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Python vgg.model_urls方法代碼示例

本文整理匯總了Python中torchvision.models.vgg.model_urls方法的典型用法代碼示例。如果您正苦於以下問題：Python vgg.model_urls方法的具體用法？Python vgg.model_urls怎麽用？Python vgg.model_urls使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類torchvision.models.vgg的用法示例。

在下文中一共展示了vgg.model_urls方法的15個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。

示例1: load_base_weights

# 需要導入模塊: from torchvision.models import vgg [as 別名]
# 或者: from torchvision.models.vgg import model_urls [as 別名]
def load_base_weights(self):
        """This is complicated because we converted the base model to be fully
        convolutional, so some surgery needs to happen here."""
        base_state_dict = model_zoo.load_url(vgg.model_urls['vgg16'])
        vgg_state_dict = {k[len('features.'):]: v
                          for k, v in base_state_dict.items()
                          if k.startswith('features.')}
        self.vgg.load_state_dict(vgg_state_dict)
        vgg_head_params = self.vgg_head.parameters()
        for k, v in base_state_dict.items():
            if not k.startswith('classifier.'):
                continue
            if k.startswith('classifier.6.'):
                # skip final classifier output
                continue
            vgg_head_param = next(vgg_head_params)
            vgg_head_param.data = v.view(vgg_head_param.size())

開發者ID:jhoffman，項目名稱:cycada_release，代碼行數:19，代碼來源:fcn8s.py

示例2: load_base_weights

# 需要導入模塊: from torchvision.models import vgg [as 別名]
# 或者: from torchvision.models.vgg import model_urls [as 別名]
def load_base_weights(self):
		"""This is complicated because we converted the base model to be fully
		convolutional, so some surgery needs to happen here."""
		base_state_dict = model_zoo.load_url(vgg.model_urls['vgg16'])
		vgg_state_dict = {k[len('features.'):]: v
		                  for k, v in base_state_dict.items()
		                  if k.startswith('features.')}
		self.vgg.load_state_dict(vgg_state_dict)
		vgg_head_params = self.vgg_head.parameters()
		for k, v in base_state_dict.items():
			if not k.startswith('classifier.'):
				continue
			if k.startswith('classifier.6.'):
				# skip final classifier output
				continue
			vgg_head_param = next(vgg_head_params)
			vgg_head_param.data = v.view(vgg_head_param.size())

開發者ID:Luodian，項目名稱:MADAN，代碼行數:19，代碼來源:fcn8s.py

示例3: vgg11

# 需要導入模塊: from torchvision.models import vgg [as 別名]
# 或者: from torchvision.models.vgg import model_urls [as 別名]
def vgg11(config_channels, anchors, num_cls):
    model = VGG(config_channels, anchors, num_cls, make_layers(config_channels, cfg['A']))
    if config_channels.config.getboolean('model', 'pretrained'):
        url = model_urls['vgg11']
        logging.info('use pretrained model: ' + url)
        state_dict = model.state_dict()
        for key, value in model_zoo.load_url(url).items():
            if key in state_dict:
                state_dict[key] = value
        model.load_state_dict(state_dict)
    return model

開發者ID:ruiminshen，項目名稱:yolo2-pytorch，代碼行數:13，代碼來源:vgg.py

示例4: vgg11_bn

# 需要導入模塊: from torchvision.models import vgg [as 別名]
# 或者: from torchvision.models.vgg import model_urls [as 別名]
def vgg11_bn(config_channels, anchors, num_cls):
    model = VGG(config_channels, anchors, num_cls, make_layers(config_channels, cfg['A'], batch_norm=True))
    if config_channels.config.getboolean('model', 'pretrained'):
        url = model_urls['vgg11_bn']
        logging.info('use pretrained model: ' + url)
        state_dict = model.state_dict()
        for key, value in model_zoo.load_url(url).items():
            if key in state_dict:
                state_dict[key] = value
        model.load_state_dict(state_dict)
    return model

開發者ID:ruiminshen，項目名稱:yolo2-pytorch，代碼行數:13，代碼來源:vgg.py

示例5: vgg13

# 需要導入模塊: from torchvision.models import vgg [as 別名]
# 或者: from torchvision.models.vgg import model_urls [as 別名]
def vgg13(config_channels, anchors, num_cls):
    model = VGG(config_channels, anchors, num_cls, make_layers(config_channels, cfg['B']))
    if config_channels.config.getboolean('model', 'pretrained'):
        url = model_urls['vgg13']
        logging.info('use pretrained model: ' + url)
        state_dict = model.state_dict()
        for key, value in model_zoo.load_url(url).items():
            if key in state_dict:
                state_dict[key] = value
        model.load_state_dict(state_dict)
    return model

