FSRCNN_paddle
July 11, 2023 · View on GitHub
This repository is implementation of the "Accelerating the Super-Resolution Convolutional Neural Network".
参考：https://github.com/yjn870/FSRCNN-pytorch
Requirements
-
paddlepaddle 2.4.0
-
paddleseg 2.8.0
-
Numpy 1.15.4
-
Pillow 5.4.1
-
h5py 2.8.0
-
tqdm 4.30.0
-
Train
The 91-image, Set5 dataset converted to HDF5 can be downloaded from the links below.
| Dataset | Scale | Type | Link |
|---|---|---|---|
| 91-image | 2 | Train | Download |
| 91-image | 3 | Train | Download |
| 91-image | 4 | Train | Download |
| Set5 | 2 | Eval | Download |
| Set5 | 3 | Eval | Download |
| Set5 | 4 | Eval | Download |
Otherwise, you can use prepare.py to create custom dataset.
python train.py --train-file "BLAH_BLAH/91-image_x4.h5" \
--eval-file "BLAH_BLAH/Set5_x4.h5" \
--outputs-dir "BLAH_BLAH/outputs" \
--scale 4 \
--lr 1e-3 \
--batch-size 16 \
--num-epochs 20 \
--num-workers 0 \
--seed 123
权重文件位置：BLAH_BLAH/outputs
python test.py --weights-file "BLAH_BLAH/outputs/x3/best.pdiparams" \
--image-file "data/butterfly_GT.bmp" \
--scale 3
Results
PSNR was calculated on the Y channel.
Set5
| Eval. Mat | Scale | Paper | Ours (butterfly_GT.bmp) |
|---|
| PSNR | 3 | 28.68 | 28.00 |
 |
 |
 |
 |
 |
 |