weights/illParking/stdc_360X640_3090_fp16.engine 类型: trt @ stdc.py:53 in __init__ 08:54:50.883 [INFO] - step 4: 共读入 1 张图片待处理 @ Bussiness_Seg.py:170 in run 08:54:50.883 [WARNING] - step 5-------------------- 处理图片 ./appIOs/samples/illParking/a2fe274345f77fb8985d2bc90aaaae7.jpg-------------------- @ Bussiness_Seg.py:175 in run 08:54:51.339 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 08:54:51.341 [WARNING] - mean not in par, use default mean(0.485, 0.456, 0.406) @ stdc.py:75 in preprocess_image 08:54:51.341 [WARNING] - std not in par, use default std(0.229, 0.224, 0.225) @ stdc.py:78 in preprocess_image 08:54:51.429 [INFO] - [业务分析]业务 总共耗时 545.5 毫秒，其中： AI_Process: 537.7 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 537.7 毫秒，其中： img_pad: 3.1 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.1 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 450.9 毫秒 aiHelper.py:165 in AI_process infer: 12.3 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 65.3 毫秒 aiHelper.py:184 in AI_process 后处理: 5.7 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 5.7 毫秒，其中： NMS: 2.4 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.3 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 7.0 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 08:54:51.430 [INFO] - step 6: 1 张图片共耗时:546.4 ms ,依次为:546.4 ms, 占用 1 线程 @ Bussiness_Seg.py:187 in run 08:55:45.440 [INFO] - 待测试业务名称: @ main.py:15 in 08:55:45.440 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 08:55:45.440 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 08:55:45.636 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 08:55:45.637 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 08:55:45.638 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:195 in checkFile 08:55:45.638 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:195 in checkFile 08:55:45.638 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:195 in checkFile 08:55:45.638 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:195 in checkFile 08:55:45.639 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:195 in checkFile 08:55:45.639 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:195 in checkFile 08:55:45.639 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 08:55:45.666 [INFO] - select_device YOLOv5 🚀 2025-9-17 torch 2.0.0+cu117 CUDA:0 (NVIDIA GeForce RTX 3090, 24258.625MB) @ torchHelper.py:106 in select_device 08:55:45.667 [INFO] - step 2: 取得参数配置 @ Bussiness_Seg.py:73 in run 08:55:45.840 [INFO] - step 3: 情况 1 - 成功载入 det model trt [./weights/illParking/yolov5_3090_fp16.engine] @ Bussiness_Seg.py:83 in run 08:55:45.864 [INFO] - 加载 stdcModel 模型: ./weights/illParking/stdc_360X640_3090_fp16.engine 类型: trt @ stdc.py:53 in __init__ 08:55:45.873 [INFO] - step 4: 共读入 1 张图片待处理 @ Bussiness_Seg.py:170 in run 08:55:45.874 [WARNING] - step 5-------------------- 处理图片 ./appIOs/samples/illParking/a2fe274345f77fb8985d2bc90aaaae7.jpg-------------------- @ Bussiness_Seg.py:175 in run 08:55:45.904 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 08:55:45.907 [WARNING] - mean not in par, use default mean(0.485, 0.456, 0.406) @ stdc.py:75 in preprocess_image 08:55:45.907 [WARNING] - std not in par, use default std(0.229, 0.224, 0.225) @ stdc.py:78 in preprocess_image 08:56:03.016 [INFO] - 待测试业务名称: @ main.py:15 in 08:56:03.016 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 08:56:03.017 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 08:56:03.207 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 08:56:03.207 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 08:56:03.208 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:195 in checkFile 08:56:03.208 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:195 in checkFile 08:56:03.208 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:195 in checkFile 08:56:03.209 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:195 in checkFile 08:56:03.209 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:195 in checkFile 08:56:03.210 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:195 in checkFile 08:56:03.210 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 08:56:03.237 [INFO] - select_device YOLOv5 🚀 2025-9-17 torch 2.0.0+cu117 CUDA:0 (NVIDIA GeForce RTX 3090, 24258.625MB) @ torchHelper.py:106 in select_device 08:56:03.237 [INFO] - step 2: 取得参数配置 @ Bussiness_Seg.py:73 in run 08:56:03.407 [INFO] - step 3: 情况 1 - 成功载入 det model trt [./weights/illParking/yolov5_3090_fp16.engine] @ Bussiness_Seg.py:83 in run 08:56:03.433 [INFO] - 加载 stdcModel 模型: ./weights/illParking/stdc_360X640_3090_fp16.engine 类型: trt @ stdc.py:53 in __init__ 08:56:03.443 [INFO] - step 4: 共读入 1 张图片待处理 @ Bussiness_Seg.py:170 in run 08:56:03.443 [WARNING] - step 5-------------------- 处理图片 ./appIOs/samples/illParking/a2fe274345f77fb8985d2bc90aaaae7.jpg-------------------- @ Bussiness_Seg.py:175 in run 08:56:03.897 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 08:56:03.899 [WARNING] - mean not in par, use default mean(0.485, 0.456, 0.406) @ stdc.py:75 in preprocess_image 08:56:03.900 [WARNING] - std not in par, use default std(0.229, 0.224, 0.225) @ stdc.py:78 in preprocess_image 08:56:03.989 [INFO] - [业务分析]业务 总共耗时 545.6 毫秒，其中： AI_Process: 537.9 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 537.9 毫秒，其中： img_pad: 1.6 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.1 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 450.4 毫秒 aiHelper.py:165 in AI_process infer: 13.5 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 65.5 毫秒 aiHelper.py:184 in AI_process 后处理: 6.5 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 6.5 毫秒，其中： NMS: 3.2 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.2 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.9 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 08:56:03.990 [INFO] - step 6: 1 张图片共耗时:546.4 ms ,依次为:546.4 ms, 占用 1 线程 @ Bussiness_Seg.py:187 in run 08:56:54.624 [INFO] - 待测试业务名称: @ main.py:15 in 08:56:54.624 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 08:56:54.624 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 08:56:54.815 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 08:56:54.816 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 08:56:54.816 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:195 in checkFile 08:56:54.816 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:195 in checkFile 08:56:54.817 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:195 in checkFile 08:56:54.817 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:195 in checkFile 08:56:54.818 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:195 in checkFile 08:56:54.818 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:195 in checkFile 08:56:54.819 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 08:56:54.845 [INFO] - select_device YOLOv5 🚀 2025-9-17 torch 2.0.0+cu117 CUDA:0 (NVIDIA GeForce RTX 3090, 24258.625MB) @ torchHelper.py:106 in select_device 08:56:54.845 [INFO] - step 2: 取得参数配置 @ Bussiness_Seg.py:73 in run 08:56:55.009 [INFO] - step 3: 情况 1 - 成功载入 det model trt [./weights/illParking/yolov5_3090_fp16.engine] @ Bussiness_Seg.py:83 in run 08:56:55.033 [INFO] - 加载 stdcModel 模型: ./weights/illParking/stdc_360X640_3090_fp16.engine 类型: trt @ stdc.py:53 in __init__ 08:56:55.042 [INFO] - step 4: 共读入 1 张图片待处理 @ Bussiness_Seg.py:170 in run 08:56:55.043 [WARNING] - step 5-------------------- 处理图片 ./appIOs/samples/illParking/a2fe274345f77fb8985d2bc90aaaae7.jpg-------------------- @ Bussiness_Seg.py:175 in run 08:56:55.047 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 08:56:55.049 [WARNING] - mean not in par, use default mean(0.485, 0.456, 0.406) @ stdc.py:75 in preprocess_image 08:56:55.050 [WARNING] - std not in par, use default std(0.229, 0.224, 0.225) @ stdc.py:78 in preprocess_image 08:57:56.058 [INFO] - 待测试业务名称: @ main.py:15 in 08:57:56.058 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 08:57:56.058 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 08:57:56.254 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 08:57:56.254 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 08:57:56.255 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:195 in checkFile 08:57:56.255 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:195 in checkFile 08:57:56.255 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:195 in checkFile 08:57:56.256 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:195 in checkFile 08:57:56.256 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:195 in checkFile 08:57:56.256 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:195 in checkFile 08:57:56.256 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 08:57:56.283 [INFO] - select_device YOLOv5 🚀 2025-9-17 torch 2.0.0+cu117 CUDA:0 (NVIDIA GeForce RTX 3090, 24258.625MB) @ torchHelper.py:106 in select_device 08:57:56.283 [INFO] - step 2: 取得参数配置 @ Bussiness_Seg.py:73 in run 08:57:56.453 [INFO] - step 3: 情况 1 - 成功载入 det model trt [./weights/illParking/yolov5_3090_fp16.engine] @ Bussiness_Seg.py:83 in run 08:57:56.477 [INFO] - 加载 stdcModel 模型: ./weights/illParking/stdc_360X640_3090_fp16.engine 类型: trt @ stdc.py:53 in __init__ 08:57:56.486 [INFO] - step 4: 共读入 1 张图片待处理 @ Bussiness_Seg.py:170 in run 08:57:56.487 [WARNING] - step 5-------------------- 处理图片 ./appIOs/samples/illParking/a2fe274345f77fb8985d2bc90aaaae7.jpg-------------------- @ Bussiness_Seg.py:175 in run 08:57:56.935 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 08:57:56.937 [WARNING] - mean not in par, use default mean(0.485, 0.456, 0.406) @ stdc.py:75 in preprocess_image 08:57:56.937 [WARNING] - std not in par, use default std(0.229, 0.224, 0.225) @ stdc.py:78 in preprocess_image 08:57:57.123 [INFO] - [业务分析]业务 总共耗时 635.6 毫秒，其中： AI_Process: 531.9 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 531.9 毫秒，其中： img_pad: 1.8 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.1 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 443.2 毫秒 aiHelper.py:166 in AI_process infer: 15.9 毫秒 aiHelper.py:178 in AI_process yolov5Trtforward: 64.6 毫秒 aiHelper.py:185 in AI_process 后处理: 6.0 毫秒 aiHelper.py:192 in AI_process -> [预测结果后处理]业务 总共耗时 6.0 毫秒，其中： NMS: 2.6 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.4 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 102.8 毫秒 Bussiness.py:93 in doAnalysis fp: 0.2 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 08:57:57.124 [INFO] - step 6: 1 张图片共耗时:636.8 ms ,依次为:636.8 ms, 占用 1 线程 @ Bussiness_Seg.py:187 in run 11:46:19.955 [INFO] - 待测试业务名称: @ main.py:15 in 11:46:19.955 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 11:46:19.955 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 11:46:20.149 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 11:46:20.150 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 11:46:20.150 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:195 in checkFile 11:46:20.151 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:195 in checkFile 11:46:20.151 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:195 in checkFile 11:46:20.151 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:195 in checkFile 11:46:20.152 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:195 in checkFile 11:46:20.152 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:195 in checkFile 11:46:20.152 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 11:46:20.179 [INFO] - select_device YOLOv5 🚀 2025-9-17 torch 2.0.0+cu117 CUDA:0 (NVIDIA GeForce RTX 3090, 24258.625MB) @ torchHelper.py:106 in select_device 11:46:20.180 [INFO] - step 2: 取得参数配置 @ Bussiness_Seg.py:73 in run 11:46:20.344 [INFO] - step 3: 情况 1 - 成功载入 det model trt [./weights/illParking/yolov5_3090_fp16.engine] @ Bussiness_Seg.py:83 in run 11:46:20.368 [INFO] - 加载 stdcModel 模型: ./weights/illParking/stdc_360X640_3090_fp16.engine 类型: trt @ stdc.py:53 in __init__ 11:46:20.391 [INFO] - step 4: 共读入 5 张图片待处理 @ Bussiness_Seg.py:170 in run 11:46:20.391 [WARNING] - step 5-------------------- 