中断训练
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@Desc：
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@Desc：
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"""
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"""
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import json
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import multiprocessing
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from app.utils.redis_config import redis_client
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def _init(): # 初始化
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def _init(): # 初始化
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dict = {}
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# 中断标志
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redis_client.__setattr__("_global_dict", json.dumps(dict))
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global _global_dict
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_global_dict = {}
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# # ws列表存储
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# global _active_connections
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# _active_connections = multiprocessing.Manager().list()
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# # ws字典存储
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# global _active_connections_dist
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# _active_connections_dist = multiprocessing.Manager().dict()
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# def get_active_connections():
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# return _active_connections
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# def get_active_connections_dist():
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# return _active_connections_dist
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def set_value(key, value):
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def set_value(key, value):
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# 定义一个全局变量
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# 定义一个全局变量
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dict = redis_client.get_redis().get("_global_dict")
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_global_dict[key] = value
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if dict is None:
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dict = {}
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dict[key] = value
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# redis_client.get_redis().set("_global_dict", json.dumps(dict))
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redis_client.__setattr__("_global_dict", json.dumps(dict))
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def get_value(key):
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def get_value(key):
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# 获得一个全局变量，不存在则提示读取对应变量失败
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# 获得一个全局变量，不存在则提示读取对应变量失败
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try:
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try:
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return redis_client.get_redis().get("_global_dict")[key]
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return _global_dict[key]
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except Exception as e:
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except:
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print(e)
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print('读取' + key + '失败\r\n')
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print('读取' + key + '失败\r\n')
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Binary file not shown.
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path: null
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path: null
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train: /mnt/sdc/aicheck/IntelligentizeAI/data_set/193120735164768256/trained/images/train/
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train: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/190857268466688000/trained/images/train/
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val: /mnt/sdc/aicheck/IntelligentizeAI/data_set/193120735164768256/trained/images/val/
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val: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/190857268466688000/trained/images/val/
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test: null
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test: null
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names:
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names:
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0: hole
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0: hole
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1: '456'
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1: '456'
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2: dog
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2: zui
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3: cat
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3: mianbang
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503
nohup.out
503
nohup.out
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nohup: ignoring input
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nohup: ignoring input
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2022-11-24 08:58:34,262 INFO sqlalchemy.engine.Engine select pg_catalog.version()
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2022-11-29 08:44:22,208 INFO sqlalchemy.engine.Engine select pg_catalog.version()
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2022-11-24 08:58:34,262 INFO sqlalchemy.engine.Engine [raw sql] {}
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2022-11-29 08:44:22,209 INFO sqlalchemy.engine.Engine [raw sql] {}
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2022-11-24 08:58:34,267 INFO sqlalchemy.engine.Engine select current_schema()
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2022-11-29 08:44:22,214 INFO sqlalchemy.engine.Engine select current_schema()
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2022-11-24 08:58:34,267 INFO sqlalchemy.engine.Engine [raw sql] {}
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2022-11-29 08:44:22,214 INFO sqlalchemy.engine.Engine [raw sql] {}
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2022-11-24 08:58:34,272 INFO sqlalchemy.engine.Engine show standard_conforming_strings
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2022-11-29 08:44:22,219 INFO sqlalchemy.engine.Engine show standard_conforming_strings
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2022-11-24 08:58:34,272 INFO sqlalchemy.engine.Engine [raw sql] {}
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2022-11-29 08:44:22,219 INFO sqlalchemy.engine.Engine [raw sql] {}
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2022-11-24 08:58:34,277 INFO sqlalchemy.engine.Engine BEGIN (implicit)
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2022-11-29 08:44:22,225 INFO sqlalchemy.engine.Engine BEGIN (implicit)
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2022-11-24 08:58:34,277 INFO sqlalchemy.engine.Engine COMMIT
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2022-11-29 08:44:22,225 INFO sqlalchemy.engine.Engine COMMIT
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[34m[1mexport: [0mdata=app/yolov5/data/coco128.yaml, weights=/mnt/sdc/aicheck/IntelligentizeAI/data_set/weights/ces2_193120735164768256_R-ODY_2_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']
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[34m[1mdetect_server: [0mid=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
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YOLOv5 🚀 2022-11-7 Python-3.8.13 torch-1.8.0+cu111 CUDA:0 (Tesla T4, 15110MiB)
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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
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To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
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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`.
