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lufficc / SSD

High quality, fast, modular reference implementation of SSD in PyTorch
MIT License
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how to use local .pth file, not to use model_urls like https://s3... to load weight file to train network #219

Open pistachio0812 opened 1 year ago

pistachio0812 commented 1 year ago

when i run train.py to train network, i meet this error: Downloading: "F:\ssd-v13\model_data\ssd_weights.pth" to C:\Users\zzh/.torch\models\ssd_weights.pth Traceback (most recent call last): File "train.py", line 128, in main() File "train.py", line 119, in main model = train(cfg, args) File "train.py", line 25, in train model = build_detection_model(cfg) File "F:\ssd-v13\ssd\modeling\detector__init.py", line 10, in build_detection_model return meta_arch(cfg) File "F:\ssd-v13\ssd\modeling\detector\ssd_detector.py", line 12, in init__ self.backbone = build_backbone(cfg) File "F:\ssd-v13\ssd\modeling\backbone__init__.py", line 13, in build_backbone return registry.BACKBONES[cfg.MODEL.BACKBONE.NAME](cfg, cfg.MODEL.BACKBONE.PRETRAINED) File "F:\ssd-v13\ssd\modeling\backbone\frassd_net\frassd_net.py", line 160, in frassd_net model.init_from_pretrain(load_state_dict_from_url(model_urls['ssdv1'])) File "F:\ssd-v13\ssd\utils\model_zoo.py", line 61, in load_state_dict_from_url cached_file = cache_url(url) File "F:\ssd-v13\ssd\utils\model_zoo.py", line 55, in cache_url download_url_to_file(url, cached_file, hash_prefix, progress=progress) File "D:\anaconda\envs\pytorch-gpu\lib\site-packages\torch\hub.py", line 437, in download_url_to_file u = urlopen(req) File "D:\anaconda\envs\pytorch-gpu\lib\urllib\request.py", line 222, in urlopen return opener.open(url, data, timeout) File "D:\anaconda\envs\pytorch-gpu\lib\urllib\request.py", line 525, in open response = self._open(req, data) File "D:\anaconda\envs\pytorch-gpu\lib\urllib\request.py", line 547, in _open return self._call_chain(self.handle_open, 'unknown', File "D:\anaconda\envs\pytorch-gpu\lib\urllib\request.py", line 502, in _call_chain result = func(*args) File "D:\anaconda\envs\pytorch-gpu\lib\urllib\request.py", line 1425, in unknown_open raise URLError('unknown url type: %s' % type) urllib.error.URLError:

train.py: model_urls ={ 'vgg': 'https://s3.amazonaws.com/amdegroot-models/vgg16_reducedfc.pth', 'ssdv1': 'F:\ssd-v13\model_data\ssd_weights.pth', 'ssd300_voc0712': '../model_data/vgg_ssd300_voc0712.pth', 'ssd300_coco2014': '../model_data/vgg_ssd300_coco_trainval35k.pth', 'ssd512_voc0712': '../model_data/vgg_ssd512_voc0712.pth', 'ssd512_coco2014': '../model_data/vgg_ssd512_coco_trainval35k.pth', }

@registry.BACKBONES.register('my_net') def my_net(cfg, pretrained=True): model = MY_NET(cfg) if pretrained: model.init_from_pretrain(load_state_dict_from_url(model_urls['ssdv1'])) return model

how to solove it, thanks!!!!

ksv87 commented 1 month ago

try this

@registry.BACKBONES.register('my_net')
def my_net(cfg, pretrained=True):
    model = MY_NET(cfg)
    if pretrained:
        if model_urls['ssdv1'].startswith("http"):
            model.init_from_pretrain(load_state_dict_from_url(model_urls['ssdv1']))
        else:
            model.load_state_dict(torch.load(model_urls['ssdv1']), strict=False)
    return model