处理图片 ./appIOs/samples/illParking/4.jpg-------------------- @ Bussiness_Seg.py:175 in run 11:46:20.842 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 11:46:20.844 [WARNING] - mean not in par, use default mean(0.485, 0.456, 0.406) @ stdc.py:75 in preprocess_image 11:46:20.844 [WARNING] - std not in par, use default std(0.229, 0.224, 0.225) @ stdc.py:78 in preprocess_image 11:46:20.935 [INFO] - [业务分析]业务 总共耗时 543.1 毫秒，其中： AI_Process: 535.4 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 535.4 毫秒，其中： img_pad: 1.7 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.1 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 446.9 毫秒 aiHelper.py:165 in AI_process infer: 14.3 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 66.4 毫秒 aiHelper.py:184 in AI_process 后处理: 5.7 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 5.7 毫秒，其中： NMS: 2.4 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.3 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.8 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 11:46:20.935 [WARNING] - step 6-------------------- 处理图片 ./appIOs/samples/illParking/3.jpg-------------------- @ Bussiness_Seg.py:175 in run 11:46:20.938 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 11:46:20.958 [INFO] - [业务分析]业务 总共耗时 22.7 毫秒，其中： AI_Process: 14.7 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 14.7 毫秒，其中： img_pad: 1.9 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 6.1 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.0 毫秒 aiHelper.py:184 in AI_process 后处理: 4.1 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.0 毫秒，其中： NMS: 1.0 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.1 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 7.2 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 11:46:20.959 [WARNING] - step 7-------------------- 处理图片 ./appIOs/samples/illParking/2.jpg-------------------- @ Bussiness_Seg.py:175 in run 11:46:20.961 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 11:46:20.981 [INFO] - [业务分析]业务 总共耗时 21.8 毫秒，其中： AI_Process: 14.0 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 14.0 毫秒，其中： img_pad: 1.1 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 5.7 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.0 毫秒 aiHelper.py:184 in AI_process 后处理: 4.5 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.5 毫秒，其中： NMS: 1.3 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.2 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.9 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 11:46:20.981 [WARNING] - step 8-------------------- 处理图片 ./appIOs/samples/illParking/1.jpg-------------------- @ Bussiness_Seg.py:175 in run 11:46:20.983 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 11:46:21.003 [INFO] - [业务分析]业务 总共耗时 21.8 毫秒，其中： AI_Process: 14.3 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 14.3 毫秒，其中： img_pad: 0.9 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.3 毫秒 aiHelper.py:165 in AI_process infer: 6.1 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.3 毫秒 aiHelper.py:184 in AI_process 后处理: 4.2 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.2 毫秒，其中： NMS: 1.1 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.1 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.7 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 11:46:21.003 [WARNING] - step 9-------------------- 处理图片 ./appIOs/samples/illParking/5.jpg-------------------- @ Bussiness_Seg.py:175 in run 11:46:21.005 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 11:46:21.026 [INFO] - [业务分析]业务 总共耗时 22.5 毫秒，其中： AI_Process: 14.8 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 14.8 毫秒，其中： img_pad: 1.0 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.3 毫秒 aiHelper.py:165 in AI_process infer: 6.7 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.1 毫秒 aiHelper.py:184 in AI_process 后处理: 4.3 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.2 毫秒，其中： NMS: 1.0 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.2 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.9 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 11:46:21.027 [INFO] - step 10: 5 张图片共耗时:635.3 ms ,依次为:127.1 ms, 占用 1 线程 @ Bussiness_Seg.py:187 in run 11:48:30.299 [INFO] - 待测试业务名称: @ main.py:15 in 11:48:30.299 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 11:48:30.300 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 11:48:30.498 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 11:48:30.499 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 11:48:30.500 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:195 in checkFile 11:48:30.500 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:195 in checkFile 11:48:30.500 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:195 in checkFile 11:48:30.500 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:195 in checkFile 11:48:30.501 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:195 in checkFile 11:48:30.501 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:195 in checkFile 11:48:30.501 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 11:48:30.527 [INFO] - select_device YOLOv5 🚀 2025-9-17 torch 2.0.0+cu117 CUDA:0 (NVIDIA GeForce RTX 3090, 24258.625MB) @ torchHelper.py:106 in select_device 11:48:30.528 [INFO] - step 2: 取得参数配置 @ Bussiness_Seg.py:73 in run 11:48:30.691 [INFO] - step 3: 情况 1 - 成功载入 det model trt [./weights/illParking/yolov5_3090_fp16.engine] @ Bussiness_Seg.py:83 in run 11:48:30.716 [INFO] - 加载 stdcModel 模型: ./weights/illParking/stdc_360X640_3090_fp16.engine 类型: trt @ stdc.py:53 in __init__ 11:48:30.740 [INFO] - step 4: 共读入 5 张图片待处理 @ Bussiness_Seg.py:170 in run 11:48:30.741 [WARNING] - step 5-------------------- 处理图片 ./appIOs/samples/illParking/4.jpg-------------------- @ Bussiness_Seg.py:175 in run 11:48:31.206 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 11:48:31.208 [WARNING] - mean not in par, use default mean(0.485, 0.456, 0.406) @ stdc.py:75 in preprocess_image 11:48:31.209 [WARNING] - std not in par, use default std(0.229, 0.224, 0.225) @ stdc.py:78 in preprocess_image 11:48:31.299 [INFO] - [业务分析]业务 总共耗时 557.9 毫秒，其中： AI_Process: 549.9 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 549.9 毫秒，其中： img_pad: 1.7 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.1 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 461.5 毫秒 aiHelper.py:165 in AI_process infer: 14.2 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 66.0 毫秒 aiHelper.py:184 in AI_process 后处理: 6.1 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 6.1 毫秒，其中： NMS: 2.7 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.4 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 7.1 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 11:48:31.299 [WARNING] - step 6-------------------- 处理图片 ./appIOs/samples/illParking/3.jpg-------------------- @ Bussiness_Seg.py:175 in run 11:48:31.302 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 11:48:31.322 [INFO] - [业务分析]业务 总共耗时 22.1 毫秒，其中： AI_Process: 14.2 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 14.2 毫秒，其中： img_pad: 1.7 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 5.7 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.0 毫秒 aiHelper.py:184 in AI_process 后处理: 4.1 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.1 毫秒，其中： NMS: 1.0 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.0 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 7.1 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 11:48:31.322 [WARNING] - step 7-------------------- 处理图片 ./appIOs/samples/illParking/2.jpg-------------------- @ Bussiness_Seg.py:175 in run 11:48:31.324 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 11:48:31.345 [INFO] - [业务分析]业务 总共耗时 22.8 毫秒，其中： AI_Process: 15.1 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 15.0 毫秒，其中： img_pad: 1.0 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 6.8 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.1 毫秒 aiHelper.py:184 in AI_process 后处理: 4.4 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.3 毫秒，其中： NMS: 1.1 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.3 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.9 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 11:48:31.346 [WARNING] - step 8-------------------- 处理图片 ./appIOs/samples/illParking/1.jpg-------------------- @ Bussiness_Seg.py:175 in run 11:48:31.348 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 11:48:31.374 [INFO] - [业务分析]业务 总共耗时 28.3 毫秒，其中： AI_Process: 18.7 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 18.7 毫秒，其中： img_pad: 1.4 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 7.2 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.1 毫秒 aiHelper.py:184 in AI_process 后处理: 6.8 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 6.8 毫秒，其中： NMS: 1.1 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 5.6 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.1 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 9.3 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 11:48:31.375 [WARNING] - step 9-------------------- 处理图片 ./appIOs/samples/illParking/5.jpg-------------------- @ Bussiness_Seg.py:175 in run 11:48:31.377 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 11:48:31.398 [INFO] - [业务分析]业务 总共耗时 23.0 毫秒，其中： AI_Process: 15.2 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 15.1 毫秒，其中： img_pad: 1.1 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 6.9 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.0 毫秒 aiHelper.py:184 in AI_process 后处理: 4.3 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.3 毫秒，其中： NMS: 1.0 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.3 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 7.0 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 11:48:31.398 [INFO] - step 10: 5 张图片共耗时:657.7 ms ,依次为:131.5 ms, 占用 1 线程 @ Bussiness_Seg.py:187 in run 11:49:48.090 [INFO] - 待测试业务名称: @ main.py:15 in 11:49:48.090 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 11:49:48.091 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 11:49:48.285 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 11:49:48.286 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 11:49:48.286 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:195 in checkFile 11:49:48.286 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:195 in checkFile 11:49:48.286 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:195 in checkFile 11:49:48.287 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:195 in checkFile 11:49:48.287 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:195 in checkFile 11:49:48.287 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:195 in checkFile 11:49:48.288 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 11:49:48.315 [INFO] - select_device YOLOv5 🚀 2025-9-17 torch 2.0.0+cu117 CUDA:0 (NVIDIA GeForce RTX 3090, 24258.625MB) @ torchHelper.py:106 in select_device 11:49:48.316 [INFO] - step 2: 取得参数配置 @ Bussiness_Seg.py:73 in run 11:49:48.481 [INFO] - step 3: 情况 1 - 成功载入 det model trt [./weights/illParking/yolov5_3090_fp16.engine] @ Bussiness_Seg.py:83 in run 11:49:48.506 [INFO] - 加载 stdcModel 模型: ./weights/illParking/stdc_360X640_3090_fp16.engine 类型: trt @ stdc.py:53 in __init__ 11:49:48.530 [INFO] - step 4: 共读入 5 张图片待处理 @ Bussiness_Seg.py:170 in run 11:49:48.531 [WARNING] - step 5-------------------- 处理图片 ./appIOs/samples/illParking/4.jpg-------------------- @ Bussiness_Seg.py:175 in run 11:49:48.979 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 11:49:48.981 [WARNING] - mean not in par, use default mean(0.485, 0.456, 0.406) @ stdc.py:75 in preprocess_image 11:49:48.981 [WARNING] - std not in par, use default std(0.229, 0.224, 0.225) @ stdc.py:78 in preprocess_image 11:49:49.069 [INFO] - [业务分析]业务 总共耗时 538.4 毫秒，其中： AI_Process: 530.7 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 530.7 毫秒，其中： img_pad: 1.8 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.1 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 