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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
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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
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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
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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.
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Fusing layers...
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192.168.0.20 - - [2022-11-29 08:44:42] "GET /api/obtain_detect_param HTTP/1.1" 200 1110 0.000672
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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
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[34m[1mdetect_server: [0mid=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
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YOLOv5 🚀 2022-11-7 Python-3.8.13 torch-1.8.0+cu111 CUDA:0 (Tesla T4, 15110MiB)
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Fusing layers...
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Model summary: 213 layers, 7020913 parameters, 0 gradients, 15.8 GFLOPs
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------进入websocket
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Model summary: 213 layers, 7020913 parameters, 0 gradients, 15.8 GFLOPs
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image 1/1 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/camera/微信截图_20221129084118.png: 640x512 1 zui, 1 mianbang, 23.9ms
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Speed: 0.4ms pre-process, 23.9ms inference, 1.5ms NMS per image at shape (1, 3, 640, 640)
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image 1/1 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/camera/微信截图_20221129084118.png: 640x512 1 zui, 1 mianbang, 21.2ms
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Speed: 0.4ms pre-process, 21.2ms inference, 1.1ms NMS per image at shape (1, 3, 640, 640)
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192.168.0.20 - - [2022-11-29 08:46:07] "GET /api/obtain_detect_param HTTP/1.1" 200 1110 0.000634
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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
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[34m[1mdetect_server: [0mid=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
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YOLOv5 🚀 2022-11-7 Python-3.8.13 torch-1.8.0+cu111 CUDA:0 (Tesla T4, 15110MiB)
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Fusing layers...
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Model summary: 213 layers, 7020913 parameters, 0 gradients, 15.8 GFLOPs
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image 1/1 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/camera/微信截图_20221129084118.png: 640x512 1 zui, 1 mianbang, 12.3ms
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Speed: 0.4ms pre-process, 12.3ms inference, 0.8ms NMS per image at shape (1, 3, 640, 640)
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------进入websocket
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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
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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
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[34m[1mdetect_server: [0mid=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
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YOLOv5 🚀 2022-11-7 Python-3.8.13 torch-1.8.0+cu111 CUDA:0 (Tesla T4, 15110MiB)
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Fusing layers...
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Model summary: 213 layers, 7020913 parameters, 0 gradients, 15.8 GFLOPs
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image 1/1 /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/195095688265211904/camera/微信截图_20221129084118.png: 640x512 1 zui, 1 mianbang, 12.3ms
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Speed: 0.4ms pre-process, 12.3ms inference, 0.8ms NMS per image at shape (1, 3, 640, 640)
|
||||||
|
------进入websocket
|
||||||
|
192.168.0.20 - - [2022-11-29 09:46:07] "GET /api/obtain_train_param HTTP/1.1" 200 1936 0.003772
|
||||||
|
------进入websocket
|
||||||
|
------进入websocket
|
||||||
|
192.168.0.20 - - [2022-11-29 09:52:50] "GET /api/obtain_train_param HTTP/1.1" 200 1936 0.000666
|
||||||
|
------进入websocket
|
||||||
|
------进入websocket
|
||||||
|
------进入websocket
|
||||||
|
-----------回调消息成功------------
|
||||||
|
-----------回调消息成功------------
|
||||||
|
-----------回调消息成功------------
|
||||||
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|
||||||
|
-----------回调消息成功------------
|
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|
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|
||||||
|
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|
||||||
|
-----------回调消息成功------------
|
||||||
|
192.168.0.20 - - [2022-11-29 10:06:37] "GET /api/obtain_train_param HTTP/1.1" 200 1936 0.000656
|
||||||
|
------进入websocket
|
||||||
|
存储ws连接对象
|
||||||
|
[31m[1mrequirements:[0m /mnt/sdc/algorithm/R-ODY/app/yolov5/requirements.txt not found, check failed.
