66 KiB
66 KiB
nohup: ignoring input
2022-11-29 08:44:22,208 INFO sqlalchemy.engine.Engine select pg_catalog.version()
2022-11-29 08:44:22,209 INFO sqlalchemy.engine.Engine [raw sql] {}
2022-11-29 08:44:22,214 INFO sqlalchemy.engine.Engine select current_schema()
2022-11-29 08:44:22,214 INFO sqlalchemy.engine.Engine [raw sql] {}
2022-11-29 08:44:22,219 INFO sqlalchemy.engine.Engine show standard_conforming_strings
2022-11-29 08:44:22,219 INFO sqlalchemy.engine.Engine [raw sql] {}
2022-11-29 08:44:22,225 INFO sqlalchemy.engine.Engine BEGIN (implicit)
2022-11-29 08:44:22,225 INFO sqlalchemy.engine.Engine COMMIT
detect_server: id=195095688265211904_17_detect, weights=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights//核酸检测_190857268466688000_R-ODY_17_640.pt, source=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/camera, output=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/results, data=app/yolov5/data/coco128.yaml, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=0, view_img=False, save_txt=True, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=app/yolov5/runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1
YOLOv5 🚀 2022-11-7 Python-3.8.13 torch-1.8.0+cu111 CUDA:0 (Tesla T4, 15110MiB)
2022-11-29 08:44:36.902619: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 AVX512F AVX512_VNNI FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-11-29 08:44:37.033367: I tensorflow/core/util/util.cc:169] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2022-11-29 08:44:37.070603: E tensorflow/stream_executor/cuda/cuda_blas.cc:2981] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2022-11-29 08:44:37.607302: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/cv2/../../lib64::/usr/local/cuda/lib64
2022-11-29 08:44:37.607416: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/cv2/../../lib64::/usr/local/cuda/lib64
2022-11-29 08:44:37.607434: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
Fusing layers...
192.168.0.20 - - [2022-11-29 08:44:42] "GET /api/obtain_detect_param HTTP/1.1" 200 1110 0.000672
192.168.0.20 - - [2022-11-29 08:44:42] "GET /api/start_detect_algorithm?param=%5B%7B%22index%22%3A+0%2C+%22name%22%3A+%22inputPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2F195095688265211904%2Fcamera%22%2C+%22description%22%3A+%22%5Cu8f93%5Cu5165%5Cu56fe%5Cu50cf%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fdatasets%2FM006B_waibi%2FJPEGImages%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+1%2C+%22name%22%3A+%22outputPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2F195095688265211904%2Fresults%22%2C+%22description%22%3A+%22%5Cu8f93%5Cu51fa%5Cu7ed3%5Cu679c%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fdatasets%2FM006B_waibi%2Fres%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+2%2C+%22name%22%3A+%22modPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F%2F%5Cu6838%5Cu9178%5Cu68c0%5Cu6d4b_190857268466688000_R-ODY_17_640.pt%22%2C+%22description%22%3A+%22%5Cu6a21%5Cu578b%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fsaved_model%2Ftest.pt%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+3%2C+%22name%22%3A+%22device%22%2C+%22value%22%3A+%220%22%2C+%22description%22%3A+%22%5Cu63a8%5Cu7406%5Cu6838%22%2C+%22default%22%3A+%22cpu%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%5D&id=195095688265211904_17_detect HTTP/1.1" 200 161 0.002945
detect_server: id=195095688265211904_17_detect, weights=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights//核酸检测_190857268466688000_R-ODY_17_640.pt, source=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/camera, output=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/results, data=app/yolov5/data/coco128.yaml, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=0, view_img=False, save_txt=True, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=app/yolov5/runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1
YOLOv5 🚀 2022-11-7 Python-3.8.13 torch-1.8.0+cu111 CUDA:0 (Tesla T4, 15110MiB)
Fusing layers...
Model summary: 213 layers, 7020913 parameters, 0 gradients, 15.8 GFLOPs
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Model summary: 213 layers, 7020913 parameters, 0 gradients, 15.8 GFLOPs
image 1/1 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/camera/微信截图_20221129084118.png: 640x512 1 zui, 1 mianbang, 23.9ms
Speed: 0.4ms pre-process, 23.9ms inference, 1.5ms NMS per image at shape (1, 3, 640, 640)
image 1/1 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/camera/微信截图_20221129084118.png: 640x512 1 zui, 1 mianbang, 21.2ms
Speed: 0.4ms pre-process, 21.2ms inference, 1.1ms NMS per image at shape (1, 3, 640, 640)
192.168.0.20 - - [2022-11-29 08:46:07] "GET /api/obtain_detect_param HTTP/1.1" 200 1110 0.000634
192.168.0.20 - - [2022-11-29 08:46:07] "GET /api/start_detect_algorithm?param=%5B%7B%22index%22%3A+0%2C+%22name%22%3A+%22inputPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2F195095688265211904%2Fcamera%22%2C+%22description%22%3A+%22%5Cu8f93%5Cu5165%5Cu56fe%5Cu50cf%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fdatasets%2FM006B_waibi%2FJPEGImages%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+1%2C+%22name%22%3A+%22outputPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2F195095688265211904%2Fresults%22%2C+%22description%22%3A+%22%5Cu8f93%5Cu51fa%5Cu7ed3%5Cu679c%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fdatasets%2FM006B_waibi%2Fres%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+2%2C+%22name%22%3A+%22modPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F%2F%5Cu6838%5Cu9178%5Cu68c0%5Cu6d4b_190857268466688000_R-ODY_17_640.pt%22%2C+%22description%22%3A+%22%5Cu6a21%5Cu578b%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fsaved_model%2Ftest.pt%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+3%2C+%22name%22%3A+%22device%22%2C+%22value%22%3A+%220%22%2C+%22description%22%3A+%22%5Cu63a8%5Cu7406%5Cu6838%22%2C+%22default%22%3A+%22cpu%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%5D&id=195095688265211904_17_detect HTTP/1.1" 200 161 0.002091
detect_server: id=195095688265211904_17_detect, weights=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights//核酸检测_190857268466688000_R-ODY_17_640.pt, source=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/camera, output=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/results, data=app/yolov5/data/coco128.yaml, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=0, view_img=False, save_txt=True, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=app/yolov5/runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1
YOLOv5 🚀 2022-11-7 Python-3.8.13 torch-1.8.0+cu111 CUDA:0 (Tesla T4, 15110MiB)
Fusing layers...
Model summary: 213 layers, 7020913 parameters, 0 gradients, 15.8 GFLOPs
image 1/1 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/camera/微信截图_20221129084118.png: 640x512 1 zui, 1 mianbang, 12.3ms
Speed: 0.4ms pre-process, 12.3ms inference, 0.8ms NMS per image at shape (1, 3, 640, 640)
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192.168.0.20 - - [2022-11-29 08:46:19] "GET /api/obtain_detect_param HTTP/1.1" 200 1110 0.000607
192.168.0.20 - - [2022-11-29 08:46:19] "GET /api/start_detect_algorithm?param=%5B%7B%22index%22%3A+0%2C+%22name%22%3A+%22inputPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2F195095688265211904%2Fcamera%22%2C+%22description%22%3A+%22%5Cu8f93%5Cu5165%5Cu56fe%5Cu50cf%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fdatasets%2FM006B_waibi%2FJPEGImages%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+1%2C+%22name%22%3A+%22outputPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2F195095688265211904%2Fresults%22%2C+%22description%22%3A+%22%5Cu8f93%5Cu51fa%5Cu7ed3%5Cu679c%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fdatasets%2FM006B_waibi%2Fres%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+2%2C+%22name%22%3A+%22modPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F%2F%5Cu6838%5Cu9178%5Cu68c0%5Cu6d4b_190857268466688000_R-ODY_17_640.pt%22%2C+%22description%22%3A+%22%5Cu6a21%5Cu578b%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fsaved_model%2Ftest.pt%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+3%2C+%22name%22%3A+%22device%22%2C+%22value%22%3A+%220%22%2C+%22description%22%3A+%22%5Cu63a8%5Cu7406%5Cu6838%22%2C+%22default%22%3A+%22cpu%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%5D&id=195095688265211904_17_detect HTTP/1.1" 200 161 0.002050
detect_server: id=195095688265211904_17_detect, weights=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights//核酸检测_190857268466688000_R-ODY_17_640.pt, source=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/camera, output=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/results, data=app/yolov5/data/coco128.yaml, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=0, view_img=False, save_txt=True, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=app/yolov5/runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1
YOLOv5 🚀 2022-11-7 Python-3.8.13 torch-1.8.0+cu111 CUDA:0 (Tesla T4, 15110MiB)
Fusing layers...
Model summary: 213 layers, 7020913 parameters, 0 gradients, 15.8 GFLOPs
image 1/1 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/camera/微信截图_20221129084118.png: 640x512 1 zui, 1 mianbang, 12.3ms
Speed: 0.4ms pre-process, 12.3ms inference, 0.8ms NMS per image at shape (1, 3, 640, 640)
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192.168.0.20 - - [2022-11-29 09:46:07] "GET /api/obtain_train_param HTTP/1.1" 200 1936 0.003772
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192.168.0.20 - - [2022-11-29 09:52:50] "GET /api/obtain_train_param HTTP/1.1" 200 1936 0.000666
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192.168.0.20 - - [2022-11-29 10:06:37] "GET /api/obtain_train_param HTTP/1.1" 200 1936 0.000656
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存储ws连接对象
requirements: /mnt/sdc/algorithm/R-ODY/app/yolov5/requirements.txt not found, check failed.
True
requirements: /mnt/sdc/algorithm/R-ODY/app/yolov5/requirements.txt not found, check failed.
True
存储ws连接对象
图片总数量： 1
处理成功数量： 1
处理失败数量： 0
图片总数量： 1
处理成功数量： 1
处理失败数量： 0
requirements: /mnt/sdc/algorithm/R-ODY/app/yolov5/requirements.txt not found, check failed.
True
图片总数量： 1
处理成功数量： 1
处理失败数量： 0
存储ws连接对象
requirements: /mnt/sdc/algorithm/R-ODY/app/yolov5/requirements.txt not found, check failed.
