Merge branch 'master' of https://gitea.star-rising.cn/xkrs_manan/RODY
This commit is contained in:
commit
066fb720bc
@ -8,8 +8,8 @@ DEBUG = True
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SECRET_KEY = 'WugjsfiYBEVsiQfiSwEbIOEAGnOIFYqoOYHEIK'
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# 数据库配置
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# SQLALCHEMY_DATABASE_URI = 'postgresql+psycopg2://deepLearner:dp2021@124.71.203.3:5432/demo'
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SQLALCHEMY_DATABASE_URI = 'mysql+pymysql://demo:demo123@192.168.2.9:3306/flask_demo'
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SQLALCHEMY_DATABASE_URI = 'postgresql+psycopg2://deepLearner:dp2021@124.71.203.3:5432/demo'
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#SQLALCHEMY_DATABASE_URI = 'mysql+pymysql://demo:demo123@192.168.2.9:3306/flask_demo'
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SQLALCHEMY_TRACK_MODIFICATIONS = False
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# 查询时会显示原始SQL语句
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SQLALCHEMY_ECHO = True
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@ -21,7 +21,7 @@ SQLALCHEMY_ECHO = True
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db = {
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'host': '127.0.0.1',
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'user': 'root',
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'password': '',
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'password': 'sdust2020',
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'port': 6379,
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'database': 'school',
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'charset': 'utf8',
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@ -10,7 +10,7 @@ from flask_sockets import Sockets
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import sys
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sys.path.append("/mnt/sdc/algorithm/AICheck-MaskRCNN")
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sys.path.append("/mnt/sdc/algorithm/R-ODY")
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# sys.path.append('E:/alg_demo-master/alg_demo/app/yolov5')
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from app.core.common_utils import logger
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from app.core.err_handler import page_not_found, method_not_allowed, exception_500, exception_400
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@ -130,5 +130,5 @@ if __name__ == '__main__':
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from geventwebsocket.handler import WebSocketHandler
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#8080 6913 '192.168.0.20'
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server = pywsgi.WSGIServer(('192.168.2.118', 6914), app, handler_class=WebSocketHandler)
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server = pywsgi.WSGIServer(('192.168.0.20', 6914), app, handler_class=WebSocketHandler)
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server.serve_forever()
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@ -5,7 +5,7 @@ import sys
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import redis
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from ..configs import default
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from configs import default
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class RedisCli(object):
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@ -1,8 +1,6 @@
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"""
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@Time ： 2022/10/12 17:55
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@Auth ： 东
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@File ：websocket_tool.py
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@IDE ：PyCharm
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@Motto：ABC(Always Be Coding)
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@Desc：
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@ -1,7 +1,9 @@
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path: null
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train: E:/aicheck/data_set/11442136178662604800/trained/images/train/
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val: E:/aicheck/data_set/11442136178662604800/trained/images/val/
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train: /mnt/sdc/aicheck/IntelligentizeAI/data_set/193120735164768256/trained/images/train/
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val: /mnt/sdc/aicheck/IntelligentizeAI/data_set/193120735164768256/trained/images/val/
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test: null
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names:
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0: hole
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1: '456'
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2: dog
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3: cat
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387
nohup.out
387
nohup.out
@ -1,338 +1,51 @@
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nohup: ignoring input
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[37m[INFO][0m select pg_catalog.version() ([1mbase.py[0m:1853)
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[37m[INFO][0m [raw sql] {} ([1mbase.py[0m:1858)
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[37m[INFO][0m select current_schema() ([1mbase.py[0m:1853)
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[37m[INFO][0m [raw sql] {} ([1mbase.py[0m:1858)
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[37m[INFO][0m show standard_conforming_strings ([1mbase.py[0m:1853)
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[37m[INFO][0m [raw sql] {} ([1mbase.py[0m:1858)
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[37m[INFO][0m BEGIN (implicit) ([1mbase.py[0m:1027)
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[37m[INFO][0m select relname from pg_class c join pg_namespace n on n.oid=c.relnamespace where pg_catalog.pg_table_is_visible(c.oid) and relname=%(name)s ([1mbase.py[0m:1853)