|
||||||
|
True
|
||||||
|
[31m[1mrequirements:[0m /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
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||||||
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图片总数量： 1
|
||||||
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处理成功数量： 1
|
||||||
|
处理失败数量： 0
|
||||||
|
[31m[1mrequirements:[0m /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
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||||||
|
处理失败数量： 0
|
||||||
|
存储ws连接对象
|
||||||
|
[31m[1mrequirements:[0m /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
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||||||
|
存储ws连接对象
|
||||||
|
存储ws连接对象
|
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|
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|
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
|
||||||
|
删除图片数据
|
||||||
|
删除json数据
|
||||||
|
[34m[1mtrain_server: [0mweights=/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
|
||||||
|
[34m[1mWeights & Biases: [0mrun 'pip install wandb' to automatically track and visualize YOLOv5 🚀 runs in Weights & Biases
|
||||||
|
[34m[1mClearML: [0mrun 'pip install clearml' to automatically track, visualize and remotely train YOLOv5 🚀 in ClearML
|
||||||
|
[34m[1mTensorBoard: [0mStart 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
|
||||||
|
[34m[1mtrain_server: [0mweights=/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
|
||||||
|
[34m[1mWeights & Biases: [0mrun 'pip install wandb' to automatically track and visualize YOLOv5 🚀 runs in Weights & Biases
|
||||||
|
[34m[1mClearML: [0mrun 'pip install clearml' to automatically track, visualize and remotely train YOLOv5 🚀 in ClearML
|
||||||
|
[34m[1mTensorBoard: [0mStart 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>]}
|
||||||
|
**********************************
|
||||||
|
[{"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_20.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_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
|
||||||
|
[34m[1mtrain_server: [0mweights=/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
|
||||||
|
[34m[1mWeights & Biases: [0mrun 'pip install wandb' to automatically track and visualize YOLOv5 🚀 runs in Weights & Biases
|
||||||
|
[34m[1mClearML: [0mrun 'pip install clearml' to automatically track, visualize and remotely train YOLOv5 🚀 in ClearML
|
||||||
|
[34m[1mTensorBoard: [0mStart 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>]}
|
||||||
|
**********************************
|
||||||
|
[{"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/\u6838\u9178\u68c0\u6d4b_190857268466688000_R-ODY_18.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": "/1128test_194741569180540928_R-ODY_13_640.pt", "description": "\u7ee7\u7eed\u8bad\u7ec3\u6a21\u578b", "default": "", "type": "E", "items": "", "show": true}, {"index": 7, "name": "CLASS_NAMES", "value": ["hole", "456", "zui", "mianbang"], "description": "\u7c7b\u522b\u540d\u79f0", "default": "", "type": "L", "items": "", "show": false}, {"index": 8, "name": "DatasetDir", "value": "/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/190857268466688000/ori", "description": "\u6570\u636e\u96c6\u8def\u5f84", "default": "./app/maskrcnn/datasets/test", "type": "S", "show": false}]
|
||||||
|
**********************************
|
||||||
|
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
|
||||||
|
[34m[1mexport: [0mdata=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)
|
YOLOv5 🚀 2022-11-7 Python-3.8.13 torch-1.8.0+cu111 CUDA:0 (Tesla T4, 15110MiB)
|
||||||
|
|
||||||
Fusing layers...
|
Fusing layers...
|
||||||
Model summary: 213 layers, 7020913 parameters, 0 gradients, 15.8 GFLOPs
|
Model summary: 213 layers, 7020913 parameters, 0 gradients, 15.8 GFLOPs
|
||||||
|
|
||||||
[34m[1mPyTorch:[0m starting from /mnt/sdc/aicheck/IntelligentizeAI/data_set/weights/ces2_193120735164768256_R-ODY_2_640.pt with output shape (1, 25200, 9) (13.8 MB)
|
[34m[1mPyTorch:[0m 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)
|
||||||
|
|
||||||
[34m[1mTorchScript:[0m starting export with torch 1.8.0+cu111...
|
[34m[1mTorchScript:[0m starting export with torch 1.8.0+cu111...
