rakeshraj97 / edsr-super-resolution

This repository is an implementation of EDSR model implemented in PyTorch

EDSR-Super-Resolution

This repository is an implementation of EDSR model using PyTorch Check the official code and paper (The video input/output super-resolution will be added soon to the Master branch)

This model was trained on NVIDIA P100 with ~4500 annotated satellite Low Resolution image pathches which were obtained by Image degradation and Image downsampling of the High Resolution images. You can download the dataset which I used for training the model here

Required Dependencies

• Python 3.6
• PyTorch >= 1.0.0
• Pillow
• Utility
• Imageio
• tqdm
• scikit-image
• OpenCV (Only for Video input/output)
• matplotlib

Quickstart (Demo)

You can test the pretrained model EDSR_baseline_x2 by placing the images in test folder. The supported formats are png and jpeg files. The pretrained model can be downloaded using this link

Run the script in src folder. Uncomment the appropriate line in demo.sh to test your image. sh demo.sh The output images can be found under experiment/test/results-Demo folder.

Output of the trained model

edsr-super-resolution's Issues

EDSRx2.pt from gdrive is crashing main.py

Hello.
I download the pretrained models from gdrive.
While model_best.pt works smoothly, the EDSRx2.pt is crashing with a tensor size error.
how is it possible?
the debug output is the below

/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:477: UserWarning: This DataLoader will create 6 worker processes in total. Our suggested max number of worker in current system is 4, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.
cpuset_checked))
Making model...
Load the model from ../../pt-models/EDSR_x2.pt
Traceback (most recent call last):
File "/content/EDSR-Super-Resolution/src/model/edsr.py", line 74, in load_state_dict
own_state[name].copy_(param)
RuntimeError: The size of tensor a (64) must match the size of tensor b (256) at non-singleton dimension 0

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "main.py", line 33, in
main()
File "main.py", line 23, in main
_model = model.Model(args, checkpoint)
File "/content/EDSR-Super-Resolution/src/model/init.py", line 34, in init
cpu=args.cpu
File "/content/EDSR-Super-Resolution/src/model/init.py", line 103, in load
self.model.load_state_dict(load_from, strict=False)
File "/content/EDSR-Super-Resolution/src/model/edsr.py", line 80, in load_state_dict
.format(name, own_state[name].size(), param.size()))
RuntimeError: While copying the parameter named head.0.weight, whose dimensions in the model are torch.Size([64, 3, 3, 3]) and whose dimensions in the checkpoint are torch.Size([256, 3, 3, 3]).