True
图片总数量： 1
处理成功数量： 1
处理失败数量： 0
存储ws连接对象
存储ws连接对象
存储ws连接对象
存储ws连接对象
存储ws连接对象
存储ws连接对象
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None
存储ws连接对象
192.168.0.20 - - [2022-11-29 10:06:49] "GET /api/start_train_algorithm?param=%5B%7B%22index%22%3A+0%2C+%22name%22%3A+%22epochnum%22%2C+%22value%22%3A+10%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu8f6e%5Cu6b21%22%2C+%22default%22%3A+100%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+1%2C+%22name%22%3A+%22batch_size%22%2C+%22value%22%3A+4%2C+%22description%22%3A+%22%5Cu6279%5Cu6b21%5Cu56fe%5Cu50cf%5Cu6570%5Cu91cf%22%2C+%22default%22%3A+1%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+2%2C+%22name%22%3A+%22img_size%22%2C+%22value%22%3A+640%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu56fe%5Cu50cf%5Cu5927%5Cu5c0f%22%2C+%22default%22%3A+640%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+3%2C+%22name%22%3A+%22device%22%2C+%22value%22%3A+%22cuda%3A0%22%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu6838%5Cu5fc3%22%2C+%22default%22%3A+%22cuda%3A0%22%2C+%22type%22%3A+%22E%22%2C+%22items%22%3A+%5B%22cuda%3A0%22%2C+%22cuda%3A1%22%5D%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+4%2C+%22name%22%3A+%22saveModDir%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F1128test_194741569180540928_R-ODY_19.pt%22%2C+%22description%22%3A+%22%5Cu4fdd%5Cu5b58%5Cu6a21%5Cu578b%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fsaved_model%2Ftest.pt%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+5%2C+%22name%22%3A+%22resumeModPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F%2Fyolov5s.pt%22%2C+%22description%22%3A+%22%5Cu7ee7%5Cu7eed%5Cu8bad%5Cu7ec3%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+6%2C+%22name%22%3A+%22resumeMod%22%2C+%22value%22%3A+%22%22%2C+%22description%22%3A+%22%5Cu7ee7%5Cu7eed%5Cu8bad%5Cu7ec3%5Cu6a21%5Cu578b%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22E%22%2C+%22items%22%3A+%22%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+7%2C+%22name%22%3A+%22CLASS_NAMES%22%2C+%22value%22%3A+%5B%22hole%22%2C+%22456%22%2C+%22aeroplane%22%2C+%22tvmonitor%22%2C+%22train%22%2C+%22boat%22%2C+%22dog%22%2C+%22chair%22%2C+%22bird%22%2C+%22bicycle%22%2C+%22person%22%2C+%22bottle%22%2C+%22sheep%22%2C+%22cat%22%5D%2C+%22description%22%3A+%22%5Cu7c7b%5Cu522b%5Cu540d%5Cu79f0%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22L%22%2C+%22items%22%3A+%22%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+8%2C+%22name%22%3A+%22DatasetDir%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2F194741569180540928%2Fori%22%2C+%22description%22%3A+%22%5Cu6570%5Cu636e%5Cu96c6%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fdatasets%2Ftest%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%5D&id=194741569180540928_19_train HTTP/1.1" 200 161 0.057693
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train_server: weights=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights//yolov5s.pt, savemodel=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/1128test_194741569180540928_R-ODY_19_640.pt, cfg=, data=/mnt/sdc/algorithm/R-ODY/app/yolov5/data/coco128.yaml, hyp=/mnt/sdc/algorithm/R-ODY/app/yolov5/data/hyps/hyp.scratch-low.yaml, epochs=10, batch_size=4, imgsz=640, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, noplots=False, evolve=None, bucket=, cache=None, image_weights=False, device=cuda:0, multi_scale=False, single_cls=False, optimizer=SGD, sync_bn=False, workers=8, project=/mnt/sdc/algorithm/R-ODY/app/yolov5/runs/train, name=exp, exist_ok=False, quad=False, cos_lr=False, label_smoothing=0.0, patience=100, freeze=[0], save_period=-1, seed=0, local_rank=-1, entity=None, upload_dataset=False, bbox_interval=-1, artifact_alias=latest
Weights & Biases: run 'pip install wandb' to automatically track and visualize YOLOv5 🚀 runs in Weights & Biases
ClearML: run 'pip install clearml' to automatically track, visualize and remotely train YOLOv5 🚀 in ClearML
TensorBoard: Start with 'tensorboard --logdir /mnt/sdc/algorithm/R-ODY/app/yolov5/runs/train', view at http://localhost:6006/
Overriding model.yaml nc=80 with nc=14
from n params module arguments
0 -1 1 3520 app.yolov5.models.common.Conv [3, 32, 6, 2, 2]
1 -1 1 18560 app.yolov5.models.common.Conv [32, 64, 3, 2]
2 -1 1 18816 app.yolov5.models.common.C3 [64, 64, 1]
3 -1 1 73984 app.yolov5.models.common.Conv [64, 128, 3, 2]
4 -1 2 115712 app.yolov5.models.common.C3 [128, 128, 2]
5 -1 1 295424 app.yolov5.models.common.Conv [128, 256, 3, 2]
6 -1 3 625152 app.yolov5.models.common.C3 [256, 256, 3]
7 -1 1 1180672 app.yolov5.models.common.Conv [256, 512, 3, 2]
8 -1 1 1182720 app.yolov5.models.common.C3 [512, 512, 1]
9 -1 1 656896 app.yolov5.models.common.SPPF [512, 512, 5]
10 -1 1 131584 app.yolov5.models.common.Conv [512, 256, 1, 1]
11 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
12 [-1, 6] 1 0 app.yolov5.models.common.Concat [1]
13 -1 1 361984 app.yolov5.models.common.C3 [512, 256, 1, False]
14 -1 1 33024 app.yolov5.models.common.Conv [256, 128, 1, 1]
15 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
16 [-1, 4] 1 0 app.yolov5.models.common.Concat [1]
17 -1 1 90880 app.yolov5.models.common.C3 [256, 128, 1, False]
18 -1 1 147712 app.yolov5.models.common.Conv [128, 128, 3, 2]
19 [-1, 14] 1 0 app.yolov5.models.common.Concat [1]
20 -1 1 296448 app.yolov5.models.common.C3 [256, 256, 1, False]
21 -1 1 590336 app.yolov5.models.common.Conv [256, 256, 3, 2]
22 [-1, 10] 1 0 app.yolov5.models.common.Concat [1]
23 -1 1 1182720 app.yolov5.models.common.C3 [512, 512, 1, False]
24 [17, 20, 23] 1 51243 app.yolov5.models.yolo.Detect [14, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]], [128, 256, 512]]
Model summary: 270 layers, 7057387 parameters, 7057387 gradients, 16.1 GFLOPs
**********************************
[<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06880>]
**********************************
**********************************
{'195095688265211904_17_detect': [<geventwebsocket.websocket.WebSocket object at 0x7fd0e269a340>, <geventwebsocket.websocket.WebSocket object at 0x7fcf55fe9820>, <geventwebsocket.websocket.WebSocket object at 0x7fcfb9ef6760>, <geventwebsocket.websocket.WebSocket object at 0x7fcf55fe9e20>], '194741569180540928_14_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06760>], '194741569180540928_15_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06a60>], '194741569180540928_16_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06520>], '194741569180540928_17_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf5499d100>], '194741569180540928_18_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf5499d460>], '194741569180540928_19_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06880>]}
**********************************
[{"index": 0, "name": "epochnum", "value": 10, "description": "\u8bad\u7ec3\u8f6e\u6b21", "default": 100, "type": "I", "show": true}, {"index": 1, "name": "batch_size", "value": 4, "description": "\u6279\u6b21\u56fe\u50cf\u6570\u91cf", "default": 1, "type": "I", "show": true}, {"index": 2, "name": "img_size", "value": 640, "description": "\u8bad\u7ec3\u56fe\u50cf\u5927\u5c0f", "default": 640, "type": "I", "show": true}, {"index": 3, "name": "device", "value": "cuda:0", "description": "\u8bad\u7ec3\u6838\u5fc3", "default": "cuda:0", "type": "E", "items": ["cuda:0", "cuda:1"], "show": false}, {"index": 4, "name": "saveModDir", "value": "/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/1128test_194741569180540928_R-ODY_19.pt", "description": "\u4fdd\u5b58\u6a21\u578b\u8def\u5f84", "default": "./app/maskrcnn/saved_model/test.pt", "type": "S", "show": false}, {"index": 5, "name": "resumeModPath", "value": "/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights//yolov5s.pt", "description": "\u7ee7\u7eed\u8bad\u7ec3\u8def\u5f84", "default": "", "type": "S", "show": false}, {"index": 6, "name": "resumeMod", "value": "", "description": "\u7ee7\u7eed\u8bad\u7ec3\u6a21\u578b", "default": "", "type": "E", "items": "", "show": true}, {"index": 7, "name": "CLASS_NAMES", "value": ["hole", "456", "aeroplane", "tvmonitor", "train", "boat", "dog", "chair", "bird", "bicycle", "person", "bottle", "sheep", "cat"], "description": "\u7c7b\u522b\u540d\u79f0", "default": "", "type": "L", "items": "", "show": false}, {"index": 8, "name": "DatasetDir", "value": "/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/194741569180540928/ori", "description": "\u6570\u636e\u96c6\u8def\u5f84", "default": "./app/maskrcnn/datasets/test", "type": "S", "show": false}]
**********************************
cuda:0
图像： ['2007_000032.jpg', '2007_000241.jpg', '2007_000068.jpg', '4.jpg', '3.jpg', '2007_000033.jpg', '10.jpg', '2007_000042.jpg', '7.jpg', '2007_000170.jpg', '2007_001583.jpg', '8.jpg', '2007_000187.jpg', '1.jpg', '2007_001457.jpg', '2007_000061.jpg', '2007_000027.jpg', '2007_000063.jpg', '2007_000129.jpg', '5.jpg', '2007_000123.jpg', '2007_000121.jpg', '9.jpg', '2007_000175.jpg', '2007_000039.jpg', '2007_001430.jpg', '6.jpg', '2007_001585.jpg', '2.jpg']
图像路径 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/194741569180540928/ori/images/2007_000032.jpg
1111
标签 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/194741569180540928/ori/labels/2007_000032.json
2222
ROOT############### /mnt/sdc/algorithm/R-ODY/app/yolov5
opt.device: cuda:0
device: cuda:0
get in train()
Process 194741569180540928_19_train:
Traceback (most recent call last):
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/flask_sockets.py", line 40, in __call__
handler, values = adapter.match()
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/werkzeug/routing.py", line 1945, in match
raise NotFound()
werkzeug.exceptions.NotFound: 404 Not Found: The requested URL was not found on the server. If you entered the URL manually please check your spelling and try again.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/multiprocessing/process.py", line 315, in _bootstrap
self.run()
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/multiprocessing/process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File "/mnt/sdc/algorithm/R-ODY/app/controller/AlgorithmController.py", line 327, in train_R0DY
train_start(weights, savemodel, epoches, img_size, batch_size, device, data_list, id, getsomething)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/train_server.py", line 733, in train_start
main(opt,data_list,id,getsomething)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/train_server.py", line 630, in main
train(opt.hyp, opt, device, data_list,id,getsomething,callbacks)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/train_server.py", line 168, in train
model = Model(cfg or ckpt['model'].yaml, ch=3, nc=nc, anchors=hyp.get('anchors')).to(device) # create
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 673, in to
return self._apply(convert)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/models/yolo.py", line 136, in _apply
self = super()._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 409, in _apply
param_applied = fn(param)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 671, in convert
return t.to(device, dtype if t.is_floating_point() or t.is_complex() else None, non_blocking)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/cuda/__init__.py", line 160, in _lazy_init
raise RuntimeError(
RuntimeError: Cannot re-initialize CUDA in forked subprocess. To use CUDA with multiprocessing, you must use the 'spawn' start method
192.168.0.20 - - [2022-11-29 10:21:16] "GET /api/obtain_train_param HTTP/1.1" 200 1936 0.000878
------进入websocket
存储ws连接对象
192.168.0.20 - - [2022-11-29 10:21:27] "GET /api/start_train_algorithm?param=%5B%7B%22index%22%3A+0%2C+%22name%22%3A+%22epochnum%22%2C+%22value%22%3A+10%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu8f6e%5Cu6b21%22%2C+%22default%22%3A+100%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+1%2C+%22name%22%3A+%22batch_size%22%2C+%22value%22%3A+4%2C+%22description%22%3A+%22%5Cu6279%5Cu6b21%5Cu56fe%5Cu50cf%5Cu6570%5Cu91cf%22%2C+%22default%22%3A+1%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+2%2C+%22name%22%3A+%22img_size%22%2C+%22value%22%3A+640%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu56fe%5Cu50cf%5Cu5927%5Cu5c0f%22%2C+%22default%22%3A+640%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+3%2C+%22name%22%3A+%22device%22%2C+%22value%22%3A+%22cuda%3A0%22%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu6838%5Cu5fc3%22%2C+%22default%22%3A+%22cuda%3A0%22%2C+%22type%22%3A+%22E%22%2C+%22items%22%3A+%5B%22cuda%3A0%22%2C+%22cuda%3A1%22%5D%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+4%2C+%22name%22%3A+%22saveModDir%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F1128test_194741569180540928_R-ODY_20.pt%22%2C+%22description%22%3A+%22%5Cu4fdd%5Cu5b58%5Cu6a21%5Cu578b%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fsaved_model%2Ftest.pt%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+5%2C+%22name%22%3A+%22resumeModPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F%2Fyolov5s.pt%22%2C+%22description%22%3A+%22%5Cu7ee7%5Cu7eed%5Cu8bad%5Cu7ec3%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+6%2C+%22name%22%3A+%22resumeMod%22%2C+%22value%22%3A+%22%22%2C+%22description%22%3A+%22%5Cu7ee7%5Cu7eed%5Cu8bad%5Cu7ec3%5Cu6a21%5Cu578b%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22E%22%2C+%22items%22%3A+%22%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+7%2C+%22name%22%3A+%22CLASS_NAMES%22%2C+%22value%22%3A+%5B%22hole%22%2C+%22456%22%2C+%22aeroplane%22%2C+%22tvmonitor%22%2C+%22train%22%2C+%22boat%22%2C+%22dog%22%2C+%22chair%22%2C+%22bird%22%2C+%22bicycle%22%2C+%22person%22%2C+%22bottle%22%2C+%22sheep%22%2C+%22cat%22%5D%2C+%22description%22%3A+%22%5Cu7c7b%5Cu522b%5Cu540d%5Cu79f0%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22L%22%2C+%22items%22%3A+%22%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+8%2C+%22name%22%3A+%22DatasetDir%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2F194741569180540928%2Fori%22%2C+%22description%22%3A+%22%5Cu6570%5Cu636e%5Cu96c6%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fdatasets%2Ftest%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%5D&id=194741569180540928_20_train HTTP/1.1" 200 161 0.050371