|
||||||
[34m[1mTorchScript:[0m export success ✅ 0.9s, saved as /mnt/sdc/aicheck/IntelligentizeAI/data_set/weights/ces2_193120735164768256_R-ODY_2_640.torchscript (27.3 MB)
|
[34m[1mTorchScript:[0m 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)
|
||||||
|
|
||||||
[34m[1mONNX:[0m starting export with onnx 1.12.0...
|
[34m[1mONNX:[0m starting export with onnx 1.12.0...
|
||||||
[34m[1mONNX:[0m export success ✅ 1.8s, saved as /mnt/sdc/aicheck/IntelligentizeAI/data_set/weights/ces2_193120735164768256_R-ODY_2_640.onnx (27.2 MB)
|
[34m[1mONNX:[0m 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 (6.5s)
|
Export complete (2.8s)
|
||||||
Results saved to [1m/mnt/sdc/aicheck/IntelligentizeAI/data_set/weights[0m
|
Results saved to [1m/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/weights[0m
|
||||||
Detect: python detect.py --weights /mnt/sdc/aicheck/IntelligentizeAI/data_set/weights/ces2_193120735164768256_R-ODY_2_640.onnx
|
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/aicheck/IntelligentizeAI/data_set/weights/ces2_193120735164768256_R-ODY_2_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/aicheck/IntelligentizeAI/data_set/weights/ces2_193120735164768256_R-ODY_2_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
|
Visualize: https://netron.app
|
||||||
192.168.0.20 - - [2022-11-24 08:59:15] "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%2Faicheck%2FIntelligentizeAI%2Fdata_set%2Fweights%2Fces2_193120735164768256_R-ODY_2_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=875 HTTP/1.1" 200 240 7.984953
|
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
|
||||||
[34m[1mexport: [0mdata=app/yolov5/data/coco128.yaml, weights=/mnt/sdc/aicheck/IntelligentizeAI/data_set/weights/ces2_193120735164768256_R-ODY_2_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']
|
------进入websocket
|
||||||
YOLOv5 🚀 2022-11-7 Python-3.8.13 torch-1.8.0+cu111 CUDA:0 (Tesla T4, 15110MiB)
|
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
|
||||||
|
[34m[1mtrain_server: [0mweights=/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
|
||||||
|
[34m[1mWeights & Biases: [0mrun 'pip install wandb' to automatically track and visualize YOLOv5 🚀 runs in Weights & Biases
|
||||||
|
[34m[1mClearML: [0mrun 'pip install clearml' to automatically track, visualize and remotely train YOLOv5 🚀 in ClearML
|
||||||
|
[34m[1mTensorBoard: [0mStart 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
|
||||||
|
|
||||||
Fusing layers...
|
from n params module arguments
|
||||||
Model summary: 213 layers, 7020913 parameters, 0 gradients, 15.8 GFLOPs
|
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]
|
||||||
[34m[1mPyTorch:[0m starting from /mnt/sdc/aicheck/IntelligentizeAI/data_set/weights/ces2_193120735164768256_R-ODY_2_640.pt with output shape (1, 25200, 9) (13.8 MB)
|
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]
|
||||||
[34m[1mTorchScript:[0m starting export with torch 1.8.0+cu111...
|
4 -1 2 115712 app.yolov5.models.common.C3 [128, 128, 2]
|
||||||
[34m[1mTorchScript:[0m export success ✅ 0.8s, saved as /mnt/sdc/aicheck/IntelligentizeAI/data_set/weights/ces2_193120735164768256_R-ODY_2_640.torchscript (27.3 MB)
|
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]
|
||||||
[34m[1mONNX:[0m starting export with onnx 1.12.0...
