urllib.error.URLError: <urlopen error [WinError 10061]，Loading pretrained weights from url Downloading

[monkeycc]

python tools/train.py --model cflow

2022-11-04 14:52:33,362 - anomalib.data - INFO - Loading the datamodule
2022-11-04 14:52:33,363 - anomalib.pre_processing.pre_process - WARNING - Transform configs has not been provided. Images will be normalized using ImageNet statistics.
2022-11-04 14:52:33,364 - anomalib.pre_processing.pre_process - WARNING - Transform configs has not been provided. Images will be normalized using ImageNet statistics.
2022-11-04 14:52:33,364 - anomalib.models - INFO - Loading the model.
2022-11-04 14:52:33,365 - anomalib.models.components.base.anomaly_module - INFO - Initializing CflowLightning model.
D:\anaconda3ok\envs\anomalib_env\lib\site-packages\torchmetrics\utilities\prints.py:36: UserWarning: Metric `PrecisionRecallCurve` will save all targets and predictions in buffer. For large datasets this may lead to large memory footprint.
  warnings.warn(*args, **kwargs)
2022-11-04 14:52:34,202 - timm.models.helpers - INFO - Loading pretrained weights from url (https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/wide_resnet50_racm-8234f177.pth)
Downloading: "https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/wide_resnet50_racm-8234f177.pth" to C:\Users\AI/.cache\torch\hub\checkpoints\wide_resnet50_racm-8234f177.pth
Traceback (most recent call last):
  File "D:\anaconda3ok\envs\anomalib_env\lib\urllib\request.py", line 1354, in do_open
    h.request(req.get_method(), req.selector, req.data, headers,
  File "D:\anaconda3ok\envs\anomalib_env\lib\http\client.py", line 1256, in request
    self._send_request(method, url, body, headers, encode_chunked)
  File "D:\anaconda3ok\envs\anomalib_env\lib\http\client.py", line 1302, in _send_request
    self.endheaders(body, encode_chunked=encode_chunked)
  File "D:\anaconda3ok\envs\anomalib_env\lib\http\client.py", line 1251, in endheaders
    self._send_output(message_body, encode_chunked=encode_chunked)
  File "D:\anaconda3ok\envs\anomalib_env\lib\http\client.py", line 1011, in _send_output
    self.send(msg)
  File "D:\anaconda3ok\envs\anomalib_env\lib\http\client.py", line 951, in send
    self.connect()
  File "D:\anaconda3ok\envs\anomalib_env\lib\http\client.py", line 1418, in connect
    super().connect()
  File "D:\anaconda3ok\envs\anomalib_env\lib\http\client.py", line 922, in connect
    self.sock = self._create_connection(
  File "D:\anaconda3ok\envs\anomalib_env\lib\socket.py", line 808, in create_connection
    raise err
  File "D:\anaconda3ok\envs\anomalib_env\lib\socket.py", line 796, in create_connection
    sock.connect(sa)
ConnectionRefusedError: [WinError 10061] 由于目标计算机积极拒绝，无法连接。

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "tools/train.py", line 71, in <module>
    train()
  File "tools/train.py", line 54, in train
    model = get_model(config)
  File "D:\anaconda3ok\envs\anomalib_env\lib\site-packages\anomalib\models\__init__.py", line 90, in get_model
    model = getattr(module, f"{_snake_to_pascal_case(config.model.name)}Lightning")(config)
  File "D:\anaconda3ok\envs\anomalib_env\lib\site-packages\anomalib\models\cflow\lightning_model.py", line 184, in __init__
    super().__init__(
  File "D:\anaconda3ok\envs\anomalib_env\lib\site-packages\anomalib\models\cflow\lightning_model.py", line 46, in __init__
    self.model: CflowModel = CflowModel(
  File "D:\anaconda3ok\envs\anomalib_env\lib\site-packages\anomalib\models\cflow\torch_model.py", line 41, in __init__
    self.encoder = FeatureExtractor(backbone=self.backbone, layers=self.pool_layers, pre_trained=pre_trained)
  File "D:\anaconda3ok\envs\anomalib_env\lib\site-packages\anomalib\models\components\feature_extractors\feature_extractor.py", line 43, in __init__
    self.feature_extractor = timm.create_model(
  File "D:\anaconda3ok\envs\anomalib_env\lib\site-packages\timm\models\factory.py", line 74, in create_model
    model = create_fn(pretrained=pretrained, **kwargs)
  File "D:\anaconda3ok\envs\anomalib_env\lib\site-packages\timm\models\resnet.py", line 876, in wide_resnet50_2
    return _create_resnet('wide_resnet50_2', pretrained, **model_args)
  File "D:\anaconda3ok\envs\anomalib_env\lib\site-packages\timm\models\resnet.py", line 694, in _create_resnet
    return build_model_with_cfg(
  File "D:\anaconda3ok\envs\anomalib_env\lib\site-packages\timm\models\helpers.py", line 465, in build_model_with_cfg
    load_pretrained(
  File "D:\anaconda3ok\envs\anomalib_env\lib\site-packages\timm\models\helpers.py", line 189, in load_pretrained
    state_dict = load_state_dict_from_url(pretrained_url, progress=progress, map_location='cpu')
  File "D:\anaconda3ok\envs\anomalib_env\lib\site-packages\torch\hub.py", line 727, in load_state_dict_from_url
    download_url_to_file(url, cached_file, hash_prefix, progress=progress)
  File "D:\anaconda3ok\envs\anomalib_env\lib\site-packages\torch\hub.py", line 593, in download_url_to_file
    u = urlopen(req)
  File "D:\anaconda3ok\envs\anomalib_env\lib\urllib\request.py", line 222, in urlopen
    return opener.open(url, data, timeout)
  File "D:\anaconda3ok\envs\anomalib_env\lib\urllib\request.py", line 525, in open
    response = self._open(req, data)
  File "D:\anaconda3ok\envs\anomalib_env\lib\urllib\request.py", line 542, in _open
    result = self._call_chain(self.handle_open, protocol, protocol +
  File "D:\anaconda3ok\envs\anomalib_env\lib\urllib\request.py", line 502, in _call_chain
    result = func(*args)
  File "D:\anaconda3ok\envs\anomalib_env\lib\urllib\request.py", line 1397, in https_open
    return self.do_open(http.client.HTTPSConnection, req,
  File "D:\anaconda3ok\envs\anomalib_env\lib\urllib\request.py", line 1357, in do_open
    raise URLError(err)
urllib.error.URLError: <urlopen error [WinError 10061] 由于目标计算机积极拒绝，无法连接。>

You can't visit github in China

Can. pth customize files ?

[samet-akcay]

@monkeycc, not sure if I understand the question. Looks like you cannot download the timm weights. Can you somehow manually download the weights?

[samet-akcay]

I'm converting this to a discussion and discuss it there.

[ashwinvaidya17]

@monkeycc With our new TorchFX feature extractor you can now pass path to the weights file. This way you can download the weights on your system and pass it to your model.

[kikyostudypython]

兄弟，可以给个联系方式吗，有些问题想请教你，关于异常检测这块

[monkeycc]

共同学习讨论 , QQ: 234539770

[kikyostudypython]

申请了