删除图片数据
删除json数据
train_server: weights=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights//yolov5s.pt, savemodel=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/1128test_194741569180540928_R-ODY_20_640.pt, cfg=, data=/mnt/sdc/algorithm/R-ODY/app/yolov5/data/coco128.yaml, hyp=/mnt/sdc/algorithm/R-ODY/app/yolov5/data/hyps/hyp.scratch-low.yaml, epochs=10, batch_size=4, imgsz=640, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, noplots=False, evolve=None, bucket=, cache=None, image_weights=False, device=cuda:0, multi_scale=False, single_cls=False, optimizer=SGD, sync_bn=False, workers=8, project=/mnt/sdc/algorithm/R-ODY/app/yolov5/runs/train, name=exp, exist_ok=False, quad=False, cos_lr=False, label_smoothing=0.0, patience=100, freeze=[0], save_period=-1, seed=0, local_rank=-1, entity=None, upload_dataset=False, bbox_interval=-1, artifact_alias=latest
Weights & Biases: run 'pip install wandb' to automatically track and visualize YOLOv5 🚀 runs in Weights & Biases
ClearML: run 'pip install clearml' to automatically track, visualize and remotely train YOLOv5 🚀 in ClearML
TensorBoard: Start with 'tensorboard --logdir /mnt/sdc/algorithm/R-ODY/app/yolov5/runs/train', view at http://localhost:6006/
Overriding model.yaml nc=80 with nc=14
from n params module arguments
0 -1 1 3520 app.yolov5.models.common.Conv [3, 32, 6, 2, 2]
1 -1 1 18560 app.yolov5.models.common.Conv [32, 64, 3, 2]
2 -1 1 18816 app.yolov5.models.common.C3 [64, 64, 1]
3 -1 1 73984 app.yolov5.models.common.Conv [64, 128, 3, 2]
4 -1 2 115712 app.yolov5.models.common.C3 [128, 128, 2]
5 -1 1 295424 app.yolov5.models.common.Conv [128, 256, 3, 2]
6 -1 3 625152 app.yolov5.models.common.C3 [256, 256, 3]
7 -1 1 1180672 app.yolov5.models.common.Conv [256, 512, 3, 2]
8 -1 1 1182720 app.yolov5.models.common.C3 [512, 512, 1]
9 -1 1 656896 app.yolov5.models.common.SPPF [512, 512, 5]
10 -1 1 131584 app.yolov5.models.common.Conv [512, 256, 1, 1]
11 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
12 [-1, 6] 1 0 app.yolov5.models.common.Concat [1]
13 -1 1 361984 app.yolov5.models.common.C3 [512, 256, 1, False]
14 -1 1 33024 app.yolov5.models.common.Conv [256, 128, 1, 1]
15 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
16 [-1, 4] 1 0 app.yolov5.models.common.Concat [1]
17 -1 1 90880 app.yolov5.models.common.C3 [256, 128, 1, False]
18 -1 1 147712 app.yolov5.models.common.Conv [128, 128, 3, 2]
19 [-1, 14] 1 0 app.yolov5.models.common.Concat [1]
20 -1 1 296448 app.yolov5.models.common.C3 [256, 256, 1, False]
21 -1 1 590336 app.yolov5.models.common.Conv [256, 256, 3, 2]
22 [-1, 10] 1 0 app.yolov5.models.common.Concat [1]
23 -1 1 1182720 app.yolov5.models.common.C3 [512, 512, 1, False]
24 [17, 20, 23] 1 51243 app.yolov5.models.yolo.Detect [14, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]], [128, 256, 512]]
Model summary: 270 layers, 7057387 parameters, 7057387 gradients, 16.1 GFLOPs
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[<geventwebsocket.websocket.WebSocket object at 0x7fcf5499d7c0>]
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**********************************
{'195095688265211904_17_detect': [<geventwebsocket.websocket.WebSocket object at 0x7fd0e269a340>, <geventwebsocket.websocket.WebSocket object at 0x7fcf55fe9820>, <geventwebsocket.websocket.WebSocket object at 0x7fcfb9ef6760>, <geventwebsocket.websocket.WebSocket object at 0x7fcf55fe9e20>], '194741569180540928_14_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06760>], '194741569180540928_15_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06a60>], '194741569180540928_16_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06520>], '194741569180540928_17_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf5499d100>], '194741569180540928_18_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf5499d460>], '194741569180540928_19_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06880>], '194741569180540928_20_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf5499d7c0>]}
**********************************
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**********************************
cuda:0
图像： ['2007_000032.jpg', '2007_000241.jpg', '2007_000068.jpg', '4.jpg', '3.jpg', '2007_000033.jpg', '10.jpg', '2007_000042.jpg', '7.jpg', '2007_000170.jpg', '2007_001583.jpg', '8.jpg', '2007_000187.jpg', '1.jpg', '2007_001457.jpg', '2007_000061.jpg', '2007_000027.jpg', '2007_000063.jpg', '2007_000129.jpg', '5.jpg', '2007_000123.jpg', '2007_000121.jpg', '9.jpg', '2007_000175.jpg', '2007_000039.jpg', '2007_001430.jpg', '6.jpg', '2007_001585.jpg', '2.jpg']
图像路径 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/194741569180540928/ori/images/2007_000032.jpg
1111
标签 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/194741569180540928/ori/labels/2007_000032.json
2222
ROOT############### /mnt/sdc/algorithm/R-ODY/app/yolov5
opt.device: cuda:0
device: cuda:0
get in train()
Process 194741569180540928_20_train:
Traceback (most recent call last):
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/flask_sockets.py", line 40, in __call__
handler, values = adapter.match()
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/werkzeug/routing.py", line 1945, in match
raise NotFound()
werkzeug.exceptions.NotFound: 404 Not Found: The requested URL was not found on the server. If you entered the URL manually please check your spelling and try again.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/multiprocessing/process.py", line 315, in _bootstrap
self.run()
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/multiprocessing/process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File "/mnt/sdc/algorithm/R-ODY/app/controller/AlgorithmController.py", line 327, in train_R0DY
train_start(weights, savemodel, epoches, img_size, batch_size, device, data_list, id, getsomething)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/train_server.py", line 733, in train_start
main(opt,data_list,id,getsomething)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/train_server.py", line 630, in main
train(opt.hyp, opt, device, data_list,id,getsomething,callbacks)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/train_server.py", line 168, in train
model = Model(cfg or ckpt['model'].yaml, ch=3, nc=nc, anchors=hyp.get('anchors')).to(device) # create
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 673, in to
return self._apply(convert)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/models/yolo.py", line 136, in _apply
self = super()._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 409, in _apply
param_applied = fn(param)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 671, in convert
return t.to(device, dtype if t.is_floating_point() or t.is_complex() else None, non_blocking)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/cuda/__init__.py", line 160, in _lazy_init
raise RuntimeError(
RuntimeError: Cannot re-initialize CUDA in forked subprocess. To use CUDA with multiprocessing, you must use the 'spawn' start method
192.168.0.20 - - [2022-11-29 10:21:55] "GET /api/obtain_train_param HTTP/1.1" 200 1936 0.000899
------进入websocket
存储ws连接对象
192.168.0.20 - - [2022-11-29 10:22:24] "GET /api/start_train_algorithm?param=%5B%7B%22index%22%3A+0%2C+%22name%22%3A+%22epochnum%22%2C+%22value%22%3A+10%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu8f6e%5Cu6b21%22%2C+%22default%22%3A+100%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+1%2C+%22name%22%3A+%22batch_size%22%2C+%22value%22%3A+4%2C+%22description%22%3A+%22%5Cu6279%5Cu6b21%5Cu56fe%5Cu50cf%5Cu6570%5Cu91cf%22%2C+%22default%22%3A+1%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+2%2C+%22name%22%3A+%22img_size%22%2C+%22value%22%3A+640%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu56fe%5Cu50cf%5Cu5927%5Cu5c0f%22%2C+%22default%22%3A+640%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+3%2C+%22name%22%3A+%22device%22%2C+%22value%22%3A+%22cuda%3A0%22%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu6838%5Cu5fc3%22%2C+%22default%22%3A+%22cuda%3A0%22%2C+%22type%22%3A+%22E%22%2C+%22items%22%3A+%5B%22cuda%3A0%22%2C+%22cuda%3A1%22%5D%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+4%2C+%22name%22%3A+%22saveModDir%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F%5Cu6838%5Cu9178%5Cu68c0%5Cu6d4b_190857268466688000_R-ODY_18.pt%22%2C+%22description%22%3A+%22%5Cu4fdd%5Cu5b58%5Cu6a21%5Cu578b%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fsaved_model%2Ftest.pt%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+5%2C+%22name%22%3A+%22resumeModPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F%2Fyolov5s.pt%22%2C+%22description%22%3A+%22%5Cu7ee7%5Cu7eed%5Cu8bad%5Cu7ec3%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+6%2C+%22name%22%3A+%22resumeMod%22%2C+%22value%22%3A+%22%2F1128test_194741569180540928_R-ODY_13_640.pt%22%2C+%22description%22%3A+%22%5Cu7ee7%5Cu7eed%5Cu8bad%5Cu7ec3%5Cu6a21%5Cu578b%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22E%22%2C+%22items%22%3A+%22%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+7%2C+%22name%22%3A+%22CLASS_NAMES%22%2C+%22value%22%3A+%5B%22hole%22%2C+%22456%22%2C+%22zui%22%2C+%22mianbang%22%5D%2C+%22description%22%3A+%22%5Cu7c7b%5Cu522b%5Cu540d%5Cu79f0%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22L%22%2C+%22items%22%3A+%22%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+8%2C+%22name%22%3A+%22DatasetDir%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2F190857268466688000%2Fori%22%2C+%22description%22%3A+%22%5Cu6570%5Cu636e%5Cu96c6%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fdatasets%2Ftest%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%5D&id=190857268466688000_18_train HTTP/1.1" 200 161 0.050019
删除图片数据
删除json数据
192.168.0.20 - - [2022-11-29 10:22:26] "GET /api/obtain_download_pt_param HTTP/1.1" 200 792 0.000835
train_server: weights=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights//yolov5s.pt, savemodel=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/核酸检测_190857268466688000_R-ODY_18_640.pt, cfg=, data=/mnt/sdc/algorithm/R-ODY/app/yolov5/data/coco128.yaml, hyp=/mnt/sdc/algorithm/R-ODY/app/yolov5/data/hyps/hyp.scratch-low.yaml, epochs=10, batch_size=4, imgsz=640, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, noplots=False, evolve=None, bucket=, cache=None, image_weights=False, device=cuda:0, multi_scale=False, single_cls=False, optimizer=SGD, sync_bn=False, workers=8, project=/mnt/sdc/algorithm/R-ODY/app/yolov5/runs/train, name=exp, exist_ok=False, quad=False, cos_lr=False, label_smoothing=0.0, patience=100, freeze=[0], save_period=-1, seed=0, local_rank=-1, entity=None, upload_dataset=False, bbox_interval=-1, artifact_alias=latest
Weights & Biases: run 'pip install wandb' to automatically track and visualize YOLOv5 🚀 runs in Weights & Biases
ClearML: run 'pip install clearml' to automatically track, visualize and remotely train YOLOv5 🚀 in ClearML
TensorBoard: Start with 'tensorboard --logdir /mnt/sdc/algorithm/R-ODY/app/yolov5/runs/train', view at http://localhost:6006/
Overriding model.yaml nc=80 with nc=4
from n params module arguments
0 -1 1 3520 app.yolov5.models.common.Conv [3, 32, 6, 2, 2]
1 -1 1 18560 app.yolov5.models.common.Conv [32, 64, 3, 2]
2 -1 1 18816 app.yolov5.models.common.C3 [64, 64, 1]
3 -1 1 73984 app.yolov5.models.common.Conv [64, 128, 3, 2]
4 -1 2 115712 app.yolov5.models.common.C3 [128, 128, 2]
5 -1 1 295424 app.yolov5.models.common.Conv [128, 256, 3, 2]
6 -1 3 625152 app.yolov5.models.common.C3 [256, 256, 3]
7 -1 1 1180672 app.yolov5.models.common.Conv [256, 512, 3, 2]
8 -1 1 1182720 app.yolov5.models.common.C3 [512, 512, 1]
9 -1 1 656896 app.yolov5.models.common.SPPF [512, 512, 5]
10 -1 1 131584 app.yolov5.models.common.Conv [512, 256, 1, 1]
11 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
12 [-1, 6] 1 0 app.yolov5.models.common.Concat [1]
13 -1 1 361984 app.yolov5.models.common.C3 [512, 256, 1, False]
14 -1 1 33024 app.yolov5.models.common.Conv [256, 128, 1, 1]
15 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
16 [-1, 4] 1 0 app.yolov5.models.common.Concat [1]
17 -1 1 90880 app.yolov5.models.common.C3 [256, 128, 1, False]
18 -1 1 147712 app.yolov5.models.common.Conv [128, 128, 3, 2]
19 [-1, 14] 1 0 app.yolov5.models.common.Concat [1]
20 -1 1 296448 app.yolov5.models.common.C3 [256, 256, 1, False]
21 -1 1 590336 app.yolov5.models.common.Conv [256, 256, 3, 2]
22 [-1, 10] 1 0 app.yolov5.models.common.Concat [1]
23 -1 1 1182720 app.yolov5.models.common.C3 [512, 512, 1, False]
24 [17, 20, 23] 1 24273 app.yolov5.models.yolo.Detect [4, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]], [128, 256, 512]]
Model summary: 270 layers, 7030417 parameters, 7030417 gradients, 16.0 GFLOPs
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[<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06e80>]
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{'195095688265211904_17_detect': [<geventwebsocket.websocket.WebSocket object at 0x7fd0e269a340>, <geventwebsocket.websocket.WebSocket object at 0x7fcf55fe9820>, <geventwebsocket.websocket.WebSocket object at 0x7fcfb9ef6760>, <geventwebsocket.websocket.WebSocket object at 0x7fcf55fe9e20>], '194741569180540928_14_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06760>], '194741569180540928_15_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06a60>], '194741569180540928_16_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06520>], '194741569180540928_17_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf5499d100>], '194741569180540928_18_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf5499d460>], '194741569180540928_19_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06880>], '194741569180540928_20_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf5499d7c0>], '190857268466688000_18_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06e80>]}
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**********************************
cuda:0
