本文整理汇总了Python中resnet.ResNet方法的典型用法代码示例。如果您正苦于以下问题：Python resnet.ResNet方法的具体用法？Python resnet.ResNet怎么用？Python resnet.ResNet使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类resnet的用法示例。
在下文中一共展示了resnet.ResNet方法的4个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: main
# 需要导入模块: import resnet [as 别名]
# 或者: from resnet import ResNet [as 别名]
def main(argv=None): # pylint: disable=unused-argument
assert args.detect or args.segment, "Either detect or segment should be True"
assert args.ckpt > 0, "Specify the number of checkpoint"
net = ResNet(config=net_config, depth=50, training=False)
loader = Loader(osp.join(EVAL_DIR, 'demodemo'))
with tf.Session(config=tf.ConfigProto(allow_soft_placement=True,
log_device_placement=False)) as sess:
detector = Detector(sess, net, loader, net_config, no_gt=args.no_seg_gt,
folder=osp.join(loader.folder, 'output'))
detector.restore_from_ckpt(args.ckpt)
for name in loader.get_filenames():
image = loader.load_image(name)
h, w = image.shape[:2]
print('Processing {}'.format(name + loader.data_format))
detector.feed_forward(img=image, name=name, w=w, h=h, draw=True,
seg_gt=None, gt_bboxes=None, gt_cats=None)
print('Done') 示例2: __init__
# 需要导入模块: import resnet [as 别名]
# 或者: from resnet import ResNet [as 别名]
def __init__(self, num_kpt=7, image_size=(80, 80), onnx_mode=False, init_weight=True):
super(KeypointNet, self).__init__()
net_size = 16
self.conv = nn.Conv2d(in_channels=3, out_channels=net_size, kernel_size=7, stride=1, padding=3)
# torch.nn.init.xavier_uniform(self.conv.weight)
self.bn = nn.BatchNorm2d(net_size)
self.relu = nn.ReLU()
self.res1 = ResNet(net_size, net_size)
self.res2 = ResNet(net_size, net_size * 2)
self.res3 = ResNet(net_size * 2, net_size * 4)
self.res4 = ResNet(net_size * 4, net_size * 8)
self.out = nn.Conv2d(in_channels=net_size * 8, out_channels=num_kpt, kernel_size=1, stride=1, padding=0)
# torch.nn.init.xavier_uniform(self.out.weight)
if init_weight:
self._initialize_weights()
self.image_size = image_size
self.num_kpt = num_kpt
self.onnx_mode = onnx_mode 示例3: init_detectot
# 需要导入模块: import resnet [as 别名]
# 或者: from resnet import ResNet [as 别名]
def init_detectot(self):
assert args.detect or args.segment, "Either detect or segment should be True"
assert args.ckpt > 0, "Specify the number of checkpoint"
net = ResNet(config=net_config, depth=50, training=False)
self.loader = Loader(opj(EVAL_DIR, 'demodemo'))
self.detector = Detector(self.sess, net, self.loader, net_config, no_gt=args.no_seg_gt,
folder=opj(self.loader.folder, 'output'))
self.detector.restore_from_ckpt(args.ckpt) 示例4: net_select
# 需要导入模块: import resnet [as 别名]
# 或者: from resnet import ResNet [as 别名]
def net_select(name, data_format='NCHW', weight_decay=5e-4):
if name == 'SphereNet':
from sphere import SphereNet
network = SphereNet(data_format=data_format,
weight_decay=weight_decay)
elif name == 'ResNeXt-26':
from resnext import ResNeXt
network = ResNeXt(num_layers=26, num_card=32,
data_format=data_format,
weight_decay=weight_decay)
elif name == 'ResNet-50':
from resnet import ResNet
network = ResNet(num_layers=50,
data_format=data_format,
weight_decay=weight_decay)
elif name == 'ShuffleNet-v2-small':
from shufflenet_v2 import ShuffleNet_v2_small
network = ShuffleNet_v2_small(alpha=2.0,
se=False, residual=False,
data_format=data_format,
weight_decay=weight_decay)
elif name == 'ShuffleNet-v2-middle':
from shufflenet_v2 import ShuffleNet_v2_middle
network = ShuffleNet_v2_middle(se=False, residual=False,
data_format=data_format,
weight_decay=weight_decay)
elif name == 'ShuffleNet-v2-large':
from shufflenet_v2 import ShuffleNet_v2_large
network = ShuffleNet_v2_large(data_format=data_format,
weight_decay=weight_decay)
elif name == 'MobileNet-v2':
pass
elif name == 'Inception-v4':
pass
elif name == 'VGG16':
pass
elif name == 'AlexNet':
pass
else:
raise ValueError('Unsupport network architecture.')
return network