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[37m[INFO][0m [generated in 0.00012s] {'name': 'sys_user'} ([1mbase.py[0m:1858)
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[37m[INFO][0m select relname from pg_class c join pg_namespace n on n.oid=c.relnamespace where pg_catalog.pg_table_is_visible(c.oid) and relname=%(name)s ([1mbase.py[0m:1853)
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[37m[INFO][0m [cached since 0.00606s ago] {'name': 'sys_role'} ([1mbase.py[0m:1858)
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[37m[INFO][0m select relname from pg_class c join pg_namespace n on n.oid=c.relnamespace where pg_catalog.pg_table_is_visible(c.oid) and relname=%(name)s ([1mbase.py[0m:1853)
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[37m[INFO][0m [cached since 0.009177s ago] {'name': 'rel_user_role'} ([1mbase.py[0m:1858)
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[37m[INFO][0m COMMIT ([1mbase.py[0m:1087)
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[33m[WARNING][0m This script is aimed to demonstrate how to convert theJSON file to a single image dataset, and not to handlemultiple JSON files to generate a real-use dataset. ([1mlabelme2VOCSeg_aicheckFrom.py[0m:101)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
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warnings.warn(
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/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=None`.
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warnings.warn(msg)
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/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained_backbone' is deprecated since 0.13 and may be removed in the future, please use 'weights_backbone' instead.
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warnings.warn(
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/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights_backbone' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights_backbone=None`.
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warnings.warn(msg)
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Exception in thread Thread-1:
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Traceback (most recent call last):
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File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/threading.py", line 932, in _bootstrap_inner
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self.run()
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File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/threading.py", line 870, in run
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self._target(*self._args, **self._kwargs)
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File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/controller/AlgorithmController.py", line 207, in main
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train_tesk.StarTrain()
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File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/train.py", line 180, in StarTrain
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_loop()
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File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/controller/AlgorithmController.py", line 112, in wrapped_function
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data = func(*args, **kwargs)
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File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/train.py", line 159, in _loop
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self.train_one_epoch(model, optimizer, data_loader, device, epoch, print_freq=10)
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File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/train.py", line 73, in train_one_epoch
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for images, targets in metric_logger.log_every(data_loader, print_freq, header):
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File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/utilss.py", line 171, in log_every
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for obj in iterable:
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File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 628, in __next__
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data = self._next_data()
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File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 671, in _next_data
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data = self._dataset_fetcher.fetch(index) # may raise StopIteration
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File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 58, in fetch
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data = [self.dataset[idx] for idx in possibly_batched_index]
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File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 58, in <listcomp>
|
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data = [self.dataset[idx] for idx in possibly_batched_index]
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File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/Dataset.py", line 58, in __getitem__
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area = (boxes[:, 3] - boxes[:, 1]) * (boxes[:, 2] - boxes[:, 0])
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IndexError: too many indices for tensor of dimension 1
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[33m[WARNING][0m This script is aimed to demonstrate how to convert theJSON file to a single image dataset, and not to handlemultiple JSON files to generate a real-use dataset. ([1mlabelme2VOCSeg_aicheckFrom.py[0m:101)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
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[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
Exception in thread Thread-2:
|
||||
Traceback (most recent call last):
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/threading.py", line 932, in _bootstrap_inner
|
||||
self.run()
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/threading.py", line 870, in run