图像： ['IMG_20221117_132941~1.jpg', 'IMG_20221117_133002~1.jpg', 'IMG_20221117_152005~1.jpg', 'IMG_20221117_133005~1.jpg', 'IMG_20221117_132939~1.jpg', 'IMG_20221117_151945~1.jpg', 'IMG_20221117_133009~1.jpg', 'IMG_20221117_152023~1.jpg', 'IMG_20221117_133035~1.jpg', 'IMG_20221117_132947~1.jpg', 'IMG_20221117_151925~1.jpg', 'IMG_20221117_152026~1.jpg', 'IMG_20221117_133037~1.jpg', 'IMG_20221117_152018~1.jpg', 'IMG_20221117_152002~1.jpg', 'IMG_20221117_152004~1.jpg', 'IMG_20221117_152019~1.jpg', 'IMG_20221117_133006~1.jpg', 'IMG_20221117_152020~1.jpg', 'IMG_20221117_151959~1.jpg', 'IMG_20221117_152024~1.jpg', 'IMG_20221117_151921~1.jpg', 'IMG_20221117_151923~1.jpg', 'IMG_20221117_133038~1.jpg', 'IMG_20221117_151943~1.jpg', 'IMG_20221117_151924~1.jpg', 'IMG_20221117_152022~1.jpg', 'IMG_20221117_133032~1.jpg', 'IMG_20221117_151957~1.jpg', 'IMG_20221117_151939~1.jpg', 'IMG_20221117_133040~1.jpg', 'IMG_20221117_151946~1.jpg', 'IMG_20221117_151944~1.jpg', 'IMG_20221117_133007~1.jpg', 'IMG_20221117_132946~1.jpg', 'IMG_20221117_133004~1.jpg', 'IMG_20221117_152001~1.jpg', 'IMG_20221117_151941~1.jpg', 'IMG_20221117_151919~1.jpg', 'IMG_20221117_132944~1.jpg']
图像路径 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/190857268466688000/ori/images/IMG_20221117_132941~1.jpg
1111
标签 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/190857268466688000/ori/labels/IMG_20221117_132941~1.json
2222
ROOT############### /mnt/sdc/algorithm/R-ODY/app/yolov5
opt.device: cuda:0
device: cuda:0
get in train()
Process 190857268466688000_18_train:
Traceback (most recent call last):
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/flask_sockets.py", line 40, in __call__
handler, values = adapter.match()
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/werkzeug/routing.py", line 1945, in match
raise NotFound()
werkzeug.exceptions.NotFound: 404 Not Found: The requested URL was not found on the server. If you entered the URL manually please check your spelling and try again.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/multiprocessing/process.py", line 315, in _bootstrap
self.run()
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/multiprocessing/process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File "/mnt/sdc/algorithm/R-ODY/app/controller/AlgorithmController.py", line 327, in train_R0DY
train_start(weights, savemodel, epoches, img_size, batch_size, device, data_list, id, getsomething)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/train_server.py", line 733, in train_start
main(opt,data_list,id,getsomething)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/train_server.py", line 630, in main
train(opt.hyp, opt, device, data_list,id,getsomething,callbacks)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/train_server.py", line 168, in train
model = Model(cfg or ckpt['model'].yaml, ch=3, nc=nc, anchors=hyp.get('anchors')).to(device) # create
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 673, in to
return self._apply(convert)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/models/yolo.py", line 136, in _apply
self = super()._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 409, in _apply
param_applied = fn(param)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 671, in convert
return t.to(device, dtype if t.is_floating_point() or t.is_complex() else None, non_blocking)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/cuda/__init__.py", line 160, in _lazy_init
raise RuntimeError(
RuntimeError: Cannot re-initialize CUDA in forked subprocess. To use CUDA with multiprocessing, you must use the 'spawn' start method
export: data=app/yolov5/data/coco128.yaml, weights=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/核酸检测_190857268466688000_R-ODY_17_640.pt, imgsz=[640, 640], batch_size=1, device=0, half=False, inplace=False, train=False, keras=False, optimize=False, int8=False, dynamic=False, simplify=False, opset=11, verbose=False, workspace=4, nms=False, agnostic_nms=False, topk_per_class=100, topk_all=100, iou_thres=0.45, conf_thres=0.25, include=['torchscript', 'onnx']
YOLOv5 🚀 2022-11-7 Python-3.8.13 torch-1.8.0+cu111 CUDA:0 (Tesla T4, 15110MiB)
Fusing layers...
Model summary: 213 layers, 7020913 parameters, 0 gradients, 15.8 GFLOPs
PyTorch: starting from /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/核酸检测_190857268466688000_R-ODY_17_640.pt with output shape (1, 25200, 9) (13.8 MB)
TorchScript: starting export with torch 1.8.0+cu111...
TorchScript: export success ✅ 1.0s, saved as /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/核酸检测_190857268466688000_R-ODY_17_640.torchscript (27.3 MB)
ONNX: starting export with onnx 1.12.0...
ONNX: export success ✅ 1.6s, saved as /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/核酸检测_190857268466688000_R-ODY_17_640.onnx (27.2 MB)
Export complete (2.8s)
Results saved to /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights
Detect: python detect.py --weights /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/核酸检测_190857268466688000_R-ODY_17_640.onnx
Validate: python val.py --weights /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/核酸检测_190857268466688000_R-ODY_17_640.onnx
PyTorch Hub: model = torch.hub.load('ultralytics/yolov5', 'custom', '/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/核酸检测_190857268466688000_R-ODY_17_640.onnx')
Visualize: https://netron.app
192.168.0.20 - - [2022-11-29 10:22:31] "GET /api/start_download_pt?param=%5B%7B%22index%22%3A+0%2C+%22name%22%3A+%22exp_inputPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F%5Cu6838%5Cu9178%5Cu68c0%5Cu6d4b_190857268466688000_R-ODY_17_640.pt%22%2C+%22description%22%3A+%22%5Cu8f6c%5Cu5316%5Cu6a21%5Cu578b%5Cu8f93%5Cu5165%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22E%3A%2Falg_demo-master%2Falg_demo%2Fapp%2Fyolov5%2F%5Cu5706%5Cu5b54_123_RODY_1_640.pt%2F%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+1%2C+%22name%22%3A+%22device%22%2C+%22value%22%3A+%22gpu%22%2C+%22description%22%3A+%22CPU%5Cu6216GPU%22%2C+%22default%22%3A+%22gpu%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+2%2C+%22name%22%3A+%22imgsz%22%2C+%22value%22%3A+640%2C+%22description%22%3A+%22%5Cu56fe%5Cu50cf%5Cu5927%5Cu5c0f%22%2C+%22default%22%3A+640%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%5D&id=737 HTTP/1.1" 200 270 3.030957
------进入websocket
输入模型： /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/核酸检测_190857268466688000_R-ODY_17_640.pt
['torchscript', 'onnx']
['torchscript', 'onnx']
('torchscript', 'onnx', 'openvino', 'engine', 'coreml', 'saved_model', 'pb', 'tflite', 'edgetpu', 'tfjs')
True
模型路径： /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/核酸检测_190857268466688000_R-ODY_17_640.zip
存储ws连接对象
192.168.0.20 - - [2022-11-29 10:44:19] "GET /api/start_train_algorithm?param=%5B%7B%22index%22%3A+0%2C+%22name%22%3A+%22epochnum%22%2C+%22value%22%3A+10%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu8f6e%5Cu6b21%22%2C+%22default%22%3A+100%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+1%2C+%22name%22%3A+%22batch_size%22%2C+%22value%22%3A+4%2C+%22description%22%3A+%22%5Cu6279%5Cu6b21%5Cu56fe%5Cu50cf%5Cu6570%5Cu91cf%22%2C+%22default%22%3A+1%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+2%2C+%22name%22%3A+%22img_size%22%2C+%22value%22%3A+640%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu56fe%5Cu50cf%5Cu5927%5Cu5c0f%22%2C+%22default%22%3A+640%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+3%2C+%22name%22%3A+%22device%22%2C+%22value%22%3A+%22cuda%3A0%22%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu6838%5Cu5fc3%22%2C+%22default%22%3A+%22cuda%3A0%22%2C+%22type%22%3A+%22E%22%2C+%22items%22%3A+%5B%22cuda%3A0%22%2C+%22cuda%3A1%22%5D%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+4%2C+%22name%22%3A+%22saveModDir%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F1128test_194741569180540928_R-ODY_21.pt%22%2C+%22description%22%3A+%22%5Cu4fdd%5Cu5b58%5Cu6a21%5Cu578b%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fsaved_model%2Ftest.pt%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+5%2C+%22name%22%3A+%22resumeModPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F%2Fyolov5s.pt%22%2C+%22description%22%3A+%22%5Cu7ee7%5Cu7eed%5Cu8bad%5Cu7ec3%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+6%2C+%22name%22%3A+%22resumeMod%22%2C+%22value%22%3A+%22%22%2C+%22description%22%3A+%22%5Cu7ee7%5Cu7eed%5Cu8bad%5Cu7ec3%5Cu6a21%5Cu578b%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22E%22%2C+%22items%22%3A+%22%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+7%2C+%22name%22%3A+%22CLASS_NAMES%22%2C+%22value%22%3A+%5B%22hole%22%2C+%22456%22%2C+%22aeroplane%22%2C+%22tvmonitor%22%2C+%22train%22%2C+%22boat%22%2C+%22dog%22%2C+%22chair%22%2C+%22bird%22%2C+%22bicycle%22%2C+%22person%22%2C+%22bottle%22%2C+%22sheep%22%2C+%22cat%22%5D%2C+%22description%22%3A+%22%5Cu7c7b%5Cu522b%5Cu540d%5Cu79f0%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22L%22%2C+%22items%22%3A+%22%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+8%2C+%22name%22%3A+%22DatasetDir%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2F194741569180540928%2Fori%22%2C+%22description%22%3A+%22%5Cu6570%5Cu636e%5Cu96c6%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fdatasets%2Ftest%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%5D&id=194741569180540928_21_train HTTP/1.1" 200 161 0.051209
删除图片数据
删除json数据
train_server: weights=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights//yolov5s.pt, savemodel=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/1128test_194741569180540928_R-ODY_21_640.pt, cfg=, data=/mnt/sdc/algorithm/R-ODY/app/yolov5/data/coco128.yaml, hyp=/mnt/sdc/algorithm/R-ODY/app/yolov5/data/hyps/hyp.scratch-low.yaml, epochs=10, batch_size=4, imgsz=640, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, noplots=False, evolve=None, bucket=, cache=None, image_weights=False, device=cuda:0, multi_scale=False, single_cls=False, optimizer=SGD, sync_bn=False, workers=8, project=/mnt/sdc/algorithm/R-ODY/app/yolov5/runs/train, name=exp, exist_ok=False, quad=False, cos_lr=False, label_smoothing=0.0, patience=100, freeze=[0], save_period=-1, seed=0, local_rank=-1, entity=None, upload_dataset=False, bbox_interval=-1, artifact_alias=latest
Weights & Biases: run 'pip install wandb' to automatically track and visualize YOLOv5 🚀 runs in Weights & Biases
ClearML: run 'pip install clearml' to automatically track, visualize and remotely train YOLOv5 🚀 in ClearML
TensorBoard: Start with 'tensorboard --logdir /mnt/sdc/algorithm/R-ODY/app/yolov5/runs/train', view at http://localhost:6006/
Overriding model.yaml nc=80 with nc=14
from n params module arguments
0 -1 1 3520 app.yolov5.models.common.Conv [3, 32, 6, 2, 2]
1 -1 1 18560 app.yolov5.models.common.Conv [32, 64, 3, 2]
2 -1 1 18816 app.yolov5.models.common.C3 [64, 64, 1]
3 -1 1 73984 app.yolov5.models.common.Conv [64, 128, 3, 2]
4 -1 2 115712 app.yolov5.models.common.C3 [128, 128, 2]
5 -1 1 295424 app.yolov5.models.common.Conv [128, 256, 3, 2]
6 -1 3 625152 app.yolov5.models.common.C3 [256, 256, 3]
7 -1 1 1180672 app.yolov5.models.common.Conv [256, 512, 3, 2]
8 -1 1 1182720 app.yolov5.models.common.C3 [512, 512, 1]
9 -1 1 656896 app.yolov5.models.common.SPPF [512, 512, 5]
10 -1 1 131584 app.yolov5.models.common.Conv [512, 256, 1, 1]
11 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
12 [-1, 6] 1 0 app.yolov5.models.common.Concat [1]
13 -1 1 361984 app.yolov5.models.common.C3 [512, 256, 1, False]
14 -1 1 33024 app.yolov5.models.common.Conv [256, 128, 1, 1]
15 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
16 [-1, 4] 1 0 app.yolov5.models.common.Concat [1]
17 -1 1 90880 app.yolov5.models.common.C3 [256, 128, 1, False]
18 -1 1 147712 app.yolov5.models.common.Conv [128, 128, 3, 2]
19 [-1, 14] 1 0 app.yolov5.models.common.Concat [1]
20 -1 1 296448 app.yolov5.models.common.C3 [256, 256, 1, False]
21 -1 1 590336 app.yolov5.models.common.Conv [256, 256, 3, 2]
22 [-1, 10] 1 0 app.yolov5.models.common.Concat [1]
23 -1 1 1182720 app.yolov5.models.common.C3 [512, 512, 1, False]
24 [17, 20, 23] 1 51243 app.yolov5.models.yolo.Detect [14, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]], [128, 256, 512]]
2022-11-29 08:44:22,208 INFO sqlalchemy.engine.Engine select pg_catalog.version()
2022-11-29 08:44:22,209 INFO sqlalchemy.engine.Engine [raw sql] {}
2022-11-29 08:44:22,214 INFO sqlalchemy.engine.Engine select current_schema()
2022-11-29 08:44:22,214 INFO sqlalchemy.engine.Engine [raw sql] {}
2022-11-29 08:44:22,219 INFO sqlalchemy.engine.Engine show standard_conforming_strings
2022-11-29 08:44:22,219 INFO sqlalchemy.engine.Engine [raw sql] {}
2022-11-29 08:44:22,225 INFO sqlalchemy.engine.Engine BEGIN (implicit)
2022-11-29 08:44:22,225 INFO sqlalchemy.engine.Engine COMMIT
detect_server: id=195095688265211904_17_detect, weights=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights//核酸检测_190857268466688000_R-ODY_17_640.pt, source=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/camera, output=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/results, data=app/yolov5/data/coco128.yaml, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=0, view_img=False, save_txt=True, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=app/yolov5/runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1
YOLOv5 🚀 2022-11-7 Python-3.8.13 torch-1.8.0+cu111 CUDA:0 (Tesla T4, 15110MiB)
2022-11-29 08:44:36.902619: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 AVX512F AVX512_VNNI FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-11-29 08:44:37.033367: I tensorflow/core/util/util.cc:169] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2022-11-29 08:44:37.070603: E tensorflow/stream_executor/cuda/cuda_blas.cc:2981] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2022-11-29 08:44:37.607302: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/cv2/../../lib64::/usr/local/cuda/lib64
2022-11-29 08:44:37.607416: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/cv2/../../lib64::/usr/local/cuda/lib64
2022-11-29 08:44:37.607434: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
Fusing layers...