|
7 -1 1 1180672 app.yolov5.models.common.Conv [256, 512, 3, 2]
|
||||||
[34m[1mONNX:[0m export success ✅ 1.6s, saved as /mnt/sdc/aicheck/IntelligentizeAI/data_set/weights/ces2_193120735164768256_R-ODY_2_640.onnx (27.2 MB)
|
8 -1 1 1182720 app.yolov5.models.common.C3 [512, 512, 1]
|
||||||
|
9 -1 1 656896 app.yolov5.models.common.SPPF [512, 512, 5]
|
||||||
Export complete (2.6s)
|
10 -1 1 131584 app.yolov5.models.common.Conv [512, 256, 1, 1]
|
||||||
Results saved to [1m/mnt/sdc/aicheck/IntelligentizeAI/data_set/weights[0m
|
11 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
|
||||||
Detect: python detect.py --weights /mnt/sdc/aicheck/IntelligentizeAI/data_set/weights/ces2_193120735164768256_R-ODY_2_640.onnx
|
12 [-1, 6] 1 0 app.yolov5.models.common.Concat [1]
|
||||||
Validate: python val.py --weights /mnt/sdc/aicheck/IntelligentizeAI/data_set/weights/ces2_193120735164768256_R-ODY_2_640.onnx
|
13 -1 1 361984 app.yolov5.models.common.C3 [512, 256, 1, False]
|
||||||
PyTorch Hub: model = torch.hub.load('ultralytics/yolov5', 'custom', '/mnt/sdc/aicheck/IntelligentizeAI/data_set/weights/ces2_193120735164768256_R-ODY_2_640.onnx')
|
14 -1 1 33024 app.yolov5.models.common.Conv [256, 128, 1, 1]
|
||||||
Visualize: https://netron.app
|
15 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
|
||||||
192.168.0.20 - - [2022-11-24 08:59:17] "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%2Faicheck%2FIntelligentizeAI%2Fdata_set%2Fweights%2Fces2_193120735164768256_R-ODY_2_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=875 HTTP/1.1" 200 240 2.709875
|
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]]
|
||||||
|
|||||||
27
train_log.txt
Normal file
27
train_log.txt
Normal file
@ -0,0 +1,27 @@
|
|||||||
|
nohup: ignoring input
|
||||||
|
2022-11-28 17:42:23,653 INFO sqlalchemy.engine.Engine select pg_catalog.version()
|
||||||
|
2022-11-28 17:42:23,653 INFO sqlalchemy.engine.Engine [raw sql] {}
|
||||||
|
2022-11-28 17:42:23,659 INFO sqlalchemy.engine.Engine select current_schema()
|
||||||
|
2022-11-28 17:42:23,659 INFO sqlalchemy.engine.Engine [raw sql] {}
|
||||||
|
2022-11-28 17:42:23,663 INFO sqlalchemy.engine.Engine show standard_conforming_strings
|
||||||
|
2022-11-28 17:42:23,664 INFO sqlalchemy.engine.Engine [raw sql] {}
|
||||||
|
2022-11-28 17:42:23,669 INFO sqlalchemy.engine.Engine BEGIN (implicit)
|
||||||
|
2022-11-28 17:42:23,669 INFO sqlalchemy.engine.Engine COMMIT
|
||||||
|
Traceback (most recent call last):
|
||||||
|
File "./app/run.py", line 134, in <module>
|
||||||
|
server.serve_forever()
|
||||||
|
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/gevent/baseserver.py", line 398, in serve_forever
|
||||||
|
self.start()
|
||||||
|
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/gevent/baseserver.py", line 336, in start
|
||||||
|
self.init_socket()
|
||||||
|
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/gevent/pywsgi.py", line 1545, in init_socket
|
||||||
|
StreamServer.init_socket(self)
|
||||||
|
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/gevent/server.py", line 180, in init_socket
|
||||||
|
self.socket = self.get_listener(self.address, self.backlog, self.family)
|
||||||
|
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/gevent/server.py", line 192, in get_listener
|
||||||
|
return _tcp_listener(address, backlog=backlog, reuse_addr=cls.reuse_addr, family=family)
|
||||||
|
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/gevent/server.py", line 288, in _tcp_listener
|
||||||
|
sock.bind(address)
|
||||||
|
File "/home/wd/anaconda3/envs/aicheck_RODY/lib/python3.8/site-packages/gevent/_socketcommon.py", line 563, in bind
|
||||||
|
return self._sock.bind(address)
|
||||||
|
OSError: [Errno 98] Address already in use: ('192.168.0.20', 6914)
|
||||||
Loading…
Reference in New Issue
Block a user