444.7 毫秒 aiHelper.py:165 in AI_process infer: 13.3 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 64.3 毫秒 aiHelper.py:184 in AI_process 后处理: 6.3 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 6.2 毫秒，其中： NMS: 2.9 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.3 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.9 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 11:49:49.070 [WARNING] - step 6-------------------- 处理图片 ./appIOs/samples/illParking/3.jpg-------------------- @ Bussiness_Seg.py:175 in run 11:49:49.073 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 11:49:49.093 [INFO] - [业务分析]业务 总共耗时 22.9 毫秒，其中： AI_Process: 15.3 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 15.3 毫秒，其中： img_pad: 1.8 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 6.6 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 1.9 毫秒 aiHelper.py:184 in AI_process 后处理: 4.1 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.1 毫秒，其中： NMS: 1.0 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.2 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.8 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 11:49:49.094 [WARNING] - step 7-------------------- 处理图片 ./appIOs/samples/illParking/2.jpg-------------------- @ Bussiness_Seg.py:175 in run 11:49:49.096 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 11:49:49.117 [INFO] - [业务分析]业务 总共耗时 22.5 毫秒，其中： AI_Process: 14.9 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 14.9 毫秒，其中： img_pad: 1.2 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 6.5 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.1 毫秒 aiHelper.py:184 in AI_process 后处理: 4.3 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.3 毫秒，其中： NMS: 1.1 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.2 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.8 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 11:49:49.117 [WARNING] - step 8-------------------- 处理图片 ./appIOs/samples/illParking/1.jpg-------------------- @ Bussiness_Seg.py:175 in run 11:49:49.120 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 11:49:49.145 [INFO] - [业务分析]业务 总共耗时 27.4 毫秒，其中： AI_Process: 18.2 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 18.2 毫秒，其中： img_pad: 1.4 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 6.8 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.0 毫秒 aiHelper.py:184 in AI_process 后处理: 6.9 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 6.9 毫秒，其中： NMS: 1.1 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 5.8 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.1 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 9.0 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 11:49:49.145 [WARNING] - step 9-------------------- 处理图片 ./appIOs/samples/illParking/5.jpg-------------------- @ Bussiness_Seg.py:175 in run 11:49:49.147 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 11:49:49.168 [INFO] - [业务分析]业务 总共耗时 23.0 毫秒，其中： AI_Process: 15.4 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 15.4 毫秒，其中： img_pad: 1.1 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.3 毫秒 aiHelper.py:165 in AI_process infer: 7.0 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.4 毫秒 aiHelper.py:184 in AI_process 后处理: 4.3 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.3 毫秒，其中： NMS: 1.2 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.1 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.7 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 11:49:49.169 [INFO] - step 10: 5 张图片共耗时:638.2 ms ,依次为:127.6 ms, 占用 1 线程 @ Bussiness_Seg.py:187 in run 13:32:54.857 [INFO] - 待测试业务名称: @ main.py:15 in 13:32:54.858 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 13:32:54.858 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 13:32:55.048 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 13:32:55.048 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 13:32:55.049 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:195 in checkFile 13:32:55.049 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:195 in checkFile 13:32:55.050 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:195 in checkFile 13:32:55.050 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:195 in checkFile 13:32:55.050 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:195 in checkFile 13:32:55.051 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:195 in checkFile 13:32:55.051 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 13:32:55.077 [INFO] - select_device YOLOv5 🚀 2025-9-17 torch 2.0.0+cu117 CUDA:0 (NVIDIA GeForce RTX 3090, 24258.625MB) @ torchHelper.py:106 in select_device 13:32:55.078 [INFO] - step 2: 取得参数配置 @ Bussiness_Seg.py:73 in run 13:32:55.243 [INFO] - step 3: 情况 1 - 成功载入 det model trt [./weights/illParking/yolov5_3090_fp16.engine] @ Bussiness_Seg.py:83 in run 13:32:55.267 [INFO] - 加载 stdcModel 模型: ./weights/illParking/stdc_360X640_3090_fp16.engine 类型: trt @ stdc.py:53 in __init__ 13:32:55.290 [INFO] - step 4: 共读入 5 张图片待处理 @ Bussiness_Seg.py:170 in run 13:32:55.290 [WARNING] - step 5-------------------- 处理图片 ./appIOs/samples/illParking/4.jpg-------------------- @ Bussiness_Seg.py:175 in run 13:32:55.737 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 13:32:55.739 [WARNING] - mean not in par, use default mean(0.485, 0.456, 0.406) @ stdc.py:75 in preprocess_image 13:32:55.739 [WARNING] - std not in par, use default std(0.229, 0.224, 0.225) @ stdc.py:78 in preprocess_image 13:32:55.827 [INFO] - [业务分析]业务 总共耗时 536.1 毫秒，其中： AI_Process: 528.4 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 528.4 毫秒，其中： img_pad: 1.6 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.1 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 442.9 毫秒 aiHelper.py:165 in AI_process infer: 13.0 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 64.6 毫秒 aiHelper.py:184 in AI_process 后处理: 5.9 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 5.8 毫秒，其中： NMS: 2.5 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.3 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.9 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 13:32:55.827 [WARNING] - step 6-------------------- 处理图片 ./appIOs/samples/illParking/3.jpg-------------------- @ Bussiness_Seg.py:175 in run 13:32:55.830 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 13:32:55.851 [INFO] - [业务分析]业务 总共耗时 22.8 毫秒，其中： AI_Process: 15.1 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 15.1 毫秒，其中： img_pad: 1.8 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 6.4 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.0 毫秒 aiHelper.py:184 in AI_process 后处理: 4.2 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.1 毫秒，其中： NMS: 1.0 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.1 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.9 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 13:32:55.851 [WARNING] - step 7-------------------- 处理图片 ./appIOs/samples/illParking/2.jpg-------------------- @ Bussiness_Seg.py:175 in run 13:32:55.854 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 13:32:55.874 [INFO] - [业务分析]业务 总共耗时 22.2 毫秒，其中： AI_Process: 14.5 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 14.4 毫秒，其中： img_pad: 0.8 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.6 毫秒 aiHelper.py:165 in AI_process infer: 6.5 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.1 毫秒 aiHelper.py:184 in AI_process 后处理: 4.0 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.0 毫秒，其中： NMS: 1.0 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.0 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.9 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 13:32:55.874 [WARNING] - step 8-------------------- 处理图片 ./appIOs/samples/illParking/1.jpg-------------------- @ Bussiness_Seg.py:175 in run 13:32:55.878 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 13:32:55.903 [INFO] - [业务分析]业务 总共耗时 28.1 毫秒，其中： AI_Process: 18.8 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 18.8 毫秒，其中： img_pad: 1.8 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.6 毫秒 aiHelper.py:165 in AI_process infer: 7.2 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 1.9 毫秒 aiHelper.py:184 in AI_process 后处理: 6.6 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 6.6 毫秒，其中： NMS: 1.0 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 5.5 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.1 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 9.1 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 13:32:55.903 [WARNING] - step 9-------------------- 处理图片 ./appIOs/samples/illParking/5.jpg-------------------- @ Bussiness_Seg.py:175 in run 13:32:55.905 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 13:32:55.927 [INFO] - [业务分析]业务 总共耗时 23.4 毫秒，其中： AI_Process: 15.6 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 15.5 毫秒，其中： img_pad: 1.3 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 7.2 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.2 毫秒 aiHelper.py:184 in AI_process 后处理: 4.2 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.1 毫秒，其中： NMS: 1.0 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.1 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 7.0 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 13:32:55.927 [INFO] - step 10: 5 张图片共耗时:636.5 ms ,依次为:127.3 ms, 占用 1 线程 @ Bussiness_Seg.py:187 in run 14:02:22.400 [INFO] - 待测试业务名称: @ main.py:15 in 14:02:22.400 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:02:22.401 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:02:22.595 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:02:22.595 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:02:22.596 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:195 in checkFile 14:02:22.596 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:195 in checkFile 14:02:22.597 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:195 in checkFile 14:02:22.597 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:195 in checkFile 14:02:22.597 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:195 in checkFile 14:02:22.598 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:195 in checkFile 14:02:22.598 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:03:33.347 [INFO] - 待测试业务名称: @ main.py:15 in 14:03:33.348 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:03:33.348 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:03:33.541 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:03:33.542 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:03:33.543 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:196 in checkFile 14:03:33.543 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:196 in checkFile 14:03:33.543 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:196 in checkFile 14:03:33.544 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:196 in checkFile 14:03:33.544 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:196 in checkFile 14:03:33.545 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:196 in checkFile 14:03:33.545 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:04:10.003 [INFO] - 待测试业务名称: @ main.py:15 in 14:04:10.003 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:04:10.003 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:04:10.198 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:04:10.198 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:04:10.199 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:196 in checkFile 14:04:10.199 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:196 in checkFile 14:04:10.199 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:196 in checkFile 14:04:10.200 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:196 in checkFile 14:04:10.200 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:196 in checkFile 14:04:10.200 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:196 in checkFile 14:04:10.201 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:04:38.411 [INFO] - 待测试业务名称: @ main.py:15 