192.168.0.20 - - [2022-11-29 08:44:42] "GET /api/obtain_detect_param HTTP/1.1" 200 1110 0.000672
192.168.0.20 - - [2022-11-29 08:44:42] "GET /api/start_detect_algorithm?param=%5B%7B%22index%22%3A+0%2C+%22name%22%3A+%22inputPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2F195095688265211904%2Fcamera%22%2C+%22description%22%3A+%22%5Cu8f93%5Cu5165%5Cu56fe%5Cu50cf%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fdatasets%2FM006B_waibi%2FJPEGImages%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+1%2C+%22name%22%3A+%22outputPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2F195095688265211904%2Fresults%22%2C+%22description%22%3A+%22%5Cu8f93%5Cu51fa%5Cu7ed3%5Cu679c%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fdatasets%2FM006B_waibi%2Fres%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+2%2C+%22name%22%3A+%22modPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F%2F%5Cu6838%5Cu9178%5Cu68c0%5Cu6d4b_190857268466688000_R-ODY_17_640.pt%22%2C+%22description%22%3A+%22%5Cu6a21%5Cu578b%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fsaved_model%2Ftest.pt%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+3%2C+%22name%22%3A+%22device%22%2C+%22value%22%3A+%220%22%2C+%22description%22%3A+%22%5Cu63a8%5Cu7406%5Cu6838%22%2C+%22default%22%3A+%22cpu%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%5D&id=195095688265211904_17_detect HTTP/1.1" 200 161 0.002945
detect_server: id=195095688265211904_17_detect, weights=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights//核酸检测_190857268466688000_R-ODY_17_640.pt, source=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/camera, output=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/results, data=app/yolov5/data/coco128.yaml, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=0, view_img=False, save_txt=True, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=app/yolov5/runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1
YOLOv5 🚀 2022-11-7 Python-3.8.13 torch-1.8.0+cu111 CUDA:0 (Tesla T4, 15110MiB)
Fusing layers...
Model summary: 213 layers, 7020913 parameters, 0 gradients, 15.8 GFLOPs
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Model summary: 213 layers, 7020913 parameters, 0 gradients, 15.8 GFLOPs
image 1/1 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/camera/微信截图_20221129084118.png: 640x512 1 zui, 1 mianbang, 23.9ms
Speed: 0.4ms pre-process, 23.9ms inference, 1.5ms NMS per image at shape (1, 3, 640, 640)
image 1/1 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/camera/微信截图_20221129084118.png: 640x512 1 zui, 1 mianbang, 21.2ms
Speed: 0.4ms pre-process, 21.2ms inference, 1.1ms NMS per image at shape (1, 3, 640, 640)
192.168.0.20 - - [2022-11-29 08:46:07] "GET /api/obtain_detect_param HTTP/1.1" 200 1110 0.000634
192.168.0.20 - - [2022-11-29 08:46:07] "GET /api/start_detect_algorithm?param=%5B%7B%22index%22%3A+0%2C+%22name%22%3A+%22inputPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2F195095688265211904%2Fcamera%22%2C+%22description%22%3A+%22%5Cu8f93%5Cu5165%5Cu56fe%5Cu50cf%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fdatasets%2FM006B_waibi%2FJPEGImages%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+1%2C+%22name%22%3A+%22outputPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2F195095688265211904%2Fresults%22%2C+%22description%22%3A+%22%5Cu8f93%5Cu51fa%5Cu7ed3%5Cu679c%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fdatasets%2FM006B_waibi%2Fres%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+2%2C+%22name%22%3A+%22modPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F%2F%5Cu6838%5Cu9178%5Cu68c0%5Cu6d4b_190857268466688000_R-ODY_17_640.pt%22%2C+%22description%22%3A+%22%5Cu6a21%5Cu578b%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fsaved_model%2Ftest.pt%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+3%2C+%22name%22%3A+%22device%22%2C+%22value%22%3A+%220%22%2C+%22description%22%3A+%22%5Cu63a8%5Cu7406%5Cu6838%22%2C+%22default%22%3A+%22cpu%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%5D&id=195095688265211904_17_detect HTTP/1.1" 200 161 0.002091
detect_server: id=195095688265211904_17_detect, weights=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights//核酸检测_190857268466688000_R-ODY_17_640.pt, source=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/camera, output=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/results, data=app/yolov5/data/coco128.yaml, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=0, view_img=False, save_txt=True, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=app/yolov5/runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1
YOLOv5 🚀 2022-11-7 Python-3.8.13 torch-1.8.0+cu111 CUDA:0 (Tesla T4, 15110MiB)
Fusing layers...
Model summary: 213 layers, 7020913 parameters, 0 gradients, 15.8 GFLOPs
image 1/1 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/camera/微信截图_20221129084118.png: 640x512 1 zui, 1 mianbang, 12.3ms
Speed: 0.4ms pre-process, 12.3ms inference, 0.8ms NMS per image at shape (1, 3, 640, 640)
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192.168.0.20 - - [2022-11-29 08:46:19] "GET /api/obtain_detect_param HTTP/1.1" 200 1110 0.000607
192.168.0.20 - - [2022-11-29 08:46:19] "GET /api/start_detect_algorithm?param=%5B%7B%22index%22%3A+0%2C+%22name%22%3A+%22inputPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2F195095688265211904%2Fcamera%22%2C+%22description%22%3A+%22%5Cu8f93%5Cu5165%5Cu56fe%5Cu50cf%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fdatasets%2FM006B_waibi%2FJPEGImages%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+1%2C+%22name%22%3A+%22outputPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2F195095688265211904%2Fresults%22%2C+%22description%22%3A+%22%5Cu8f93%5Cu51fa%5Cu7ed3%5Cu679c%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fdatasets%2FM006B_waibi%2Fres%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+2%2C+%22name%22%3A+%22modPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F%2F%5Cu6838%5Cu9178%5Cu68c0%5Cu6d4b_190857268466688000_R-ODY_17_640.pt%22%2C+%22description%22%3A+%22%5Cu6a21%5Cu578b%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fsaved_model%2Ftest.pt%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+3%2C+%22name%22%3A+%22device%22%2C+%22value%22%3A+%220%22%2C+%22description%22%3A+%22%5Cu63a8%5Cu7406%5Cu6838%22%2C+%22default%22%3A+%22cpu%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%5D&id=195095688265211904_17_detect HTTP/1.1" 200 161 0.002050
detect_server: id=195095688265211904_17_detect, weights=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights//核酸检测_190857268466688000_R-ODY_17_640.pt, source=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/camera, output=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/results, data=app/yolov5/data/coco128.yaml, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=0, view_img=False, save_txt=True, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=app/yolov5/runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1
YOLOv5 🚀 2022-11-7 Python-3.8.13 torch-1.8.0+cu111 CUDA:0 (Tesla T4, 15110MiB)
Fusing layers...
Model summary: 213 layers, 7020913 parameters, 0 gradients, 15.8 GFLOPs
image 1/1 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/camera/微信截图_20221129084118.png: 640x512 1 zui, 1 mianbang, 12.3ms
Speed: 0.4ms pre-process, 12.3ms inference, 0.8ms NMS per image at shape (1, 3, 640, 640)
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192.168.0.20 - - [2022-11-29 09:46:07] "GET /api/obtain_train_param HTTP/1.1" 200 1936 0.003772
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192.168.0.20 - - [2022-11-29 09:52:50] "GET /api/obtain_train_param HTTP/1.1" 200 1936 0.000666
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192.168.0.20 - - [2022-11-29 10:06:37] "GET /api/obtain_train_param HTTP/1.1" 200 1936 0.000656
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存储ws连接对象
requirements: /mnt/sdc/algorithm/R-ODY/app/yolov5/requirements.txt not found, check failed.
True
requirements: /mnt/sdc/algorithm/R-ODY/app/yolov5/requirements.txt not found, check failed.
True
存储ws连接对象
图片总数量： 1
处理成功数量： 1
处理失败数量： 0
图片总数量： 1
处理成功数量： 1
处理失败数量： 0
requirements: /mnt/sdc/algorithm/R-ODY/app/yolov5/requirements.txt not found, check failed.
True
图片总数量： 1
处理成功数量： 1
处理失败数量： 0
存储ws连接对象
requirements: /mnt/sdc/algorithm/R-ODY/app/yolov5/requirements.txt not found, check failed.