開發者ID:ruiminshen，項目名稱:yolo2-pytorch，代碼行數:13，代碼來源:vgg.py

示例6: vgg13_bn

# 需要導入模塊: from torchvision.models import vgg [as 別名]
# 或者: from torchvision.models.vgg import model_urls [as 別名]
def vgg13_bn(config_channels, anchors, num_cls):
    model = VGG(config_channels, anchors, num_cls, make_layers(config_channels, cfg['B'], batch_norm=True))
    if config_channels.config.getboolean('model', 'pretrained'):
        url = model_urls['vgg13_bn']
        logging.info('use pretrained model: ' + url)
        state_dict = model.state_dict()
        for key, value in model_zoo.load_url(url).items():
            if key in state_dict:
                state_dict[key] = value
        model.load_state_dict(state_dict)
    return model

開發者ID:ruiminshen，項目名稱:yolo2-pytorch，代碼行數:13，代碼來源:vgg.py

示例7: vgg16

# 需要導入模塊: from torchvision.models import vgg [as 別名]
# 或者: from torchvision.models.vgg import model_urls [as 別名]
def vgg16(config_channels, anchors, num_cls):
    model = VGG(config_channels, anchors, num_cls, make_layers(config_channels, cfg['D']))
    if config_channels.config.getboolean('model', 'pretrained'):
        url = model_urls['vgg16']
        logging.info('use pretrained model: ' + url)
        state_dict = model.state_dict()
        for key, value in model_zoo.load_url(url).items():
            if key in state_dict:
                state_dict[key] = value
        model.load_state_dict(state_dict)
    return model

開發者ID:ruiminshen，項目名稱:yolo2-pytorch，代碼行數:13，代碼來源:vgg.py

示例8: vgg19

# 需要導入模塊: from torchvision.models import vgg [as 別名]
# 或者: from torchvision.models.vgg import model_urls [as 別名]
def vgg19(config_channels, anchors, num_cls):
    model = VGG(config_channels, anchors, num_cls, make_layers(config_channels, cfg['E']))
    if config_channels.config.getboolean('model', 'pretrained'):
        url = model_urls['vgg19']
        logging.info('use pretrained model: ' + url)
        state_dict = model.state_dict()
        for key, value in model_zoo.load_url(url).items():
            if key in state_dict:
                state_dict[key] = value
        model.load_state_dict(state_dict)
    return model

開發者ID:ruiminshen，項目名稱:yolo2-pytorch，代碼行數:13，代碼來源:vgg.py

示例9: vgg19_bn

# 需要導入模塊: from torchvision.models import vgg [as 別名]
# 或者: from torchvision.models.vgg import model_urls [as 別名]
def vgg19_bn(config_channels, anchors, num_cls):
    model = VGG(config_channels, anchors, num_cls, make_layers(config_channels, cfg['E'], batch_norm=True))
    if config_channels.config.getboolean('model', 'pretrained'):
        url = model_urls['vgg19_bn']
        logging.info('use pretrained model: ' + url)
        state_dict = model.state_dict()
        for key, value in model_zoo.load_url(url).items():
            if key in state_dict:
                state_dict[key] = value
        model.load_state_dict(state_dict)
    return model

開發者ID:ruiminshen，項目名稱:yolo2-pytorch，代碼行數:13，代碼來源:vgg.py

示例10: init

# 需要導入模塊: from torchvision.models import vgg [as 別名]
# 或者: from torchvision.models.vgg import model_urls [as 別名]
def __init__(self, pretrained=True, freeze=True):
        super(vgg16_bn, self).__init__()
        model_urls['vgg16_bn'] = model_urls['vgg16_bn'].replace('https://', 'http://')
        vgg_pretrained_features = models.vgg16_bn(pretrained=pretrained).features
        self.slice1 = torch.nn.Sequential()
        self.slice2 = torch.nn.Sequential()
        self.slice3 = torch.nn.Sequential()
        self.slice4 = torch.nn.Sequential()
        self.slice5 = torch.nn.Sequential()
        for x in range(12):         # conv2_2
            self.slice1.add_module(str(x), vgg_pretrained_features[x])
        for x in range(12, 19):         # conv3_3
            self.slice2.add_module(str(x), vgg_pretrained_features[x])
        for x in range(19, 29):         # conv4_3
            self.slice3.add_module(str(x), vgg_pretrained_features[x])
        for x in range(29, 39):         # conv5_3
            self.slice4.add_module(str(x), vgg_pretrained_features[x])