in 14:04:38.412 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:04:38.412 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:04:38.603 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:04:38.603 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:04:38.604 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:196 in checkFile 14:04:38.604 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:196 in checkFile 14:04:38.605 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:196 in checkFile 14:04:38.605 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:196 in checkFile 14:04:38.605 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:196 in checkFile 14:04:38.605 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:196 in checkFile 14:04:38.606 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:05:50.927 [INFO] - 待测试业务名称: @ main.py:15 in 14:05:50.928 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:05:50.928 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:05:51.127 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:05:51.128 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:05:51.128 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:05:51.128 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:05:51.129 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:05:51.129 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:05:51.129 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:05:51.130 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:05:51.130 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:06:25.266 [INFO] - 待测试业务名称: @ main.py:15 in 14:06:25.266 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:06:25.266 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:06:25.461 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:06:25.462 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:06:25.462 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:06:25.462 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:06:25.463 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:06:25.463 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:06:25.463 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:06:25.464 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:06:25.464 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:06:59.331 [INFO] - 待测试业务名称: @ main.py:15 in 14:06:59.331 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:06:59.332 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:06:59.522 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:06:59.523 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:06:59.523 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:06:59.524 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:06:59.524 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:06:59.524 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:06:59.525 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:06:59.525 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:06:59.525 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:07:23.751 [INFO] - 待测试业务名称: @ main.py:15 in 14:07:23.752 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:07:23.752 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:07:23.945 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:07:23.946 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:07:23.946 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:07:23.947 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:07:23.947 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:07:23.947 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:07:23.947 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:07:23.948 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:07:23.948 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:07:23.978 [INFO] - select_device YOLOv5 🚀 torch 2.0.0+cu117 CUDA:0 (NVIDIA GeForce RTX 3090, 24258.625MB) @ torchHelper.py:74 in select_device 14:07:23.979 [INFO] - step 2: 取得参数配置 @ Bussiness_Seg.py:73 in run 14:07:24.137 [INFO] - step 3: 情况 1 - 成功载入 det model trt [./weights/illParking/yolov5_3090_fp16.engine] @ Bussiness_Seg.py:83 in run 14:07:24.161 [INFO] - 加载 stdcModel 模型: ./weights/illParking/stdc_360X640_3090_fp16.engine 类型: trt @ stdc.py:53 in __init__ 14:07:24.184 [INFO] - step 4: 共读入 5 张图片待处理 @ Bussiness_Seg.py:170 in run 14:07:24.185 [WARNING] - step 5-------------------- 处理图片 ./appIOs/samples/illParking/4.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:07:24.618 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:07:24.620 [WARNING] - mean not in par, use default mean(0.485, 0.456, 0.406) @ stdc.py:75 in preprocess_image 14:07:24.620 [WARNING] - std not in par, use default std(0.229, 0.224, 0.225) @ stdc.py:78 in preprocess_image 14:07:24.705 [INFO] - [业务分析]业务 总共耗时 519.9 毫秒，其中： AI_Process: 512.1 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 512.1 毫秒，其中： img_pad: 1.8 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.1 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 429.5 毫秒 aiHelper.py:165 in AI_process infer: 13.2 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 61.1 毫秒 aiHelper.py:184 in AI_process 后处理: 6.0 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 6.0 毫秒，其中： NMS: 2.5 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.4 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.9 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:07:24.705 [WARNING] - step 6-------------------- 处理图片 ./appIOs/samples/illParking/3.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:07:24.708 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:07:24.729 [INFO] - [业务分析]业务 总共耗时 23.9 毫秒，其中： AI_Process: 16.1 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 16.1 毫秒，其中： img_pad: 2.0 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.5 毫秒 aiHelper.py:165 in AI_process infer: 6.7 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.1 毫秒 aiHelper.py:184 in AI_process 后处理: 4.4 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.3 毫秒，其中： NMS: 1.2 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.2 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 7.0 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:07:24.730 [WARNING] - step 7-------------------- 处理图片 ./appIOs/samples/illParking/2.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:07:24.732 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:07:24.753 [INFO] - [业务分析]业务 总共耗时 22.3 毫秒，其中： AI_Process: 14.5 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 14.5 毫秒，其中： img_pad: 0.9 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 6.6 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.0 毫秒 aiHelper.py:184 in AI_process 后处理: 4.3 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.3 毫秒，其中： NMS: 1.1 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.2 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 7.0 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:07:24.753 [WARNING] - step 8-------------------- 处理图片 ./appIOs/samples/illParking/1.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:07:24.756 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:07:24.782 [INFO] - [业务分析]业务 总共耗时 28.8 毫秒，其中： AI_Process: 18.9 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 18.9 毫秒，其中： img_pad: 1.6 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 7.4 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.0 毫秒 aiHelper.py:184 in AI_process 后处理: 6.8 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 6.8 毫秒，其中： NMS: 1.0 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 5.8 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.2 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 9.6 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:07:24.783 [WARNING] - step 9-------------------- 处理图片 ./appIOs/samples/illParking/5.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:07:24.785 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:07:24.807 [INFO] - [业务分析]业务 总共耗时 24.0 毫秒，其中： AI_Process: 16.2 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 16.2 毫秒，其中： img_pad: 1.3 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 7.6 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.2 毫秒 aiHelper.py:184 in AI_process 后处理: 4.3 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.2 毫秒，其中： NMS: 1.1 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.2 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 7.0 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:07:24.807 [INFO] - step 10: 5 张图片共耗时:623.0 ms ,依次为:124.6 ms, 占用 1 线程 @ Bussiness_Seg.py:187 in run 14:07:31.613 [INFO] - 待测试业务名称: @ main.py:15 in 14:07:31.614 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:07:31.614 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:07:31.809 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:07:31.810 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:07:31.810 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:07:31.810 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:07:31.811 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:07:31.811 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:07:31.812 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:07:31.812 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:07:31.812 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:39:36.115 [INFO] - 待测试业务名称: @ main.py:15 in 14:39:36.116 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:39:36.116 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:39:36.308 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:39:36.309 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:39:36.309 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:39:36.310 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:39:36.310 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:39:36.310 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:39:36.311 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:39:36.311 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:39:36.312 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:40:00.446 [INFO] - 待测试业务名称: @ main.py:15 in 14:40:00.446 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:40:00.446 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:40:00.642 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:40:00.643 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:40:00.643 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:40:00.643 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:40:00.644 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:40:00.644 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:40:00.644 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:40:00.645 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:40:00.645 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:41:19.176 [INFO] - 待测试业务名称: @ main.py:15 in 14:41:19.177 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:41:19.177 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:41:19.369 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:41:19.370 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:41:19.370 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:41:19.370 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:41:19.371 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:41:19.371 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:41:19.372 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:41:19.372 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:41:19.372 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:41:44.892 [INFO] - 待测试业务名称: @ main.py:15 in 14:41:44.893 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:41:44.893 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:41:45.087 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:41:45.087 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:41:45.088 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:41:45.088 