Open SlowMonk opened 4 years ago
python train.py --dataset COCO --dataset_root /media/jake/mark-4tb3/input/datasets/coco_2014/coco/annotations
idk but this stop at '
else: print('elseA',in_channels,v) conv2d = nn.Conv2d(in_channels, v, kernel_size=3, padding=1)
point its in ssd.py
def vgg(cfg, i, batch_norm=False): print('vgg') layers = [] in_channels = i for idx,v in enumerate(cfg): print(idx) if v == 'M': print('M') layers += [nn.MaxPool2d(kernel_size=2, stride=2)] elif v == 'C': print('C') layers += [nn.MaxPool2d(kernel_size=2, stride=2, ceil_mode=True)] else: print('elseA',in_channels,v) conv2d = nn.Conv2d(in_channels, v, kernel_size=3, padding=1) print('elseB') if batch_norm: print('if batch_norm') layers += [conv2d, nn.BatchNorm2d(v), nn.ReLU(inplace=True)] else: print('if elseC') layers += [conv2d, nn.ReLU(inplace=True)] in_channels = v print('state_pool5') pool5 = nn.MaxPool2d(kernel_size=3, stride=1, padding=1) conv6 = nn.Conv2d(512, 1024, kernel_size=3, padding=6, dilation=6) conv7 = nn.Conv2d(1024, 1024, kernel_size=1) layers += [pool5, conv6, nn.ReLU(inplace=True), conv7, nn.ReLU(inplace=True)] print('return layers') return layers
Run visdom before training, you won't get connection refuse error. python -m visdom.server then open other tab, must always run visdom during training python train.py ...
python -m visdom.server
python train.py ...
python train.py --dataset COCO --dataset_root /media/jake/mark-4tb3/input/datasets/coco_2014/coco/annotations
idk but this stop at '
point its in ssd.py