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yassouali / pytorch-segmentation

:art: Semantic segmentation models, datasets and losses implemented in PyTorch.
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Fail to use SegNet, UperNet, GCN for training (already successful with PSPNet and ENet) #39

Closed ustcychu closed 4 years ago

ustcychu commented 4 years ago

Hello, I have already trained a model with PSPNet and ADE20K dataset, now I want to turn to other models like SegNet. But I got the error as follows, I have only changed the 'name' and 'arch/type' in the config.json from 'PSPNet' to 'SegNet'(same for UperNet and GCN), so could you please help me with that?

My config.json:

{ "name": "SegNet", "n_gpu": 2, "use_synch_bn": true,

"arch": {
    "type": "SegNet",
    "args": {
        "backbone": "resnet50",
        "freeze_bn": false,
        "freeze_backbone": false
    }
},

"train_loader": {
    "type": "ADE20K",
    "args":{
        "data_dir": "data/ADEChallengeData2016",
        "batch_size": 8,
        "base_size": 400,
        "crop_size": 380,
        "augment": true,
        "shuffle": true,
        "scale": true,
        "flip": true,
        "rotate": true,
        "blur": false,
        "split": "training",
        "num_workers": 8
    }
},

"val_loader": {
    "type": "ADE20K",
    "args":{
        "data_dir": "data/ADEChallengeData2016",
        "batch_size": 8,
        "crop_size": 480,
        "val": true,
        "split": "validation",
        "num_workers": 4
    }
},

"optimizer": {
    "type": "SGD",
    "differential_lr": true,
    "args":{
        "lr": 0.01,
        "weight_decay": 1e-4,
        "momentum": 0.9
    }
},

"loss": "CrossEntropyLoss2d",
"ignore_index": -1,
"lr_scheduler": {
    "type": "Poly",
    "args": {}
},

"trainer": {
    "epochs": 40,
    "save_dir": "saved/",
    "save_period": 10,

    "monitor": "max Mean_IoU",
    "early_stop": 10,

    "tensorboard": true,
    "log_dir": "saved/runs",
    "log_per_iter": 20,

    "val": true,
    "val_per_epochs": 5
}

}

Error:

/home/notegeek/anaconda3/envs/semantic/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_qint8 = np.dtype([("qint8", np.int8, 1)]) /home/notegeek/anaconda3/envs/semantic/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_quint8 = np.dtype([("quint8", np.uint8, 1)]) /home/notegeek/anaconda3/envs/semantic/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_qint16 = np.dtype([("qint16", np.int16, 1)]) /home/notegeek/anaconda3/envs/semantic/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_quint16 = np.dtype([("quint16", np.uint16, 1)]) /home/notegeek/anaconda3/envs/semantic/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. _np_qint32 = np.dtype([("qint32", np.int32, 1)]) /home/notegeek/anaconda3/envs/semantic/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'. np_resource = np.dtype([("resource", np.ubyte, 1)]) Downloading: "https://download.pytorch.org/models/vgg16_bn-6c64b313.pth" to /home/notegeek/.cache/torch/checkpoints/vgg16_bn-6c64b313.pth Traceback (most recent call last): File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/urllib/request.py", line 1318, in do_open encode_chunked=req.has_header('Transfer-encoding')) File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/http/client.py", line 1254, in request self._send_request(method, url, body, headers, encode_chunked) File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/http/client.py", line 1300, in _send_request self.endheaders(body, encode_chunked=encode_chunked) File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/http/client.py", line 1249, in endheaders self._send_output(message_body, encode_chunked=encode_chunked) File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/http/client.py", line 1036, in _send_output self.send(msg) File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/http/client.py", line 974, in send self.connect() File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/http/client.py", line 1415, in connect server_hostname=server_hostname) File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/ssl.py", line 407, in wrap_socket _context=self, _session=session) File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/ssl.py", line 817, in init self.do_handshake() File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/ssl.py", line 1077, in do_handshake self._sslobj.do_handshake() File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/ssl.py", line 689, in do_handshake self._sslobj.do_handshake() ssl.SSLError: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed (_ssl.c:852)

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "train.py", line 61, in main(config, args.resume) File "train.py", line 26, in main model = get_instance(models, 'arch', config, train_loader.dataset.num_classes) File "train.py", line 16, in get_instance return getattr(module, config[name]['type'])(args, config[name]['args']) File "/home/notegeek/pytorch_segmentation/models/segnet.py", line 12, in init vgg_bn = models.vgg16_bn(pretrained= pretrained) File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/site-packages/torchvision/models/vgg.py", line 154, in vgg16_bn return _vgg('vgg16_bn', 'D', True, pretrained, progress, kwargs) File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/site-packages/torchvision/models/vgg.py", line 92, in _vgg progress=progress) File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/site-packages/torch/hub.py", line 433, in load_state_dict_from_url _download_url_to_file(url, cached_file, hash_prefix, progress=progress) File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/site-packages/torch/hub.py", line 349, in _download_url_to_file u = urlopen(url) File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/urllib/request.py", line 223, in urlopen return opener.open(url, data, timeout) File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/urllib/request.py", line 526, in open response = self._open(req, data) File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/urllib/request.py", line 544, in _open '_open', req) File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/urllib/request.py", line 504, in _call_chain result = func(args) File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/urllib/request.py", line 1361, in https_open context=self._context, check_hostname=self._check_hostname) File "/home/notegeek/anaconda3/envs/semantic/lib/python3.6/urllib/request.py", line 1320, in do_open raise URLError(err) urllib.error.URLError: <urlopen error [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed (_ssl.c:852)>

yassouali commented 4 years ago

Just tested it, worked without any problem. You have a problem with our SSL certificate when downloading the pytorch pretrained models (VGG in this case).

Here is a possible solution https://github.com/pytorch/pytorch/issues/2271