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:41:45.089 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:41:45.089 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:41:45.090 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:41:45.090 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:41:45.090 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:42:23.564 [INFO] - 待测试业务名称: @ main.py:15 in 14:42:23.564 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:42:23.565 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:42:23.757 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:42:23.758 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:42:23.758 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:42:23.759 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:42:23.759 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:42:23.759 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:42:23.760 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:42:23.760 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:42:23.760 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:42:40.698 [INFO] - 待测试业务名称: @ main.py:15 in 14:42:40.698 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:42:40.699 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:42:40.893 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:42:40.894 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:42:40.894 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:42:40.895 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:42:40.895 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:42:40.895 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:42:40.896 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:42:40.896 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:42:40.896 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:43:54.433 [INFO] - 待测试业务名称: @ main.py:15 in 14:43:54.434 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:43:54.434 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:43:54.629 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:43:54.630 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:43:54.630 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:43:54.630 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:43:54.631 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:43:54.631 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:43:54.631 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:43:54.632 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:43:54.632 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:44:38.939 [INFO] - 待测试业务名称: @ main.py:15 in 14:44:38.940 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:44:38.940 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:44:39.133 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:44:39.134 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:44:39.134 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:44:39.135 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:44:39.135 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:44:39.136 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:44:39.136 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:44:39.137 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:44:39.137 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:45:07.678 [INFO] - 待测试业务名称: @ main.py:15 in 14:45:07.679 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:45:07.679 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:45:07.873 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:45:07.874 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:45:07.874 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:45:07.875 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:45:07.875 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:45:07.875 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:45:07.875 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:45:07.876 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:45:07.876 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:45:21.917 [INFO] - 待测试业务名称: @ main.py:15 in 14:45:21.918 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:45:21.918 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:45:22.109 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:45:22.110 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:45:22.111 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:45:22.111 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:45:22.111 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:45:22.112 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:45:22.112 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:45:22.112 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:45:22.113 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:45:36.433 [INFO] - 待测试业务名称: @ main.py:15 in 14:45:36.433 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:45:36.433 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:45:36.626 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:45:36.627 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:45:36.627 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:45:36.627 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:45:36.628 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:45:36.628 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:45:36.629 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:45:36.629 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:45:36.629 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:45:36.657 [INFO] - select_device YOLOv5 🚀 2025-9-19 torch 2.0.0+cu117 CUDA:0 (NVIDIA GeForce RTX 3090, 24258.625MB) @ torchHelper.py:78 in select_device 14:45:36.658 [INFO] - step 2: 取得参数配置 @ Bussiness_Seg.py:73 in run 14:45:36.813 [INFO] - step 3: 情况 1 - 成功载入 det model trt [./weights/illParking/yolov5_3090_fp16.engine] @ Bussiness_Seg.py:83 in run 14:45:36.837 [INFO] - 加载 stdcModel 模型: ./weights/illParking/stdc_360X640_3090_fp16.engine 类型: trt @ stdc.py:53 in __init__ 14:45:36.860 [INFO] - step 4: 共读入 5 张图片待处理 @ Bussiness_Seg.py:170 in run 14:45:36.860 [WARNING] - step 5-------------------- 处理图片 ./appIOs/samples/illParking/4.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:45:37.285 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:45:37.287 [WARNING] - mean not in par, use default mean(0.485, 0.456, 0.406) @ stdc.py:75 in preprocess_image 14:45:37.288 [WARNING] - std not in par, use default std(0.229, 0.224, 0.225) @ stdc.py:78 in preprocess_image 14:45:37.386 [INFO] - [业务分析]业务 总共耗时 525.0 毫秒，其中： AI_Process: 505.4 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 505.4 毫秒，其中： img_pad: 1.8 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.1 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 420.6 毫秒 aiHelper.py:165 in AI_process infer: 14.9 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 62.0 毫秒 aiHelper.py:184 in AI_process 后处理: 5.7 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 5.7 毫秒，其中： NMS: 2.4 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.3 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 18.8 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:45:37.386 [WARNING] - step 6-------------------- 处理图片 ./appIOs/samples/illParking/3.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:45:37.389 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:45:37.410 [INFO] - [业务分析]业务 总共耗时 23.6 毫秒，其中： AI_Process: 16.0 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 16.0 毫秒，其中： img_pad: 1.9 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.6 毫秒 aiHelper.py:165 in AI_process infer: 6.7 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.1 毫秒 aiHelper.py:184 in AI_process 后处理: 4.3 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.3 毫秒，其中： NMS: 1.2 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.1 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.8 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:45:37.411 [WARNING] - step 7-------------------- 处理图片 ./appIOs/samples/illParking/2.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:45:37.413 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:45:37.435 [INFO] - [业务分析]业务 总共耗时 23.8 毫秒，其中： AI_Process: 14.4 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 14.3 毫秒，其中： img_pad: 1.0 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 6.7 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.0 毫秒 aiHelper.py:184 in AI_process 后处理: 4.0 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.0 毫秒，其中： NMS: 1.0 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.0 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 8.6 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:45:37.435 [WARNING] - step 8-------------------- 处理图片 ./appIOs/samples/illParking/1.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:45:37.438 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:45:37.463 [INFO] - [业务分析]业务 总共耗时 27.0 毫秒，其中： AI_Process: 17.5 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 17.5 毫秒，其中： img_pad: 1.4 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.3 毫秒 aiHelper.py:165 in AI_process infer: 6.5 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.0 毫秒 aiHelper.py:184 in AI_process 后处理: 6.6 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 6.6 毫秒，其中： NMS: 1.0 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 5.6 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.1 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 9.2 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:45:37.463 [WARNING] - step 9-------------------- 处理图片 ./appIOs/samples/illParking/5.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:45:37.465 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:45:37.486 [INFO] - [业务分析]业务 总共耗时 22.4 毫秒，其中： AI_Process: 14.8 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 14.8 毫秒，其中： img_pad: 1.0 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 6.6 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.3 毫秒 aiHelper.py:184 in AI_process 后处理: 4.2 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.2 毫秒，其中： NMS: 1.0 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.2 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.8 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:45:37.486 [INFO] - step 10: 5 张图片共耗时:626.0 ms ,依次为:125.2 ms, 占用 1 线程 @ Bussiness_Seg.py:187 in run 14:45:54.396 [INFO] - 待测试业务名称: @ main.py:15 in 14:45:54.396 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:45:54.397 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:45:54.590 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:45:54.590 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:45:54.591 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:45:54.591 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:45:54.591 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:45:54.592 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:45:54.592 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:45:54.592 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:45:54.593 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:45:54.618 [INFO] - select_device YOLOv5 🚀 2025-9-19 torch 2.0.0+cu117 CUDA:0 (NVIDIA GeForce RTX 3090, 24258.625MB) @ torchHelper.py:77 in select_device 14:45:54.619 [INFO] - step 2: 取得参数配置 @ Bussiness_Seg.py:73 in run 14:45:54.773 [INFO] - step 3: 情况 1 - 成功载入 det model trt [./weights/illParking/yolov5_3090_fp16.engine] @ Bussiness_Seg.py:83 in run 14:45:54.796 [INFO] - 加载 stdcModel 模型: ./weights/illParking/stdc_360X640_3090_fp16.engine 类型: trt @ stdc.py:53 in __init__ 14:45:54.820 [INFO] - step 4: 共读入 5 张图片待处理 @ Bussiness_Seg.py:170 in run 14:45:54.820 [WARNING] - step 5-------------------- 处理图片 ./appIOs/samples/illParking/4.