def __init__(self, cfgfile, use_giou_loss):
super(Darknet, self).__init__()
self.use_giou_loss = use_giou_loss
self.blocks = parse_cfg(cfgfile)
self.width = int(self.blocks[0]['width'])
self.height = int(self.blocks[0]['height'])
self.models = self.create_network(self.blocks) # merge conv, bn,leaky
self.yolo_layers = [
layer for layer in self.models
if layer.__class__.__name__ == 'YoloLayer'
]
self.loss = self.models[len(self.models) - 1]
self.header = torch.IntTensor([0, 0, 0, 0])
self.seen = 0
def __init__(self, cfgfile):
super(Darknet, self).__init__()
self.blocks = parse_cfg(cfgfile)
self.width = int(self.blocks[0]['width'])
self.height = int(self.blocks[0]['height'])
self.models = self.create_network(self.blocks) # merge conv, bn,leaky
self.yolo_layers = [layer for layer in self.models if hasattr(layer, "metrics")]
self.loss = self.models[len(self.models) - 1]
if self.blocks[(len(self.blocks) - 1)]['type'] == 'region':
self.anchors = self.loss.anchors
self.num_anchors = self.loss.num_anchors
self.anchor_step = self.loss.anchor_step
self.num_classes = self.loss.num_classes
self.header = torch.IntTensor([0, 0, 0, 0])
self.seen = 0
def __init__(self, cfgfile, use_giou_loss):
super(YOLO_only, self).__init__()
self.use_giou_loss = use_giou_loss
dict_blocks = parse_cfg(cfgfile)
self.blocks = nn.ModuleList()
for block in dict_blocks:
self.blocks.append(DictWrapper(block))
#self.blocks = nn.ModuleList(parse_cfg(cfgfile))
self.width = int(self.blocks[0]['width'])
self.height = int(self.blocks[0]['height'])
self.models = self.create_network(self.blocks) # merge conv, bn,leaky
self.yolo_layers = [
layer for layer in self.models
if layer.__class__.__name__ == 'YoloLayer'
]
self.loss = self.models[len(self.models) - 1]
self.header = torch.IntTensor([0, 0, 0, 0])
self.seen = 0