Wrong pretrained models for segmentation task

[D-Sokol]

Wrong pretrained models for segmentation task

[ydhongHIT]

I've tried to use your code and pretrained models for an image segmentation. However, it turns out that files best_val.pth and best_val_smaller.pth from the Google Drive are compatible with some unknown class with fields model and seghead_extra rather than DualResNet.
Currently I load pretrained weight with the following code:

def fix_snapshot(state_dict, prefix='model.'):
    return {key[len(prefix):]: weight
            for key, weight in state_dict.items()
            if key.startswith(prefix)}

from DDRNet.segmentation.DDRNet_23_slim import DualResNet_imagenet  # or DDRNet_23
net = DualResNet_imagenet()
state_dict = torch.load('weights/best_val_smaller.pth')  # or best_val.pth
state_dict = fix_snapshot(state_dict)
net.load_state_dict(state_dict, strict=False)  # None missing keys, a lot of unexpected ones

and it works quite fine, but it doesn't seem right to me.
Could you please update pretrained models or provide code of that class?
(There is no such problem for classification task models)

Hi, I didn't exactly understand what you mean. Please refer to https://github.com/chenjun2hao/DDRNet.pytorch which correctly evaluated the segmentation pretrained models.