        # fc6, fc7 without atrous conv
        self.slice5 = torch.nn.Sequential(
                nn.MaxPool2d(kernel_size=3, stride=1, padding=1),
                nn.Conv2d(512, 1024, kernel_size=3, padding=6, dilation=6),
                nn.Conv2d(1024, 1024, kernel_size=1)
        )

        if not pretrained:
            init_weights(self.slice1.modules())
            init_weights(self.slice2.modules())
            init_weights(self.slice3.modules())
            init_weights(self.slice4.modules())

        init_weights(self.slice5.modules())        # no pretrained model for fc6 and fc7

        if freeze:
            for param in self.slice1.parameters():      # only first conv
                param.requires_grad= False

開發者ID:clovaai，項目名稱:CRAFT-pytorch，代碼行數:38，代碼來源:vgg16_bn.py

示例11: vgg11

# 需要導入模塊: from torchvision.models import vgg [as 別名]
# 或者: from torchvision.models.vgg import model_urls [as 別名]
def vgg11(config_channels):
    model = VGG(config_channels, make_layers(config_channels, cfg['A']))
    if config_channels.config.getboolean('model', 'pretrained'):
        url = model_urls['vgg11']
        logging.info('use pretrained model: ' + url)
        state_dict = model.state_dict()
        for key, value in model_zoo.load_url(url).items():
            if key in state_dict:
                state_dict[key] = value
        model.load_state_dict(state_dict)
    return model

開發者ID:ruiminshen，項目名稱:openpose-pytorch，代碼行數:13，代碼來源:vgg.py

示例12: vgg11_bn

# 需要導入模塊: from torchvision.models import vgg [as 別名]
# 或者: from torchvision.models.vgg import model_urls [as 別名]
def vgg11_bn(config_channels):
    model = VGG(config_channels, make_layers(config_channels, cfg['A'], batch_norm=True))
    if config_channels.config.getboolean('model', 'pretrained'):
        url = model_urls['vgg11_bn']
        logging.info('use pretrained model: ' + url)
        state_dict = model.state_dict()
        for key, value in model_zoo.load_url(url).items():
            if key in state_dict:
                state_dict[key] = value
        model.load_state_dict(state_dict)
    return model

開發者ID:ruiminshen，項目名稱:openpose-pytorch，代碼行數:13，代碼來源:vgg.py

示例13: vgg13

# 需要導入模塊: from torchvision.models import vgg [as 別名]
# 或者: from torchvision.models.vgg import model_urls [as 別名]
def vgg13(config_channels):
    model = VGG(config_channels, make_layers(config_channels, cfg['B']))
    if config_channels.config.getboolean('model', 'pretrained'):
        url = model_urls['vgg13']
        logging.info('use pretrained model: ' + url)
        state_dict = model.state_dict()
        for key, value in model_zoo.load_url(url).items():
            if key in state_dict:
                state_dict[key] = value
        model.load_state_dict(state_dict)
    return model

開發者ID:ruiminshen，項目名稱:openpose-pytorch，代碼行數:13，代碼來源:vgg.py

示例14: vgg13_bn

# 需要導入模塊: from torchvision.models import vgg [as 別名]
# 或者: from torchvision.models.vgg import model_urls [as 別名]
def vgg13_bn(config_channels):
    model = VGG(config_channels, make_layers(config_channels, cfg['B'], batch_norm=True))
    if config_channels.config.getboolean('model', 'pretrained'):
        url = model_urls['vgg13_bn']
        logging.info('use pretrained model: ' + url)
        state_dict = model.state_dict()
        for key, value in model_zoo.load_url(url).items():
            if key in state_dict:
                state_dict[key] = value
        model.load_state_dict(state_dict)
    return model

開發者ID:ruiminshen，項目名稱:openpose-pytorch，代碼行數:13，代碼來源:vgg.py

示例15: vgg16

# 需要導入模塊: from torchvision.models import vgg [as 別名]
# 或者: from torchvision.models.vgg import model_urls [as 別名]
def vgg16(config_channels):
    model = VGG(config_channels, make_layers(config_channels, cfg['D']))
    if config_channels.config.getboolean('model', 'pretrained'):
        url = model_urls['vgg16']
        logging.info('use pretrained model: ' + url)
        state_dict = model.state_dict()
        for key, value in model_zoo.load_url(url).items():
            if key in state_dict:
                state_dict[key] = value
        model.load_state_dict(state_dict)
    return model

開發者ID:ruiminshen，項目名稱:openpose-pytorch，代碼行數:13，代碼來源:vgg.py

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