True
图片总数量： 1
处理成功数量： 1
处理失败数量： 0
存储ws连接对象
存储ws连接对象
存储ws连接对象
存储ws连接对象
存储ws连接对象
存储ws连接对象
None
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存储ws连接对象
192.168.0.20 - - [2022-11-29 10:06:49] "GET /api/start_train_algorithm?param=%5B%7B%22index%22%3A+0%2C+%22name%22%3A+%22epochnum%22%2C+%22value%22%3A+10%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu8f6e%5Cu6b21%22%2C+%22default%22%3A+100%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+1%2C+%22name%22%3A+%22batch_size%22%2C+%22value%22%3A+4%2C+%22description%22%3A+%22%5Cu6279%5Cu6b21%5Cu56fe%5Cu50cf%5Cu6570%5Cu91cf%22%2C+%22default%22%3A+1%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+2%2C+%22name%22%3A+%22img_size%22%2C+%22value%22%3A+640%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu56fe%5Cu50cf%5Cu5927%5Cu5c0f%22%2C+%22default%22%3A+640%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+3%2C+%22name%22%3A+%22device%22%2C+%22value%22%3A+%22cuda%3A0%22%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu6838%5Cu5fc3%22%2C+%22default%22%3A+%22cuda%3A0%22%2C+%22type%22%3A+%22E%22%2C+%22items%22%3A+%5B%22cuda%3A0%22%2C+%22cuda%3A1%22%5D%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+4%2C+%22name%22%3A+%22saveModDir%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F1128test_194741569180540928_R-ODY_19.pt%22%2C+%22description%22%3A+%22%5Cu4fdd%5Cu5b58%5Cu6a21%5Cu578b%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fsaved_model%2Ftest.pt%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+5%2C+%22name%22%3A+%22resumeModPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F%2Fyolov5s.pt%22%2C+%22description%22%3A+%22%5Cu7ee7%5Cu7eed%5Cu8bad%5Cu7ec3%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+6%2C+%22name%22%3A+%22resumeMod%22%2C+%22value%22%3A+%22%22%2C+%22description%22%3A+%22%5Cu7ee7%5Cu7eed%5Cu8bad%5Cu7ec3%5Cu6a21%5Cu578b%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22E%22%2C+%22items%22%3A+%22%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+7%2C+%22name%22%3A+%22CLASS_NAMES%22%2C+%22value%22%3A+%5B%22hole%22%2C+%22456%22%2C+%22aeroplane%22%2C+%22tvmonitor%22%2C+%22train%22%2C+%22boat%22%2C+%22dog%22%2C+%22chair%22%2C+%22bird%22%2C+%22bicycle%22%2C+%22person%22%2C+%22bottle%22%2C+%22sheep%22%2C+%22cat%22%5D%2C+%22description%22%3A+%22%5Cu7c7b%5Cu522b%5Cu540d%5Cu79f0%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22L%22%2C+%22items%22%3A+%22%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+8%2C+%22name%22%3A+%22DatasetDir%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2F194741569180540928%2Fori%22%2C+%22description%22%3A+%22%5Cu6570%5Cu636e%5Cu96c6%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fdatasets%2Ftest%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%5D&id=194741569180540928_19_train HTTP/1.1" 200 161 0.057693
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删除json数据
train_server: weights=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights//yolov5s.pt, savemodel=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/1128test_194741569180540928_R-ODY_19_640.pt, cfg=, data=/mnt/sdc/algorithm/R-ODY/app/yolov5/data/coco128.yaml, hyp=/mnt/sdc/algorithm/R-ODY/app/yolov5/data/hyps/hyp.scratch-low.yaml, epochs=10, batch_size=4, imgsz=640, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, noplots=False, evolve=None, bucket=, cache=None, image_weights=False, device=cuda:0, multi_scale=False, single_cls=False, optimizer=SGD, sync_bn=False, workers=8, project=/mnt/sdc/algorithm/R-ODY/app/yolov5/runs/train, name=exp, exist_ok=False, quad=False, cos_lr=False, label_smoothing=0.0, patience=100, freeze=[0], save_period=-1, seed=0, local_rank=-1, entity=None, upload_dataset=False, bbox_interval=-1, artifact_alias=latest
Weights & Biases: run 'pip install wandb' to automatically track and visualize YOLOv5 🚀 runs in Weights & Biases
ClearML: run 'pip install clearml' to automatically track, visualize and remotely train YOLOv5 🚀 in ClearML
TensorBoard: Start with 'tensorboard --logdir /mnt/sdc/algorithm/R-ODY/app/yolov5/runs/train', view at http://localhost:6006/
Overriding model.yaml nc=80 with nc=14
from n params module arguments
0 -1 1 3520 app.yolov5.models.common.Conv [3, 32, 6, 2, 2]
1 -1 1 18560 app.yolov5.models.common.Conv [32, 64, 3, 2]
2 -1 1 18816 app.yolov5.models.common.C3 [64, 64, 1]
3 -1 1 73984 app.yolov5.models.common.Conv [64, 128, 3, 2]
4 -1 2 115712 app.yolov5.models.common.C3 [128, 128, 2]
5 -1 1 295424 app.yolov5.models.common.Conv [128, 256, 3, 2]
6 -1 3 625152 app.yolov5.models.common.C3 [256, 256, 3]
7 -1 1 1180672 app.yolov5.models.common.Conv [256, 512, 3, 2]
8 -1 1 1182720 app.yolov5.models.common.C3 [512, 512, 1]
9 -1 1 656896 app.yolov5.models.common.SPPF [512, 512, 5]
10 -1 1 131584 app.yolov5.models.common.Conv [512, 256, 1, 1]
11 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
12 [-1, 6] 1 0 app.yolov5.models.common.Concat [1]
13 -1 1 361984 app.yolov5.models.common.C3 [512, 256, 1, False]
14 -1 1 33024 app.yolov5.models.common.Conv [256, 128, 1, 1]
15 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
16 [-1, 4] 1 0 app.yolov5.models.common.Concat [1]
17 -1 1 90880 app.yolov5.models.common.C3 [256, 128, 1, False]
18 -1 1 147712 app.yolov5.models.common.Conv [128, 128, 3, 2]
19 [-1, 14] 1 0 app.yolov5.models.common.Concat [1]
20 -1 1 296448 app.yolov5.models.common.C3 [256, 256, 1, False]
21 -1 1 590336 app.yolov5.models.common.Conv [256, 256, 3, 2]
22 [-1, 10] 1 0 app.yolov5.models.common.Concat [1]
23 -1 1 1182720 app.yolov5.models.common.C3 [512, 512, 1, False]
24 [17, 20, 23] 1 51243 app.yolov5.models.yolo.Detect [14, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]], [128, 256, 512]]
Model summary: 270 layers, 7057387 parameters, 7057387 gradients, 16.1 GFLOPs
**********************************
[<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06880>]
**********************************
**********************************
{'195095688265211904_17_detect': [<geventwebsocket.websocket.WebSocket object at 0x7fd0e269a340>, <geventwebsocket.websocket.WebSocket object at 0x7fcf55fe9820>, <geventwebsocket.websocket.WebSocket object at 0x7fcfb9ef6760>, <geventwebsocket.websocket.WebSocket object at 0x7fcf55fe9e20>], '194741569180540928_14_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06760>], '194741569180540928_15_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06a60>], '194741569180540928_16_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06520>], '194741569180540928_17_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf5499d100>], '194741569180540928_18_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf5499d460>], '194741569180540928_19_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06880>]}
**********************************
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**********************************
cuda:0
图像： ['2007_000032.jpg', '2007_000241.jpg', '2007_000068.jpg', '4.jpg', '3.jpg', '2007_000033.jpg', '10.jpg', '2007_000042.jpg', '7.jpg', '2007_000170.jpg', '2007_001583.jpg', '8.jpg', '2007_000187.jpg', '1.jpg', '2007_001457.jpg', '2007_000061.jpg', '2007_000027.jpg', '2007_000063.jpg', '2007_000129.jpg', '5.jpg', '2007_000123.jpg', '2007_000121.jpg', '9.jpg', '2007_000175.jpg', '2007_000039.jpg', '2007_001430.jpg', '6.jpg', '2007_001585.jpg', '2.jpg']
图像路径 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/194741569180540928/ori/images/2007_000032.jpg
1111
标签 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/194741569180540928/ori/labels/2007_000032.json
2222
ROOT############### /mnt/sdc/algorithm/R-ODY/app/yolov5
opt.device: cuda:0
device: cuda:0
get in train()
Process 194741569180540928_19_train:
Traceback (most recent call last):
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/flask_sockets.py", line 40, in __call__
handler, values = adapter.match()
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/werkzeug/routing.py", line 1945, in match
raise NotFound()
werkzeug.exceptions.NotFound: 404 Not Found: The requested URL was not found on the server. If you entered the URL manually please check your spelling and try again.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/multiprocessing/process.py", line 315, in _bootstrap
self.run()
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/multiprocessing/process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File "/mnt/sdc/algorithm/R-ODY/app/controller/AlgorithmController.py", line 327, in train_R0DY
train_start(weights, savemodel, epoches, img_size, batch_size, device, data_list, id, getsomething)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/train_server.py", line 733, in train_start
main(opt,data_list,id,getsomething)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/train_server.py", line 630, in main
train(opt.hyp, opt, device, data_list,id,getsomething,callbacks)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/train_server.py", line 168, in train
model = Model(cfg or ckpt['model'].yaml, ch=3, nc=nc, anchors=hyp.get('anchors')).to(device) # create
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 673, in to
return self._apply(convert)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/models/yolo.py", line 136, in _apply
self = super()._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 409, in _apply
param_applied = fn(param)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 671, in convert
return t.to(device, dtype if t.is_floating_point() or t.is_complex() else None, non_blocking)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/cuda/__init__.py", line 160, in _lazy_init
raise RuntimeError(
RuntimeError: Cannot re-initialize CUDA in forked subprocess. To use CUDA with multiprocessing, you must use the 'spawn' start method
192.168.0.20 - - [2022-11-29 10:21:16] "GET /api/obtain_train_param HTTP/1.1" 200 1936 0.000878
------进入websocket
存储ws连接对象
192.168.0.20 - - [2022-11-29 10:21:27] "GET /api/start_train_algorithm?param=%5B%7B%22index%22%3A+0%2C+%22name%22%3A+%22epochnum%22%2C+%22value%22%3A+10%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu8f6e%5Cu6b21%22%2C+%22default%22%3A+100%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+1%2C+%22name%22%3A+%22batch_size%22%2C+%22value%22%3A+4%2C+%22description%22%3A+%22%5Cu6279%5Cu6b21%5Cu56fe%5Cu50cf%5Cu6570%5Cu91cf%22%2C+%22default%22%3A+1%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+2%2C+%22name%22%3A+%22img_size%22%2C+%22value%22%3A+640%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu56fe%5Cu50cf%5Cu5927%5Cu5c0f%22%2C+%22default%22%3A+640%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+3%2C+%22name%22%3A+%22device%22%2C+%22value%22%3A+%22cuda%3A0%22%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu6838%5Cu5fc3%22%2C+%22default%22%3A+%22cuda%3A0%22%2C+%22type%22%3A+%22E%22%2C+%22items%22%3A+%5B%22cuda%3A0%22%2C+%22cuda%3A1%22%5D%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+4%2C+%22name%22%3A+%22saveModDir%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F1128test_194741569180540928_R-ODY_20.pt%22%2C+%22description%22%3A+%22%5Cu4fdd%5Cu5b58%5Cu6a21%5Cu578b%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fsaved_model%2Ftest.pt%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+5%2C+%22name%22%3A+%22resumeModPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F%2Fyolov5s.pt%22%2C+%22description%22%3A+%22%5Cu7ee7%5Cu7eed%5Cu8bad%5Cu7ec3%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+6%2C+%22name%22%3A+%22resumeMod%22%2C+%22value%22%3A+%22%22%2C+%22description%22%3A+%22%5Cu7ee7%5Cu7eed%5Cu8bad%5Cu7ec3%5Cu6a21%5Cu578b%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22E%22%2C+%22items%22%3A+%22%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+7%2C+%22name%22%3A+%22CLASS_NAMES%22%2C+%22value%22%3A+%5B%22hole%22%2C+%22456%22%2C+%22aeroplane%22%2C+%22tvmonitor%22%2C+%22train%22%2C+%22boat%22%2C+%22dog%22%2C+%22chair%22%2C+%22bird%22%2C+%22bicycle%22%2C+%22person%22%2C+%22bottle%22%2C+%22sheep%22%2C+%22cat%22%5D%2C+%22description%22%3A+%22%5Cu7c7b%5Cu522b%5Cu540d%5Cu79f0%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22L%22%2C+%22items%22%3A+%22%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+8%2C+%22name%22%3A+%22DatasetDir%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2F194741569180540928%2Fori%22%2C+%22description%22%3A+%22%5Cu6570%5Cu636e%5Cu96c6%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fdatasets%2Ftest%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%5D&id=194741569180540928_20_train HTTP/1.1" 200 161 0.050371
删除图片数据
删除json数据
train_server: weights=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights//yolov5s.pt, savemodel=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/1128test_194741569180540928_R-ODY_20_640.pt, cfg=, data=/mnt/sdc/algorithm/R-ODY/app/yolov5/data/coco128.yaml, hyp=/mnt/sdc/algorithm/R-ODY/app/yolov5/data/hyps/hyp.scratch-low.yaml, epochs=10, batch_size=4, imgsz=640, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, noplots=False, evolve=None, bucket=, cache=None, image_weights=False, device=cuda:0, multi_scale=False, single_cls=False, optimizer=SGD, sync_bn=False, workers=8, project=/mnt/sdc/algorithm/R-ODY/app/yolov5/runs/train, name=exp, exist_ok=False, quad=False, cos_lr=False, label_smoothing=0.0, patience=100, freeze=[0], save_period=-1, seed=0, local_rank=-1, entity=None, upload_dataset=False, bbox_interval=-1, artifact_alias=latest
Weights & Biases: run 'pip install wandb' to automatically track and visualize YOLOv5 🚀 runs in Weights & Biases
ClearML: run 'pip install clearml' to automatically track, visualize and remotely train YOLOv5 🚀 in ClearML
TensorBoard: Start with 'tensorboard --logdir /mnt/sdc/algorithm/R-ODY/app/yolov5/runs/train', view at http://localhost:6006/
Overriding model.yaml nc=80 with nc=14
from n params module arguments
0 -1 1 3520 app.yolov5.models.common.Conv [3, 32, 6, 2, 2]
1 -1 1 18560 app.yolov5.models.common.Conv [32, 64, 3, 2]
2 -1 1 18816 app.yolov5.models.common.C3 [64, 64, 1]
3 -1 1 73984 app.yolov5.models.common.Conv [64, 128, 3, 2]
4 -1 2 115712 app.yolov5.models.common.C3 [128, 128, 2]
5 -1 1 295424 app.yolov5.models.common.Conv [128, 256, 3, 2]
6 -1 3 625152 app.yolov5.models.common.C3 [256, 256, 3]
7 -1 1 1180672 app.yolov5.models.common.Conv [256, 512, 3, 2]
8 -1 1 1182720 app.yolov5.models.common.C3 [512, 512, 1]
9 -1 1 656896 app.yolov5.models.common.SPPF [512, 512, 5]
10 -1 1 131584 app.yolov5.models.common.Conv [512, 256, 1, 1]
11 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
12 [-1, 6] 1 0 app.yolov5.models.common.Concat [1]
13 -1 1 361984 app.yolov5.models.common.C3 [512, 256, 1, False]
14 -1 1 33024 app.yolov5.models.common.Conv [256, 128, 1, 1]
15 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
16 [-1, 4] 1 0 app.yolov5.models.common.Concat [1]
17 -1 1 90880 app.yolov5.models.common.C3 [256, 128, 1, False]
18 -1 1 147712 app.yolov5.models.common.Conv [128, 128, 3, 2]
19 [-1, 14] 1 0 app.yolov5.models.common.Concat [1]
20 -1 1 296448 app.yolov5.models.common.C3 [256, 256, 1, False]
21 -1 1 590336 app.yolov5.models.common.Conv [256, 256, 3, 2]
22 [-1, 10] 1 0 app.yolov5.models.common.Concat [1]
23 -1 1 1182720 app.yolov5.models.common.C3 [512, 512, 1, False]
24 [17, 20, 23] 1 51243 app.yolov5.models.yolo.Detect [14, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]], [128, 256, 512]]