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:45:55.251 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:45:55.253 [WARNING] - mean not in par, use default mean(0.485, 0.456, 0.406) @ stdc.py:75 in preprocess_image 14:45:55.254 [WARNING] - std not in par, use default std(0.229, 0.224, 0.225) @ stdc.py:78 in preprocess_image 14:45:55.338 [INFO] - [业务分析]业务 总共耗时 517.7 毫秒，其中： AI_Process: 509.9 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 509.8 毫秒，其中： img_pad: 1.7 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.1 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 427.5 毫秒 aiHelper.py:165 in AI_process infer: 13.3 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 60.8 毫秒 aiHelper.py:184 in AI_process 后处理: 6.1 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 6.1 毫秒，其中： NMS: 2.7 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.4 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 7.0 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:45:55.339 [WARNING] - step 6-------------------- 处理图片 ./appIOs/samples/illParking/3.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:45:55.342 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:45:55.362 [INFO] - [业务分析]业务 总共耗时 23.1 毫秒，其中： AI_Process: 15.4 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 15.4 毫秒，其中： img_pad: 1.7 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 6.3 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.2 毫秒 aiHelper.py:184 in AI_process 后处理: 4.4 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.4 毫秒，其中： NMS: 1.1 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.3 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.9 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:45:55.362 [WARNING] - step 7-------------------- 处理图片 ./appIOs/samples/illParking/2.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:45:55.364 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:45:55.385 [INFO] - [业务分析]业务 总共耗时 22.1 毫秒，其中： AI_Process: 14.5 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 14.5 毫秒，其中： img_pad: 0.9 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.3 毫秒 aiHelper.py:165 in AI_process infer: 6.2 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.2 毫秒 aiHelper.py:184 in AI_process 后处理: 4.4 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.4 毫秒，其中： NMS: 1.1 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.3 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.8 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:45:55.385 [WARNING] - step 8-------------------- 处理图片 ./appIOs/samples/illParking/1.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:45:55.389 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:45:55.415 [INFO] - [业务分析]业务 总共耗时 28.9 毫秒，其中： AI_Process: 19.5 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 19.5 毫秒，其中： img_pad: 1.7 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.5 毫秒 aiHelper.py:165 in AI_process infer: 7.6 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.1 毫秒 aiHelper.py:184 in AI_process 后处理: 6.8 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 6.8 毫秒，其中： NMS: 1.1 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 5.7 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.1 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 9.1 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:45:55.415 [WARNING] - step 9-------------------- 处理图片 ./appIOs/samples/illParking/5.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:45:55.417 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:45:55.438 [INFO] - [业务分析]业务 总共耗时 23.0 毫秒，其中： AI_Process: 14.9 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 14.9 毫秒，其中： img_pad: 0.9 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.5 毫秒 aiHelper.py:165 in AI_process infer: 6.8 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.1 毫秒 aiHelper.py:184 in AI_process 后处理: 4.2 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.2 毫秒，其中： NMS: 1.0 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.2 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 7.3 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:45:55.439 [INFO] - step 10: 5 张图片共耗时:618.7 ms ,依次为:123.7 ms, 占用 1 线程 @ Bussiness_Seg.py:187 in run 14:46:02.358 [INFO] - 待测试业务名称: @ main.py:15 in 14:46:02.358 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:46:02.358 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:46:02.549 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:46:02.550 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:46:02.550 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:46:02.551 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:46:02.551 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:46:02.551 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:46:02.552 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:46:02.552 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:46:02.552 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:57 in run 14:46:32.124 [INFO] - 待测试业务名称: @ main.py:15 in 14:46:32.125 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:46:32.125 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:46:32.321 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:306 in __init__ 14:46:32.322 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:46:32.322 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:46:32.323 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:46:32.323 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:46:32.323 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:46:32.324 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:46:32.324 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:46:32.324 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:56 in run 14:47:11.982 [INFO] - 待测试业务名称: @ main.py:15 in 14:47:11.982 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:47:11.982 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:47:12.180 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:306 in __init__ 14:47:12.181 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:47:12.181 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:47:12.181 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:47:12.182 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:47:12.182 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:47:12.182 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:47:12.183 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:47:12.183 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:56 in run 14:47:12.209 [INFO] - select_device YOLOv5 🚀 2025-9-19 torch 2.0.0+cu117 CUDA:0 (NVIDIA GeForce RTX 3090, 24258.625MB) @ torchHelper.py:77 in select_device 14:47:12.211 [INFO] - step 2: 取得参数配置 @ Bussiness_Seg.py:72 in run 14:47:12.369 [INFO] - step 3: 情况 1 - 成功载入 det model trt [./weights/illParking/yolov5_3090_fp16.engine] @ Bussiness_Seg.py:82 in run 14:47:12.395 [INFO] - 加载 stdcModel 模型: ./weights/illParking/stdc_360X640_3090_fp16.engine 类型: trt @ stdc.py:53 in __init__ 14:47:12.418 [INFO] - step 4: 共读入 5 张图片待处理 @ Bussiness_Seg.py:169 in run 14:47:12.419 [WARNING] - step 5-------------------- 处理图片 ./appIOs/samples/illParking/4.jpg-------------------- @ Bussiness_Seg.py:174 in run 14:47:12.848 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:47:12.850 [WARNING] - mean not in par, use default mean(0.485, 0.456, 0.406) @ stdc.py:75 in preprocess_image 14:47:12.850 [WARNING] - std not in par, use default std(0.229, 0.224, 0.225) @ stdc.py:78 in preprocess_image 14:47:12.935 [INFO] - [业务分析]业务 总共耗时 515.7 毫秒，其中： AI_Process: 507.8 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 507.8 毫秒，其中： img_pad: 1.6 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.1 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 425.1 毫秒 aiHelper.py:165 in AI_process infer: 14.2 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 60.9 毫秒 aiHelper.py:184 in AI_process 后处理: 5.7 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 5.7 毫秒，其中： NMS: 2.3 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.3 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 7.0 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:47:12.935 [WARNING] - step 6-------------------- 处理图片 ./appIOs/samples/illParking/3.jpg-------------------- @ Bussiness_Seg.py:174 in run 14:47:12.938 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:47:12.958 [INFO] - [业务分析]业务 总共耗时 22.4 毫秒，其中： AI_Process: 14.7 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 14.7 毫秒，其中： img_pad: 1.6 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.3 毫秒 aiHelper.py:165 in AI_process infer: 5.8 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.2 毫秒 aiHelper.py:184 in AI_process 后处理: 4.3 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.3 毫秒，其中： NMS: 1.1 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.2 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 7.0 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:47:12.959 [WARNING] - step 7-------------------- 处理图片 ./appIOs/samples/illParking/2.jpg-------------------- @ Bussiness_Seg.py:174 in run 14:47:12.961 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:47:12.982 [INFO] - [业务分析]业务 总共耗时 22.8 毫秒，其中： AI_Process: 15.0 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 15.0 毫秒，其中： img_pad: 1.3 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 6.2 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.2 毫秒 aiHelper.py:184 in AI_process 后处理: 4.5 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.5 毫秒，其中： NMS: 1.2 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.3 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.9 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:47:12.982 [WARNING] - step 8-------------------- 处理图片 ./appIOs/samples/illParking/1.jpg-------------------- @ Bussiness_Seg.py:174 in run 14:47:12.984 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:47:13.009 [INFO] - [业务分析]业务 总共耗时 27.0 毫秒，其中： AI_Process: 17.6 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 17.6 毫秒，其中： img_pad: 1.4 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.3 毫秒 aiHelper.py:165 in AI_process infer: 6.4 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.2 毫秒 aiHelper.py:184 in AI_process 后处理: 6.7 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 6.7 毫秒，其中： NMS: 1.1 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 5.5 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.2 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 9.1 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:47:13.010 [WARNING] - step 9-------------------- 处理图片 ./appIOs/samples/illParking/5.jpg-------------------- @ Bussiness_Seg.py:174 in run 14:47:13.012 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:47:13.034 [INFO] - [业务分析]业务 总共耗时 23.3 毫秒，其中： AI_Process: 15.5 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 15.5 毫秒，其中： img_pad: 1.0 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 7.6 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 1.9 毫秒 aiHelper.py:184 in AI_process 后处理: 4.2 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.2 毫秒，其中： NMS: 1.0 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.2 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 7.0 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:47:13.034 [INFO] - step 10: 5 张图片共耗时:615.0 ms ,依次为:123.0 ms, 占用 1 线程 @ Bussiness_Seg.py:186 in run 14:49:09.918 [INFO] - 待测试业务名称: @ main.py:15 in 14:49:09.918 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:49:09.918 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:49:10.110 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:306 in __init__ 14:49:10.111 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:49:10.111 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:49:10.112 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:49:10.112 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:49:10.112 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:49:10.113 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:49:10.113 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:49:10.113 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:56 