kushajveersingh / resize_network_cv Goto Github PK

The situation you mentioned are the input image and out image are the same Height and Width.

What about if we want different Height and width?

path = os.path.join(path, f"{cfg.data.name}.ckpt")
ckpt = torch.load(path)['state_dict']

The .ckpt file is not in the dataset I downloaded.
Where should I look for this file?Thanks！

I found this bug by printing model summary.
The model should return out instead of x (the original input image).

https://github.com/KushajveerSingh/resize_network_cv/blob/main/src/models/resizer.py#L76

The original paper says:

... the proposed architecture allows for resizing an image to any target size and aspect ratio.

So the Resizer should handle input image with any aspect ratio.
In spite of that, the Resizer implementation (interpolation) seems to assume the input image is square (or, only handle uniform-scale resize: e.g. (512, 256) -> (256, 128)).

The current implementation interpolates by specifying scale_factor, though I think it's more useful to specify the output image size and calculate scale factor automatically.

The reference code:

# current implementation
self.interpolate = partial(F.interpolate,
                           scale_factor=self.scale_factor,
                           mode=self.interpolate_mode,
                           align_corners=False,
                           recompute_scale_factor=False)

# suggestion
self.interpolate = partial(F.interpolate,
                           size=output_size,
                           mode=self.interpolate_mode,
                           align_corners=False)

c.f. https://github.com/KushajveerSingh/resize_network_cv/blob/main/src/models/resizer.py#L56-L60

I have run twice，one is follow you config，another is to extand the epoch,but the result is nothing different，
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after try your config，the second try config is , ran the resize_net 800 epoch, learn rate step_size is 100，
and the fintune 50 epoch，but the result is the same，
is there any problem？thank you for your reply.
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if needed, I will show the config