|
||||
self._target(*self._args, **self._kwargs)
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/controller/AlgorithmController.py", line 207, in main
|
||||
train_tesk.StarTrain()
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/train.py", line 180, in StarTrain
|
||||
_loop()
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/controller/AlgorithmController.py", line 112, in wrapped_function
|
||||
data = func(*args, **kwargs)
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/train.py", line 159, in _loop
|
||||
self.train_one_epoch(model, optimizer, data_loader, device, epoch, print_freq=10)
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/train.py", line 73, in train_one_epoch
|
||||
for images, targets in metric_logger.log_every(data_loader, print_freq, header):
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/utilss.py", line 171, in log_every
|
||||
for obj in iterable:
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 628, in __next__
|
||||
data = self._next_data()
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 671, in _next_data
|
||||
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 58, in fetch
|
||||
data = [self.dataset[idx] for idx in possibly_batched_index]
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 58, in <listcomp>
|
||||
data = [self.dataset[idx] for idx in possibly_batched_index]
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/Dataset.py", line 58, in __getitem__
|
||||
area = (boxes[:, 3] - boxes[:, 1]) * (boxes[:, 2] - boxes[:, 0])
|
||||
IndexError: too many indices for tensor of dimension 1
|
||||
[33m[WARNING][0m This script is aimed to demonstrate how to convert theJSON file to a single image dataset, and not to handlemultiple JSON files to generate a real-use dataset. ([1mlabelme2VOCSeg_aicheckFrom.py[0m:101)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
Exception in thread Thread-3:
|
||||
Traceback (most recent call last):
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/threading.py", line 932, in _bootstrap_inner
|
||||
self.run()
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/threading.py", line 870, in run
|
||||
self._target(*self._args, **self._kwargs)
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/controller/AlgorithmController.py", line 207, in main
|
||||
train_tesk.StarTrain()
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/train.py", line 180, in StarTrain
|
||||
_loop()
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/controller/AlgorithmController.py", line 112, in wrapped_function
|
||||
data = func(*args, **kwargs)
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/train.py", line 159, in _loop
|
||||
self.train_one_epoch(model, optimizer, data_loader, device, epoch, print_freq=10)
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/train.py", line 73, in train_one_epoch
|
||||
for images, targets in metric_logger.log_every(data_loader, print_freq, header):
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/utilss.py", line 171, in log_every
|
||||
for obj in iterable:
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 628, in __next__
|
||||
data = self._next_data()
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 671, in _next_data
|
||||
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 58, in fetch
|
||||
data = [self.dataset[idx] for idx in possibly_batched_index]
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 58, in <listcomp>
|
||||
data = [self.dataset[idx] for idx in possibly_batched_index]
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/Dataset.py", line 58, in __getitem__
|
||||
area = (boxes[:, 3] - boxes[:, 1]) * (boxes[:, 2] - boxes[:, 0])
|
||||
IndexError: too many indices for tensor of dimension 1
|
||||
[33m[WARNING][0m This script is aimed to demonstrate how to convert theJSON file to a single image dataset, and not to handlemultiple JSON files to generate a real-use dataset. ([1mlabelme2VOCSeg_aicheckFrom.py[0m:101)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
Exception in thread Thread-4:
|
||||
Traceback (most recent call last):
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/threading.py", line 932, in _bootstrap_inner
|
||||
self.run()
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/threading.py", line 870, in run
|
||||
self._target(*self._args, **self._kwargs)
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/controller/AlgorithmController.py", line 207, in main
|
||||
train_tesk.StarTrain()
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/train.py", line 180, in StarTrain
|
||||
_loop()
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/controller/AlgorithmController.py", line 112, in wrapped_function
|
||||
data = func(*args, **kwargs)
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/train.py", line 159, in _loop
|
||||
self.train_one_epoch(model, optimizer, data_loader, device, epoch, print_freq=10)
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/train.py", line 73, in train_one_epoch
|
||||
for images, targets in metric_logger.log_every(data_loader, print_freq, header):
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/utilss.py", line 171, in log_every
|
||||
for obj in iterable:
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 628, in __next__
|
||||
data = self._next_data()
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 671, in _next_data
|
||||
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 58, in fetch
|
||||
data = [self.dataset[idx] for idx in possibly_batched_index]
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 58, in <listcomp>
|
||||
data = [self.dataset[idx] for idx in possibly_batched_index]
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/Dataset.py", line 58, in __getitem__
|
||||
area = (boxes[:, 3] - boxes[:, 1]) * (boxes[:, 2] - boxes[:, 0])
|
||||
IndexError: too many indices for tensor of dimension 1
|
||||
[33m[WARNING][0m This script is aimed to demonstrate how to convert theJSON file to a single image dataset, and not to handlemultiple JSON files to generate a real-use dataset. ([1mlabelme2VOCSeg_aicheckFrom.py[0m:101)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
CUDA is available!