in run 14:49:10.141 [INFO] - select_device YOLOv5 🚀 2025-9-19 torch 2.0.0+cu117 CUDA:0 (NVIDIA GeForce RTX 3090, 24258.625MB) @ torchHelper.py:75 in select_device 14:49:10.142 [INFO] - step 2: 取得参数配置 @ Bussiness_Seg.py:72 in run 14:49:10.299 [INFO] - step 3: 情况 1 - 成功载入 det model trt [./weights/illParking/yolov5_3090_fp16.engine] @ Bussiness_Seg.py:82 in run 14:49:10.323 [INFO] - 加载 stdcModel 模型: ./weights/illParking/stdc_360X640_3090_fp16.engine 类型: trt @ stdc.py:53 in __init__ 14:49:10.347 [INFO] - step 4: 共读入 5 张图片待处理 @ Bussiness_Seg.py:169 in run 14:49:10.347 [WARNING] - step 5-------------------- 处理图片 ./appIOs/samples/illParking/4.jpg-------------------- @ Bussiness_Seg.py:174 in run 14:49:10.773 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:49:10.775 [WARNING] - mean not in par, use default mean(0.485, 0.456, 0.406) @ stdc.py:75 in preprocess_image 14:49:10.776 [WARNING] - std not in par, use default std(0.229, 0.224, 0.225) @ stdc.py:78 in preprocess_image 14:49:10.902 [INFO] - [业务分析]业务 总共耗时 554.5 毫秒，其中： AI_Process: 505.7 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 505.7 毫秒，其中： img_pad: 1.6 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.1 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 422.1 毫秒 aiHelper.py:165 in AI_process infer: 14.1 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 61.2 毫秒 aiHelper.py:184 in AI_process 后处理: 6.3 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 6.2 毫秒，其中： NMS: 2.9 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.3 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.8 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 47.6 毫秒 Bussiness.py:93 in doAnalysis fp: 0.4 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:49:10.903 [WARNING] - step 6-------------------- 处理图片 ./appIOs/samples/illParking/3.jpg-------------------- @ Bussiness_Seg.py:174 in run 14:49:10.917 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:49:10.969 [INFO] - [业务分析]业务 总共耗时 58.2 毫秒，其中： AI_Process: 40.6 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 40.5 毫秒，其中： img_pad: 5.0 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.1 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.6 毫秒 aiHelper.py:165 in AI_process infer: 15.9 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 4.9 毫秒 aiHelper.py:184 in AI_process 后处理: 13.1 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 13.0 毫秒，其中： NMS: 4.1 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 8.9 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 2.0 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 15.2 毫秒 Bussiness.py:93 in doAnalysis fp: 0.3 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:49:10.970 [WARNING] - step 7-------------------- 处理图片 ./appIOs/samples/illParking/2.jpg-------------------- @ Bussiness_Seg.py:174 in run 14:49:10.973 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:49:11.003 [INFO] - [业务分析]业务 总共耗时 32.4 毫秒，其中： AI_Process: 20.9 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 20.9 毫秒，其中： img_pad: 1.5 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 9.8 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.5 毫秒 aiHelper.py:184 in AI_process 后处理: 6.2 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 6.2 毫秒，其中： NMS: 1.5 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 4.6 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 1.0 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 10.3 毫秒 Bussiness.py:93 in doAnalysis fp: 0.2 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:49:11.003 [WARNING] - step 8-------------------- 处理图片 ./appIOs/samples/illParking/1.jpg-------------------- @ Bussiness_Seg.py:174 in run 14:49:11.007 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:49:11.043 [INFO] - [业务分析]业务 总共耗时 39.0 毫秒，其中： AI_Process: 24.8 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 24.7 毫秒，其中： img_pad: 2.1 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 9.3 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.5 毫秒 aiHelper.py:184 in AI_process 后处理: 9.5 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 9.5 毫秒，其中： NMS: 1.5 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 8.0 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.3 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 13.8 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:49:11.044 [WARNING] - step 9-------------------- 处理图片 ./appIOs/samples/illParking/5.jpg-------------------- @ Bussiness_Seg.py:174 in run 14:49:11.046 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:49:11.069 [INFO] - [业务分析]业务 总共耗时 24.8 毫秒，其中： AI_Process: 16.7 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 16.6 毫秒，其中： img_pad: 1.5 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 7.3 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.4 毫秒 aiHelper.py:184 in AI_process 后处理: 4.7 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.7 毫秒，其中： NMS: 1.2 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.5 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.8 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 7.2 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:49:11.069 [INFO] - step 10: 5 张图片共耗时:722.1 ms ,依次为:144.4 ms, 占用 1 线程 @ Bussiness_Seg.py:186 in run 14:50:12.079 [INFO] - 待测试业务名称: @ main.py:15 in 14:50:12.079 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:50:12.080 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:50:12.273 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:50:12.274 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:50:12.274 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:50:12.274 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:50:12.275 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:50:12.275 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:50:12.275 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:50:12.276 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:50:12.276 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:56 in run 14:50:58.328 [INFO] - 待测试业务名称: @ main.py:15 in 14:50:58.328 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:50:58.329 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:50:58.523 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:50:58.524 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:50:58.524 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:50:58.525 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:50:58.525 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:50:58.525 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:50:58.526 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:50:58.526 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:50:58.526 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:56 in run 14:50:58.552 [INFO] - select_device YOLOv5 🚀 2025-9-19 torch 2.0.0+cu117 CUDA:0 (NVIDIA GeForce RTX 3090, 24258.625MB) @ torchHelper.py:74 in select_device 14:50:58.553 [INFO] - step 2: 取得参数配置 @ Bussiness_Seg.py:73 in run 14:50:58.714 [INFO] - step 3: 情况 1 - 成功载入 det model trt [./weights/illParking/yolov5_3090_fp16.engine] @ Bussiness_Seg.py:83 in run 14:50:58.738 [INFO] - 加载 stdcModel 模型: ./weights/illParking/stdc_360X640_3090_fp16.engine 类型: trt @ stdc.py:53 in __init__ 14:50:58.761 [INFO] - step 4: 共读入 5 张图片待处理 @ Bussiness_Seg.py:170 in run 14:50:58.761 [WARNING] - step 5-------------------- 处理图片 ./appIOs/samples/illParking/4.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:50:59.194 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:50:59.196 [WARNING] - mean not in par, use default mean(0.485, 0.456, 0.406) @ stdc.py:75 in preprocess_image 14:50:59.196 [WARNING] - std not in par, use default std(0.229, 0.224, 0.225) @ stdc.py:78 in preprocess_image 14:50:59.281 [INFO] - [业务分析]业务 总共耗时 519.3 毫秒，其中： AI_Process: 511.5 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 511.5 毫秒，其中： img_pad: 1.5 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.1 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 428.7 毫秒 aiHelper.py:165 in AI_process infer: 13.7 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 60.9 毫秒 aiHelper.py:184 in AI_process 后处理: 6.2 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 6.2 毫秒，其中： NMS: 2.8 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.3 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.9 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:50:59.282 [WARNING] - step 6-------------------- 处理图片 ./appIOs/samples/illParking/3.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:50:59.284 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:50:59.305 [INFO] - [业务分析]业务 总共耗时 23.2 毫秒，其中： AI_Process: 15.5 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 15.5 毫秒，其中： img_pad: 1.7 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 6.6 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.1 毫秒 aiHelper.py:184 in AI_process 后处理: 4.3 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.3 毫秒，其中： NMS: 1.1 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.2 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.9 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:50:59.306 [WARNING] - step 7-------------------- 处理图片 ./appIOs/samples/illParking/2.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:50:59.308 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:50:59.329 [INFO] - [业务分析]业务 总共耗时 22.7 毫秒，其中： AI_Process: 15.0 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 14.9 毫秒，其中： img_pad: 0.9 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 6.8 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.2 毫秒 aiHelper.py:184 in AI_process 后处理: 4.3 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.3 毫秒，其中： NMS: 1.1 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.2 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.9 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:50:59.329 [WARNING] - step 8-------------------- 处理图片 ./appIOs/samples/illParking/1.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:50:59.332 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:50:59.359 [INFO] - [业务分析]业务 总共耗时 29.0 毫秒，其中： AI_Process: 19.5 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 19.5 毫秒，其中： img_pad: 1.7 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 7.8 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.0 毫秒 aiHelper.py:184 in AI_process 后处理: 6.8 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 6.7 毫秒，其中： NMS: 1.0 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 5.7 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.2 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 9.2 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:50:59.359 [WARNING] - step 9-------------------- 处理图片 ./appIOs/samples/illParking/5.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:50:59.361 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:50:59.382 [INFO] - [业务分析]业务 总共耗时 22.8 毫秒，其中： AI_Process: 15.1 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 15.1 毫秒，其中： img_pad: 1.0 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 6.8 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.3 毫秒 aiHelper.py:184 in AI_process 后处理: 4.2 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.2 毫秒，其中： NMS: 1.1 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.1 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.9 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:50:59.383 [INFO] - step 10: 5 张图片共耗时:621.1 ms ,依次为:124.2 ms, 占用 1 线程 @ Bussiness_Seg.py:187 in run 14:51:38.374 [INFO] - 待测试业务名称: @ main.py:15 in 14:51:38.375 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 14:51:38.375 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 14:51:38.570 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 14:51:38.571 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 14:51:38.571 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 14:51:38.571 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:51:38.572 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 14:51:38.572 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 14:51:38.573 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 14:51:38.573 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 14:51:38.573 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:56 in run 14:51:38.618 [INFO] - select_device YOLOv5 🚀 2025-9-19 torch 2.0.0+cu117 CUDA:0 (NVIDIA GeForce RTX 3090, 24258.625MB) @ torchHelper.py:73 in select_device 14:51:38.619 [INFO] - step 2: 取得参数配置 @ Bussiness_Seg.py:73 in run 14:51:38.784 [INFO] - step 3: 情况 1 - 成功载入 det model trt [./weights/illParking/yolov5_3090_fp16.engine] @ Bussiness_Seg.py:83 in run 14:51:38.808 [INFO] - 加载 stdcModel 模型: ./weights/illParking/stdc_360X640_3090_fp16.engine 类型: trt @ stdc.py:53 in __init__ 14:51:38.832 [INFO] - step 4: 共读入 5 张图片待处理 @ Bussiness_Seg.py:170 in run 14:51:38.833 [WARNING] - step 5-------------------- 处理图片 ./appIOs/samples/illParking/4.