Model summary: 270 layers, 7057387 parameters, 7057387 gradients, 16.1 GFLOPs
**********************************
[<geventwebsocket.websocket.WebSocket object at 0x7fcf5499d7c0>]
**********************************
**********************************
{'195095688265211904_17_detect': [<geventwebsocket.websocket.WebSocket object at 0x7fd0e269a340>, <geventwebsocket.websocket.WebSocket object at 0x7fcf55fe9820>, <geventwebsocket.websocket.WebSocket object at 0x7fcfb9ef6760>, <geventwebsocket.websocket.WebSocket object at 0x7fcf55fe9e20>], '194741569180540928_14_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06760>], '194741569180540928_15_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06a60>], '194741569180540928_16_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06520>], '194741569180540928_17_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf5499d100>], '194741569180540928_18_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf5499d460>], '194741569180540928_19_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06880>], '194741569180540928_20_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf5499d7c0>]}
**********************************
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**********************************
cuda:0
图像： ['2007_000032.jpg', '2007_000241.jpg', '2007_000068.jpg', '4.jpg', '3.jpg', '2007_000033.jpg', '10.jpg', '2007_000042.jpg', '7.jpg', '2007_000170.jpg', '2007_001583.jpg', '8.jpg', '2007_000187.jpg', '1.jpg', '2007_001457.jpg', '2007_000061.jpg', '2007_000027.jpg', '2007_000063.jpg', '2007_000129.jpg', '5.jpg', '2007_000123.jpg', '2007_000121.jpg', '9.jpg', '2007_000175.jpg', '2007_000039.jpg', '2007_001430.jpg', '6.jpg', '2007_001585.jpg', '2.jpg']
图像路径 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/194741569180540928/ori/images/2007_000032.jpg
1111
标签 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/194741569180540928/ori/labels/2007_000032.json
2222
ROOT############### /mnt/sdc/algorithm/R-ODY/app/yolov5
opt.device: cuda:0
device: cuda:0
get in train()
Process 194741569180540928_20_train:
Traceback (most recent call last):
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/flask_sockets.py", line 40, in __call__
handler, values = adapter.match()
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/werkzeug/routing.py", line 1945, in match
raise NotFound()
werkzeug.exceptions.NotFound: 404 Not Found: The requested URL was not found on the server. If you entered the URL manually please check your spelling and try again.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/multiprocessing/process.py", line 315, in _bootstrap
self.run()
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/multiprocessing/process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File "/mnt/sdc/algorithm/R-ODY/app/controller/AlgorithmController.py", line 327, in train_R0DY
train_start(weights, savemodel, epoches, img_size, batch_size, device, data_list, id, getsomething)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/train_server.py", line 733, in train_start
main(opt,data_list,id,getsomething)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/train_server.py", line 630, in main
train(opt.hyp, opt, device, data_list,id,getsomething,callbacks)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/train_server.py", line 168, in train
model = Model(cfg or ckpt['model'].yaml, ch=3, nc=nc, anchors=hyp.get('anchors')).to(device) # create
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 673, in to
return self._apply(convert)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/models/yolo.py", line 136, in _apply
self = super()._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 409, in _apply
param_applied = fn(param)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 671, in convert
return t.to(device, dtype if t.is_floating_point() or t.is_complex() else None, non_blocking)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/cuda/__init__.py", line 160, in _lazy_init
raise RuntimeError(
RuntimeError: Cannot re-initialize CUDA in forked subprocess. To use CUDA with multiprocessing, you must use the 'spawn' start method
192.168.0.20 - - [2022-11-29 10:21:55] "GET /api/obtain_train_param HTTP/1.1" 200 1936 0.000899
------进入websocket
存储ws连接对象
192.168.0.20 - - [2022-11-29 10:22:24] "GET /api/start_train_algorithm?param=%5B%7B%22index%22%3A+0%2C+%22name%22%3A+%22epochnum%22%2C+%22value%22%3A+10%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu8f6e%5Cu6b21%22%2C+%22default%22%3A+100%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+1%2C+%22name%22%3A+%22batch_size%22%2C+%22value%22%3A+4%2C+%22description%22%3A+%22%5Cu6279%5Cu6b21%5Cu56fe%5Cu50cf%5Cu6570%5Cu91cf%22%2C+%22default%22%3A+1%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+2%2C+%22name%22%3A+%22img_size%22%2C+%22value%22%3A+640%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu56fe%5Cu50cf%5Cu5927%5Cu5c0f%22%2C+%22default%22%3A+640%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+3%2C+%22name%22%3A+%22device%22%2C+%22value%22%3A+%22cuda%3A0%22%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu6838%5Cu5fc3%22%2C+%22default%22%3A+%22cuda%3A0%22%2C+%22type%22%3A+%22E%22%2C+%22items%22%3A+%5B%22cuda%3A0%22%2C+%22cuda%3A1%22%5D%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+4%2C+%22name%22%3A+%22saveModDir%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F%5Cu6838%5Cu9178%5Cu68c0%5Cu6d4b_190857268466688000_R-ODY_18.pt%22%2C+%22description%22%3A+%22%5Cu4fdd%5Cu5b58%5Cu6a21%5Cu578b%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fsaved_model%2Ftest.pt%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+5%2C+%22name%22%3A+%22resumeModPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F%2Fyolov5s.pt%22%2C+%22description%22%3A+%22%5Cu7ee7%5Cu7eed%5Cu8bad%5Cu7ec3%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+6%2C+%22name%22%3A+%22resumeMod%22%2C+%22value%22%3A+%22%2F1128test_194741569180540928_R-ODY_13_640.pt%22%2C+%22description%22%3A+%22%5Cu7ee7%5Cu7eed%5Cu8bad%5Cu7ec3%5Cu6a21%5Cu578b%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22E%22%2C+%22items%22%3A+%22%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+7%2C+%22name%22%3A+%22CLASS_NAMES%22%2C+%22value%22%3A+%5B%22hole%22%2C+%22456%22%2C+%22zui%22%2C+%22mianbang%22%5D%2C+%22description%22%3A+%22%5Cu7c7b%5Cu522b%5Cu540d%5Cu79f0%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22L%22%2C+%22items%22%3A+%22%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+8%2C+%22name%22%3A+%22DatasetDir%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2F190857268466688000%2Fori%22%2C+%22description%22%3A+%22%5Cu6570%5Cu636e%5Cu96c6%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fdatasets%2Ftest%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%5D&id=190857268466688000_18_train HTTP/1.1" 200 161 0.050019
删除图片数据
删除json数据
192.168.0.20 - - [2022-11-29 10:22:26] "GET /api/obtain_download_pt_param HTTP/1.1" 200 792 0.000835
train_server: weights=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights//yolov5s.pt, savemodel=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/核酸检测_190857268466688000_R-ODY_18_640.pt, cfg=, data=/mnt/sdc/algorithm/R-ODY/app/yolov5/data/coco128.yaml, hyp=/mnt/sdc/algorithm/R-ODY/app/yolov5/data/hyps/hyp.scratch-low.yaml, epochs=10, batch_size=4, imgsz=640, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, noplots=False, evolve=None, bucket=, cache=None, image_weights=False, device=cuda:0, multi_scale=False, single_cls=False, optimizer=SGD, sync_bn=False, workers=8, project=/mnt/sdc/algorithm/R-ODY/app/yolov5/runs/train, name=exp, exist_ok=False, quad=False, cos_lr=False, label_smoothing=0.0, patience=100, freeze=[0], save_period=-1, seed=0, local_rank=-1, entity=None, upload_dataset=False, bbox_interval=-1, artifact_alias=latest
Weights & Biases: run 'pip install wandb' to automatically track and visualize YOLOv5 🚀 runs in Weights & Biases
ClearML: run 'pip install clearml' to automatically track, visualize and remotely train YOLOv5 🚀 in ClearML
TensorBoard: Start with 'tensorboard --logdir /mnt/sdc/algorithm/R-ODY/app/yolov5/runs/train', view at http://localhost:6006/
Overriding model.yaml nc=80 with nc=4
from n params module arguments
0 -1 1 3520 app.yolov5.models.common.Conv [3, 32, 6, 2, 2]
1 -1 1 18560 app.yolov5.models.common.Conv [32, 64, 3, 2]
2 -1 1 18816 app.yolov5.models.common.C3 [64, 64, 1]
3 -1 1 73984 app.yolov5.models.common.Conv [64, 128, 3, 2]
4 -1 2 115712 app.yolov5.models.common.C3 [128, 128, 2]
5 -1 1 295424 app.yolov5.models.common.Conv [128, 256, 3, 2]
6 -1 3 625152 app.yolov5.models.common.C3 [256, 256, 3]
7 -1 1 1180672 app.yolov5.models.common.Conv [256, 512, 3, 2]
8 -1 1 1182720 app.yolov5.models.common.C3 [512, 512, 1]
9 -1 1 656896 app.yolov5.models.common.SPPF [512, 512, 5]
10 -1 1 131584 app.yolov5.models.common.Conv [512, 256, 1, 1]
11 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
12 [-1, 6] 1 0 app.yolov5.models.common.Concat [1]
13 -1 1 361984 app.yolov5.models.common.C3 [512, 256, 1, False]
14 -1 1 33024 app.yolov5.models.common.Conv [256, 128, 1, 1]
15 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
16 [-1, 4] 1 0 app.yolov5.models.common.Concat [1]
17 -1 1 90880 app.yolov5.models.common.C3 [256, 128, 1, False]
18 -1 1 147712 app.yolov5.models.common.Conv [128, 128, 3, 2]
19 [-1, 14] 1 0 app.yolov5.models.common.Concat [1]
20 -1 1 296448 app.yolov5.models.common.C3 [256, 256, 1, False]
21 -1 1 590336 app.yolov5.models.common.Conv [256, 256, 3, 2]
22 [-1, 10] 1 0 app.yolov5.models.common.Concat [1]
23 -1 1 1182720 app.yolov5.models.common.C3 [512, 512, 1, False]
24 [17, 20, 23] 1 24273 app.yolov5.models.yolo.Detect [4, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]], [128, 256, 512]]
Model summary: 270 layers, 7030417 parameters, 7030417 gradients, 16.0 GFLOPs
**********************************
[<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06e80>]
**********************************
**********************************
{'195095688265211904_17_detect': [<geventwebsocket.websocket.WebSocket object at 0x7fd0e269a340>, <geventwebsocket.websocket.WebSocket object at 0x7fcf55fe9820>, <geventwebsocket.websocket.WebSocket object at 0x7fcfb9ef6760>, <geventwebsocket.websocket.WebSocket object at 0x7fcf55fe9e20>], '194741569180540928_14_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06760>], '194741569180540928_15_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06a60>], '194741569180540928_16_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06520>], '194741569180540928_17_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf5499d100>], '194741569180540928_18_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf5499d460>], '194741569180540928_19_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06880>], '194741569180540928_20_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf5499d7c0>], '190857268466688000_18_train': [<geventwebsocket.websocket.WebSocket object at 0x7fcf54d06e80>]}
**********************************
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**********************************
cuda:0
图像： ['IMG_20221117_132941~1.jpg', 'IMG_20221117_133002~1.jpg', 'IMG_20221117_152005~1.jpg', 'IMG_20221117_133005~1.jpg', 'IMG_20221117_132939~1.jpg', 'IMG_20221117_151945~1.jpg', 'IMG_20221117_133009~1.jpg', 'IMG_20221117_152023~1.jpg', 'IMG_20221117_133035~1.jpg', 'IMG_20221117_132947~1.jpg', 'IMG_20221117_151925~1.jpg', 'IMG_20221117_152026~1.jpg', 'IMG_20221117_133037~1.jpg', 'IMG_20221117_152018~1.jpg', 'IMG_20221117_152002~1.jpg', 'IMG_20221117_152004~1.jpg', 'IMG_20221117_152019~1.jpg', 'IMG_20221117_133006~1.jpg', 'IMG_20221117_152020~1.jpg', 'IMG_20221117_151959~1.jpg', 'IMG_20221117_152024~1.jpg', 'IMG_20221117_151921~1.jpg', 'IMG_20221117_151923~1.jpg', 'IMG_20221117_133038~1.jpg', 'IMG_20221117_151943~1.jpg', 'IMG_20221117_151924~1.jpg', 'IMG_20221117_152022~1.jpg', 'IMG_20221117_133032~1.jpg', 'IMG_20221117_151957~1.jpg', 'IMG_20221117_151939~1.jpg', 'IMG_20221117_133040~1.jpg', 'IMG_20221117_151946~1.jpg', 'IMG_20221117_151944~1.jpg', 'IMG_20221117_133007~1.jpg', 'IMG_20221117_132946~1.jpg', 'IMG_20221117_133004~1.jpg', 'IMG_20221117_152001~1.jpg', 'IMG_20221117_151941~1.jpg', 'IMG_20221117_151919~1.jpg', 'IMG_20221117_132944~1.jpg']
图像路径 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/190857268466688000/ori/images/IMG_20221117_132941~1.jpg
1111
标签 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/190857268466688000/ori/labels/IMG_20221117_132941~1.json
2222
ROOT############### /mnt/sdc/algorithm/R-ODY/app/yolov5
opt.device: cuda:0
device: cuda:0
get in train()
Process 190857268466688000_18_train:
Traceback (most recent call last):
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/flask_sockets.py", line 40, in __call__
handler, values = adapter.match()
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/werkzeug/routing.py", line 1945, in match
raise NotFound()
werkzeug.exceptions.NotFound: 404 Not Found: The requested URL was not found on the server. If you entered the URL manually please check your spelling and try again.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/multiprocessing/process.py", line 315, in _bootstrap
self.run()
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/multiprocessing/process.py", line 108, in run
self._target(*self._args, **self._kwargs)
File "/mnt/sdc/algorithm/R-ODY/app/controller/AlgorithmController.py", line 327, in train_R0DY
train_start(weights, savemodel, epoches, img_size, batch_size, device, data_list, id, getsomething)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/train_server.py", line 733, in train_start
main(opt,data_list,id,getsomething)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/train_server.py", line 630, in main
train(opt.hyp, opt, device, data_list,id,getsomething,callbacks)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/train_server.py", line 168, in train
model = Model(cfg or ckpt['model'].yaml, ch=3, nc=nc, anchors=hyp.get('anchors')).to(device) # create
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 673, in to
return self._apply(convert)
File "/mnt/sdc/algorithm/R-ODY/app/yolov5/models/yolo.py", line 136, in _apply
self = super()._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 387, in _apply
module._apply(fn)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 409, in _apply
param_applied = fn(param)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/nn/modules/module.py", line 671, in convert
return t.to(device, dtype if t.is_floating_point() or t.is_complex() else None, non_blocking)
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/torch/cuda/__init__.py", line 160, in _lazy_init
raise RuntimeError(
RuntimeError: Cannot re-initialize CUDA in forked subprocess. To use CUDA with multiprocessing, you must use the 'spawn' start method
export: data=app/yolov5/data/coco128.yaml, weights=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/核酸检测_190857268466688000_R-ODY_17_640.pt, imgsz=[640, 640], batch_size=1, device=0, half=False, inplace=False, train=False, keras=False, optimize=False, int8=False, dynamic=False, simplify=False, opset=11, verbose=False, workspace=4, nms=False, agnostic_nms=False, topk_per_class=100, topk_all=100, iou_thres=0.45, conf_thres=0.25, include=['torchscript', 'onnx']
YOLOv5 🚀 2022-11-7 Python-3.8.13 torch-1.8.0+cu111 CUDA:0 (Tesla T4, 15110MiB)
Fusing layers...