|
||||
cuda
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_26.json
|
||||
Polygon must have points more than 2
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_5.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_38.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_23.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_46.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_17.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_14.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_30.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_42.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_22.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_13.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_11.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_51.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_0.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_27.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_8.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_1.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_4.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_10.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_12.json
|
||||
None
|
||||
cuda
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_26.json
|
||||
Polygon must have points more than 2
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_5.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_38.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_23.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_46.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_17.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_14.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_30.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_42.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_22.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_13.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_11.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_51.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_0.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_27.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_8.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_1.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_4.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_10.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_12.json
|
||||
cuda
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/masks
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_5.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_38.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_23.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_46.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_17.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_14.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_30.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_42.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_22.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_13.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_11.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_51.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_0.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_27.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_8.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_1.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_4.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_10.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182075175733436416/ori/labels/tucengbuliang_a_12.json
|
||||
cuda
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/labels/tucengbuliang_a_5.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/labels/tucengbuliang_a_23.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/labels/tucengbuliang_a_46.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/labels/tucengbuliang_a_14.json
|
||||
Polygon must have points more than 2
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/labels/tucengbuliang_a_55.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/labels/tucengbuliang_a_30.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/labels/tucengbuliang_a_77.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/labels/tucengbuliang_a_67.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/labels/tucengbuliang_a_11.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/labels/tucengbuliang_a_0.json
|
||||
cuda
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/labels/tucengbuliang_a_5.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/labels/tucengbuliang_a_23.json
|
||||
/mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/labels/tucengbuliang_a_46.json
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
[37m[INFO][0m Saved to: /mnt/sdc/IntelligentizeAI/IntelligentizeAI/data_set/182423143779016704/ori/masks ([1mlabelme2VOCSeg_aicheckFrom.py[0m:97)
|
||||
Exception in thread Thread-5:
|
||||
Traceback (most recent call last):
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/threading.py", line 932, in _bootstrap_inner
|
||||
self.run()
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/threading.py", line 870, in run
|
||||
self._target(*self._args, **self._kwargs)
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/controller/AlgorithmController.py", line 207, in main
|
||||
train_tesk.StarTrain()
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/train.py", line 180, in StarTrain
|
||||
_loop()
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/controller/AlgorithmController.py", line 112, in wrapped_function
|
||||
data = func(*args, **kwargs)
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/train.py", line 159, in _loop
|
||||
self.train_one_epoch(model, optimizer, data_loader, device, epoch, print_freq=10)
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/train.py", line 73, in train_one_epoch
|
||||
for images, targets in metric_logger.log_every(data_loader, print_freq, header):
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/utilss.py", line 171, in log_every
|
||||
for obj in iterable:
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 628, in __next__
|
||||
data = self._next_data()
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 671, in _next_data
|
||||
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 58, in fetch
|
||||
data = [self.dataset[idx] for idx in possibly_batched_index]
|
||||
File "/home/wd/anaconda3/envs/aicheck_maskrcnn/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 58, in <listcomp>
|
||||
data = [self.dataset[idx] for idx in possibly_batched_index]
|
||||
File "/mnt/sdc/algorithm/AICheck-MaskRCNN/app/maskrcnn/Dataset.py", line 58, in __getitem__
|
||||
area = (boxes[:, 3] - boxes[:, 1]) * (boxes[:, 2] - boxes[:, 0])
|
||||
IndexError: too many indices for tensor of dimension 1
|
||||
2022-11-24 08:58:34,262 INFO sqlalchemy.engine.Engine select pg_catalog.version()
|
||||
2022-11-24 08:58:34,262 INFO sqlalchemy.engine.Engine [raw sql] {}
|
||||
2022-11-24 08:58:34,267 INFO sqlalchemy.engine.Engine select current_schema()
|
||||
2022-11-24 08:58:34,267 INFO sqlalchemy.engine.Engine [raw sql] {}
|
||||
2022-11-24 08:58:34,272 INFO sqlalchemy.engine.Engine show standard_conforming_strings
|
||||
2022-11-24 08:58:34,272 INFO sqlalchemy.engine.Engine [raw sql] {}
|
||||
2022-11-24 08:58:34,277 INFO sqlalchemy.engine.Engine BEGIN (implicit)
|
||||
2022-11-24 08:58:34,277 INFO sqlalchemy.engine.Engine COMMIT
|
||||
[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']
|
||||
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
|
||||
|
||||
[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[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[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)
|
||||
|
||||
Export complete (6.5s)
|
||||
Results saved to [1m/mnt/sdc/aicheck/IntelligentizeAI/data_set/weights[0m
|
||||
Detect: python detect.py --weights /mnt/sdc/aicheck/IntelligentizeAI/data_set/weights/ces2_193120735164768256_R-ODY_2_640.onnx
|
||||
Validate: python val.py --weights /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/aicheck/IntelligentizeAI/data_set/weights/ces2_193120735164768256_R-ODY_2_640.onnx')
|
||||
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
|
||||
[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']
|
||||
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
|
||||
|
||||
[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[1mTorchScript:[0m starting export with torch 1.8.0+cu111...