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:51:39.263 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:51:39.264 [WARNING] - mean not in par, use default mean(0.485, 0.456, 0.406) @ stdc.py:75 in preprocess_image 14:51:39.265 [WARNING] - std not in par, use default std(0.229, 0.224, 0.225) @ stdc.py:78 in preprocess_image 14:51:39.351 [INFO] - [业务分析]业务 总共耗时 517.7 毫秒，其中： AI_Process: 509.9 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 509.8 毫秒，其中： img_pad: 1.6 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.1 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 426.6 毫秒 aiHelper.py:165 in AI_process infer: 13.1 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 62.3 毫秒 aiHelper.py:184 in AI_process 后处理: 5.9 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 5.8 毫秒，其中： NMS: 2.4 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.4 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 7.0 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:51:39.351 [WARNING] - step 6-------------------- 处理图片 ./appIOs/samples/illParking/3.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:51:39.354 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:51:39.374 [INFO] - [业务分析]业务 总共耗时 22.7 毫秒，其中： AI_Process: 14.8 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 14.8 毫秒，其中： img_pad: 1.7 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 5.9 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.2 毫秒 aiHelper.py:184 in AI_process 后处理: 4.2 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.2 毫秒，其中： NMS: 1.1 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.1 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 7.0 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:51:39.375 [WARNING] - step 7-------------------- 处理图片 ./appIOs/samples/illParking/2.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:51:39.377 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:51:39.398 [INFO] - [业务分析]业务 总共耗时 22.8 毫秒，其中： AI_Process: 14.8 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 14.8 毫秒，其中： img_pad: 1.1 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 6.5 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.0 毫秒 aiHelper.py:184 in AI_process 后处理: 4.4 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.4 毫秒，其中： NMS: 1.0 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.4 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 7.2 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:51:39.398 [WARNING] - step 8-------------------- 处理图片 ./appIOs/samples/illParking/1.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:51:39.401 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:51:39.425 [INFO] - [业务分析]业务 总共耗时 27.0 毫秒，其中： AI_Process: 17.6 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 17.6 毫秒，其中： img_pad: 1.4 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.3 毫秒 aiHelper.py:165 in AI_process infer: 6.1 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.1 毫秒 aiHelper.py:184 in AI_process 后处理: 7.0 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 7.0 毫秒，其中： NMS: 1.3 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 5.7 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.2 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 9.0 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:51:39.426 [WARNING] - step 9-------------------- 处理图片 ./appIOs/samples/illParking/5.jpg-------------------- @ Bussiness_Seg.py:175 in run 14:51:39.428 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 14:51:39.449 [INFO] - [业务分析]业务 总共耗时 22.8 毫秒，其中： AI_Process: 15.1 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 15.0 毫秒，其中： img_pad: 1.1 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 6.7 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.2 毫秒 aiHelper.py:184 in AI_process 后处理: 4.3 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.2 毫秒，其中： NMS: 1.1 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.2 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.9 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 14:51:39.450 [INFO] - step 10: 5 张图片共耗时:617.0 ms ,依次为:123.4 ms, 占用 1 线程 @ Bussiness_Seg.py:187 in run 16:26:04.590 [INFO] - 待测试业务名称: @ main.py:15 in 16:26:04.590 [INFO] - -------------------- 开始业务 [illParking] -------------------- @ main.py:19 in 16:26:04.590 [INFO] - bussiness: illParking @ Bussiness.py:16 in createModel 16:26:04.980 [INFO] - create AlAlg_IllParking @ Bussiness_Seg.py:307 in __init__ 16:26:04.982 [WARNING] - [illParking] 业务配置 - ['device', 'labelnames', 'max_workers', 'Detweights', 'detModelpara', 'seg_nclass', 'segRegionCnt', 'Segweights', 'postFile', 'txtFontSize', 'digitFont', 'testImgPath', 'testOutPath', 'segPar'] - 重点配置： 检测类别(labelnames):./weights/conf/illParking/labelnames.json >>>>>> ['车', 'T角点', 'L角点', '违停'] 检测模型路径(Detweights): ./weights/illParking/yolov5_3090_fp16.engine 分割模型权重文件(Segweights): ./weights/illParking/stdc_360X640_3090_fp16.engine 后处理参数文件(postFile): ./weights/conf/illParking/para.json 测试图像路径(testImgPath): ./appIOs/samples/illParking/ 输出图像位置(testOutPath): ./appIOs/results/illParking/ 输出图像路径: ./appIOs/results/illParking/ @ Bussiness.py:39 in __init__ 16:26:04.982 [INFO] - 检测类别 - ./weights/conf/illParking/labelnames.json 存在 @ drHelper.py:197 in checkFile 16:26:04.982 [INFO] - 检测模型路径 - ./weights/illParking/yolov5_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 16:26:04.983 [INFO] - 后处理参数文件 - ./weights/conf/illParking/para.json 存在 @ drHelper.py:197 in checkFile 16:26:04.983 [INFO] - 分割模型权重文件 - ./weights/illParking/stdc_360X640_3090_fp16.engine 存在 @ drHelper.py:197 in checkFile 16:26:04.983 [INFO] - 测试图像路径 - ./appIOs/samples/illParking/ 存在 @ drHelper.py:197 in checkFile 16:26:04.984 [INFO] - 输出图像路径 - ./appIOs/results/illParking/ 存在 @ drHelper.py:197 in checkFile 16:26:04.984 [INFO] - step 1: 业务分析配置 - trtFlag_seg: True, trtFlag_det: True @ Bussiness_Seg.py:56 in run 16:26:05.020 [INFO] - select_device YOLOv5 🚀 2025-9-19 torch 2.0.0+cu117 CUDA:0 (NVIDIA GeForce RTX 3090, 24258.625MB) @ torchHelper.py:73 in select_device 16:26:05.021 [INFO] - step 2: 取得参数配置 @ Bussiness_Seg.py:73 in run 16:26:05.235 [INFO] - step 3: 情况 1 - 成功载入 det model trt [./weights/illParking/yolov5_3090_fp16.engine] @ Bussiness_Seg.py:83 in run 16:26:05.261 [INFO] - 加载 stdcModel 模型: ./weights/illParking/stdc_360X640_3090_fp16.engine 类型: trt @ stdc.py:53 in __init__ 16:26:05.308 [INFO] - step 4: 共读入 5 张图片待处理 @ Bussiness_Seg.py:170 in run 16:26:05.309 [WARNING] - step 5-------------------- 处理图片 ./appIOs/samples/illParking/4.jpg-------------------- @ Bussiness_Seg.py:175 in run 16:26:05.754 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 16:26:05.757 [WARNING] - mean not in par, use default mean(0.485, 0.456, 0.406) @ stdc.py:75 in preprocess_image 16:26:05.757 [WARNING] - std not in par, use default std(0.229, 0.224, 0.225) @ stdc.py:78 in preprocess_image 16:26:05.849 [INFO] - [业务分析]业务 总共耗时 539.3 毫秒，其中： AI_Process: 531.6 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 531.5 毫秒，其中： img_pad: 1.6 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.1 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 441.4 毫秒 aiHelper.py:165 in AI_process infer: 14.7 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 67.6 毫秒 aiHelper.py:184 in AI_process 后处理: 5.8 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 5.8 毫秒，其中： NMS: 2.6 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.2 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.9 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 16:26:05.849 [WARNING] - step 6-------------------- 处理图片 ./appIOs/samples/illParking/3.jpg-------------------- @ Bussiness_Seg.py:175 in run 16:26:05.853 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 16:26:05.873 [INFO] - [业务分析]业务 总共耗时 23.4 毫秒，其中： AI_Process: 15.5 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 15.5 毫秒，其中： img_pad: 2.2 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 6.5 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.0 毫秒 aiHelper.py:184 in AI_process 后处理: 4.0 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.0 毫秒，其中： NMS: 1.0 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.0 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 7.0 毫秒 Bussiness.py:93 in doAnalysis fp: 0.2 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 16:26:05.874 [WARNING] - step 7-------------------- 处理图片 ./appIOs/samples/illParking/2.jpg-------------------- @ Bussiness_Seg.py:175 in run 16:26:05.877 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 16:26:05.897 [INFO] - [业务分析]业务 总共耗时 22.2 毫秒，其中： AI_Process: 14.4 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 14.4 毫秒，其中： img_pad: 1.2 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.4 毫秒 aiHelper.py:165 in AI_process infer: 6.1 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.0 毫秒 aiHelper.py:184 in AI_process 后处理: 4.3 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.2 毫秒，其中： NMS: 1.0 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.2 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 7.0 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 16:26:05.897 [WARNING] - step 8-------------------- 处理图片 ./appIOs/samples/illParking/1.jpg-------------------- @ Bussiness_Seg.py:175 in run 16:26:05.900 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 16:26:05.925 [INFO] - [业务分析]业务 总共耗时 27.4 毫秒，其中： AI_Process: 18.1 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 18.0 毫秒，其中： img_pad: 1.4 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.3 毫秒 aiHelper.py:165 in AI_process infer: 6.7 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.2 毫秒 aiHelper.py:184 in AI_process 后处理: 6.7 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 6.6 毫秒，其中： NMS: 1.1 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 5.5 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.1 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 9.1 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 16:26:05.925 [WARNING] - step 9-------------------- 处理图片 ./appIOs/samples/illParking/5.jpg-------------------- @ Bussiness_Seg.py:175 in run 16:26:05.927 [WARNING] - modelSize not in par, use default size(640, 360) @ stdc.py:66 in preprocess_image 16:26:05.948 [INFO] - [业务分析]业务 总共耗时 22.4 毫秒，其中： AI_Process: 14.9 毫秒 Bussiness.py:80 in doAnalysis -> [AI_process]业务 总共耗时 14.8 毫秒，其中： img_pad: 1.0 毫秒 aiHelper.py:159 in AI_process from_numpy(640 x 640): 0.0 毫秒 aiHelper.py:163 in AI_process to GPU(640 x 640): 0.3 毫秒 aiHelper.py:165 in AI_process infer: 6.6 毫秒 aiHelper.py:177 in AI_process yolov5Trtforward: 2.0 毫秒 aiHelper.py:184 in AI_process 后处理: 4.5 毫秒 aiHelper.py:191 in AI_process -> [预测结果后处理]业务 总共耗时 4.5 毫秒，其中： NMS: 1.2 毫秒 aiHelper.py:40 in getDetectionsFromPreds ScaleBack: 3.2 毫秒 aiHelper.py:65 in getDetectionsFromPreds drawAllBox: 0.7 毫秒 Bussiness.py:82 in doAnalysis testOutPath: 6.8 毫秒 Bussiness.py:93 in doAnalysis fp: 0.1 毫秒 Bussiness.py:100 in doAnalysis @ Bussiness.py:102 in doAnalysis 16:26:05.948 [INFO] - step 10: 5 张图片共耗时:639.5 ms ,依次为:127.9 ms, 占用 1 线程 @ Bussiness_Seg.py:187 in run