Model summary: 213 layers, 7020913 parameters, 0 gradients, 15.8 GFLOPs
PyTorch: starting from /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/核酸检测_190857268466688000_R-ODY_17_640.pt with output shape (1, 25200, 9) (13.8 MB)
TorchScript: starting export with torch 1.8.0+cu111...
TorchScript: export success ✅ 1.0s, saved as /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/核酸检测_190857268466688000_R-ODY_17_640.torchscript (27.3 MB)
ONNX: starting export with onnx 1.12.0...
ONNX: export success ✅ 1.6s, saved as /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/核酸检测_190857268466688000_R-ODY_17_640.onnx (27.2 MB)
Export complete (2.8s)
Results saved to /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights
Detect: python detect.py --weights /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/核酸检测_190857268466688000_R-ODY_17_640.onnx
Validate: python val.py --weights /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/核酸检测_190857268466688000_R-ODY_17_640.onnx
PyTorch Hub: model = torch.hub.load('ultralytics/yolov5', 'custom', '/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/核酸检测_190857268466688000_R-ODY_17_640.onnx')
Visualize: https://netron.app
192.168.0.20 - - [2022-11-29 10:22:31] "GET /api/start_download_pt?param=%5B%7B%22index%22%3A+0%2C+%22name%22%3A+%22exp_inputPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F%5Cu6838%5Cu9178%5Cu68c0%5Cu6d4b_190857268466688000_R-ODY_17_640.pt%22%2C+%22description%22%3A+%22%5Cu8f6c%5Cu5316%5Cu6a21%5Cu578b%5Cu8f93%5Cu5165%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22E%3A%2Falg_demo-master%2Falg_demo%2Fapp%2Fyolov5%2F%5Cu5706%5Cu5b54_123_RODY_1_640.pt%2F%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+1%2C+%22name%22%3A+%22device%22%2C+%22value%22%3A+%22gpu%22%2C+%22description%22%3A+%22CPU%5Cu6216GPU%22%2C+%22default%22%3A+%22gpu%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+2%2C+%22name%22%3A+%22imgsz%22%2C+%22value%22%3A+640%2C+%22description%22%3A+%22%5Cu56fe%5Cu50cf%5Cu5927%5Cu5c0f%22%2C+%22default%22%3A+640%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%5D&id=737 HTTP/1.1" 200 270 3.030957
------进入websocket
输入模型： /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/核酸检测_190857268466688000_R-ODY_17_640.pt
['torchscript', 'onnx']
['torchscript', 'onnx']
('torchscript', 'onnx', 'openvino', 'engine', 'coreml', 'saved_model', 'pb', 'tflite', 'edgetpu', 'tfjs')
True
模型路径： /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/核酸检测_190857268466688000_R-ODY_17_640.zip
存储ws连接对象
192.168.0.20 - - [2022-11-29 10:44:19] "GET /api/start_train_algorithm?param=%5B%7B%22index%22%3A+0%2C+%22name%22%3A+%22epochnum%22%2C+%22value%22%3A+10%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu8f6e%5Cu6b21%22%2C+%22default%22%3A+100%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+1%2C+%22name%22%3A+%22batch_size%22%2C+%22value%22%3A+4%2C+%22description%22%3A+%22%5Cu6279%5Cu6b21%5Cu56fe%5Cu50cf%5Cu6570%5Cu91cf%22%2C+%22default%22%3A+1%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+2%2C+%22name%22%3A+%22img_size%22%2C+%22value%22%3A+640%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu56fe%5Cu50cf%5Cu5927%5Cu5c0f%22%2C+%22default%22%3A+640%2C+%22type%22%3A+%22I%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+3%2C+%22name%22%3A+%22device%22%2C+%22value%22%3A+%22cuda%3A0%22%2C+%22description%22%3A+%22%5Cu8bad%5Cu7ec3%5Cu6838%5Cu5fc3%22%2C+%22default%22%3A+%22cuda%3A0%22%2C+%22type%22%3A+%22E%22%2C+%22items%22%3A+%5B%22cuda%3A0%22%2C+%22cuda%3A1%22%5D%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+4%2C+%22name%22%3A+%22saveModDir%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F1128test_194741569180540928_R-ODY_21.pt%22%2C+%22description%22%3A+%22%5Cu4fdd%5Cu5b58%5Cu6a21%5Cu578b%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fsaved_model%2Ftest.pt%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+5%2C+%22name%22%3A+%22resumeModPath%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2Fweights%2F%2Fyolov5s.pt%22%2C+%22description%22%3A+%22%5Cu7ee7%5Cu7eed%5Cu8bad%5Cu7ec3%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+6%2C+%22name%22%3A+%22resumeMod%22%2C+%22value%22%3A+%22%22%2C+%22description%22%3A+%22%5Cu7ee7%5Cu7eed%5Cu8bad%5Cu7ec3%5Cu6a21%5Cu578b%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22E%22%2C+%22items%22%3A+%22%22%2C+%22show%22%3A+true%7D%2C+%7B%22index%22%3A+7%2C+%22name%22%3A+%22CLASS_NAMES%22%2C+%22value%22%3A+%5B%22hole%22%2C+%22456%22%2C+%22aeroplane%22%2C+%22tvmonitor%22%2C+%22train%22%2C+%22boat%22%2C+%22dog%22%2C+%22chair%22%2C+%22bird%22%2C+%22bicycle%22%2C+%22person%22%2C+%22bottle%22%2C+%22sheep%22%2C+%22cat%22%5D%2C+%22description%22%3A+%22%5Cu7c7b%5Cu522b%5Cu540d%5Cu79f0%22%2C+%22default%22%3A+%22%22%2C+%22type%22%3A+%22L%22%2C+%22items%22%3A+%22%22%2C+%22show%22%3A+false%7D%2C+%7B%22index%22%3A+8%2C+%22name%22%3A+%22DatasetDir%22%2C+%22value%22%3A+%22%2Fmnt%2Fsdc%2FIntelligentizeAI%2FIntelligentizeAI%2Fdata_set%2F194741569180540928%2Fori%22%2C+%22description%22%3A+%22%5Cu6570%5Cu636e%5Cu96c6%5Cu8def%5Cu5f84%22%2C+%22default%22%3A+%22.%2Fapp%2Fmaskrcnn%2Fdatasets%2Ftest%22%2C+%22type%22%3A+%22S%22%2C+%22show%22%3A+false%7D%5D&id=194741569180540928_21_train HTTP/1.1" 200 161 0.051209
删除图片数据
删除json数据
train_server: weights=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights//yolov5s.pt, savemodel=/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights/1128test_194741569180540928_R-ODY_21_640.pt, cfg=, data=/mnt/sdc/algorithm/R-ODY/app/yolov5/data/coco128.yaml, hyp=/mnt/sdc/algorithm/R-ODY/app/yolov5/data/hyps/hyp.scratch-low.yaml, epochs=10, batch_size=4, imgsz=640, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, noplots=False, evolve=None, bucket=, cache=None, image_weights=False, device=cuda:0, multi_scale=False, single_cls=False, optimizer=SGD, sync_bn=False, workers=8, project=/mnt/sdc/algorithm/R-ODY/app/yolov5/runs/train, name=exp, exist_ok=False, quad=False, cos_lr=False, label_smoothing=0.0, patience=100, freeze=[0], save_period=-1, seed=0, local_rank=-1, entity=None, upload_dataset=False, bbox_interval=-1, artifact_alias=latest
Weights & Biases: run 'pip install wandb' to automatically track and visualize YOLOv5 🚀 runs in Weights & Biases
ClearML: run 'pip install clearml' to automatically track, visualize and remotely train YOLOv5 🚀 in ClearML
TensorBoard: Start with 'tensorboard --logdir /mnt/sdc/algorithm/R-ODY/app/yolov5/runs/train', view at http://localhost:6006/
Overriding model.yaml nc=80 with nc=14
from n params module arguments
0 -1 1 3520 app.yolov5.models.common.Conv [3, 32, 6, 2, 2]
1 -1 1 18560 app.yolov5.models.common.Conv [32, 64, 3, 2]
2 -1 1 18816 app.yolov5.models.common.C3 [64, 64, 1]
3 -1 1 73984 app.yolov5.models.common.Conv [64, 128, 3, 2]
4 -1 2 115712 app.yolov5.models.common.C3 [128, 128, 2]
5 -1 1 295424 app.yolov5.models.common.Conv [128, 256, 3, 2]
6 -1 3 625152 app.yolov5.models.common.C3 [256, 256, 3]
7 -1 1 1180672 app.yolov5.models.common.Conv [256, 512, 3, 2]
8 -1 1 1182720 app.yolov5.models.common.C3 [512, 512, 1]
9 -1 1 656896 app.yolov5.models.common.SPPF [512, 512, 5]
10 -1 1 131584 app.yolov5.models.common.Conv [512, 256, 1, 1]
11 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
12 [-1, 6] 1 0 app.yolov5.models.common.Concat [1]
13 -1 1 361984 app.yolov5.models.common.C3 [512, 256, 1, False]
14 -1 1 33024 app.yolov5.models.common.Conv [256, 128, 1, 1]
15 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
16 [-1, 4] 1 0 app.yolov5.models.common.Concat [1]
17 -1 1 90880 app.yolov5.models.common.C3 [256, 128, 1, False]
18 -1 1 147712 app.yolov5.models.common.Conv [128, 128, 3, 2]
19 [-1, 14] 1 0 app.yolov5.models.common.Concat [1]
20 -1 1 296448 app.yolov5.models.common.C3 [256, 256, 1, False]
21 -1 1 590336 app.yolov5.models.common.Conv [256, 256, 3, 2]
22 [-1, 10] 1 0 app.yolov5.models.common.Concat [1]
23 -1 1 1182720 app.yolov5.models.common.C3 [512, 512, 1, False]
24 [17, 20, 23] 1 51243 app.yolov5.models.yolo.Detect [14, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]], [128, 256, 512]]