|
||||
[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)
|
||||
|
||||
[34m[1mONNX:[0m starting export with onnx 1.12.0...
|
||||
[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)
|
||||
|
||||
Export complete (2.6s)
|
||||
Results saved to [1m/mnt/sdc/aicheck/IntelligentizeAI/data_set/weights[0m
|
||||
Detect: python detect.py --weights /mnt/sdc/aicheck/IntelligentizeAI/data_set/weights/ces2_193120735164768256_R-ODY_2_640.onnx
|
||||
Validate: python val.py --weights /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/aicheck/IntelligentizeAI/data_set/weights/ces2_193120735164768256_R-ODY_2_640.onnx')
|
||||
Visualize: https://netron.app
|
||||
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
|
||||
|
||||
@ -78,7 +78,7 @@ zipp==3.8.1
|
||||
zope.event==4.5.0
|
||||
zope.interface==5.5.0
|
||||
|
||||
torch>=1.8.0+cu111
|
||||
torch==1.8.0
|
||||
wandb>=0.12.10
|
||||
tqdm>=4.64.0
|
||||
opencv-python>=4.5.5.62
|
||||
@ -86,6 +86,6 @@ matplotlib>=3.2.2
|
||||
pandas>=1.4.3
|
||||
seaborn>=0.11.2
|
||||
pillow>=9.0.1
|
||||
torchvision>=0.9.0+cu111
|
||||
torchvision==0.9.0
|
||||
requests>=2.27.1
|
||||
thop>=0.1.1-2209072238
|
||||
28
start.sh
Executable file
28
start.sh
Executable file
@ -0,0 +1,28 @@
|
||||
#!/bin/sh
|
||||
RESOURCE_NAME=app/run.py
|
||||
|
||||
tpid=`ps -ef|grep $RESOURCE_NAME|grep -v grep|grep -v kill|awk '{print $2}'`
|
||||
if [ ${tpid} ]; then
|
||||
echo 'Stop Process...'
|
||||
kill -15 $tpid
|
||||
fi
|
||||
sleep 5
|
||||
tpid=`ps -ef|grep $RESOURCE_NAME|grep -v grep|grep -v kill|awk '{print $2}'`
|
||||
if [ ${tpid} ]; then
|
||||
echo 'Kill Process!'
|
||||
kill -9 $tpid
|
||||
else
|
||||
echo 'Stop Success!'
|
||||
fi
|
||||
|
||||
tpid=`ps -ef|grep $RESOURCE_NAME|grep -v grep|grep -v kill|awk '{print $2}'`
|
||||
if [ ${tpid} ]; then
|
||||
echo 'App is running.'
|
||||
else
|
||||
echo 'App is NOT running.'
|
||||
fi
|
||||
|
||||
rm -f tpid
|
||||
nohup python ./$RESOURCE_NAME > nohup.out 2>&1 &
|
||||
echo $! > tpid
|
||||
echo Start Success!
|
||||
Loading…
x
Reference in New Issue
Block a user