# IQA01

**Repository Path**: fl9621/IQA01

## Basic Information

- **Project Name**: IQA01
- **Description**: No description available
- **Primary Language**: Python
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-05-11
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Deep Image Structure and Texture Similarity (DISTS) Metric

This is the repository of paper [Image Quality Assessment: Unifying Structure and Texture Similarity](https://arxiv.org/abs/2004.07728).


### Highlights:
1. A full-reference IQA model correlated well with human perception of image quality.
2. It is robust to texture variance (e.g., evaluating the images generated by GANs) and mild geometric transformations (e.g., evaluating the image pair that are not strictly point-by-point aligned).
3. It can be employed as the objective function in various optimization problems (see [optimization comparison](https://github.com/dingkeyan93/IQA-optimization)). <!-- (The best practice: pretrain with L1/L2 loss, then finetune with DISTS + GAN loss) -->
   

**Three implementation versions:** 
1. Pytorch [```DISTS_pt.py```](/DISTS_pytorch/DISTS_pt.py) (recommend)
2. Tensorflow [```DISTS_tf.py```](/DISTS_tensorflow/DISTS_tf.py) 
3. Matlab [```DISTS.m```](/DISTS_matlab/DISTS.m). 

### ====== Pytorch ======
**Installation:** 
- ```pip install dists-pytorch```

### Requirements: 
- Python>=3.6
- Pytorch>=1.0

**Usage:** 
```python
from DISTS_pytorch import DISTS
D = DISTS()
# calculate DISTS between X, Y (a batch of RGB images, data range: 0~1)
# X: (N,3,H,W) 
# Y: (N,3,H,W) 
dists_value = D(X, Y)
# set 'require_grad=True, batch_average=True' to get a scalar value as loss.
dists_loss = D(X, Y, require_grad=True, batch_average=True) 
dists_loss.backward()
```
or

```bash
git clone https://github.com/dingkeyan93/DISTS
cd DISTS_pytorch
python DISTS_pt.py --ref <ref_path> --dist <dist_path>
```


### ====== Tensorflow ======

**Requirements:** 
- Python>=3.6
- Tensorflow>=1.15

**Usage:** 
```bash
git clone https://github.com/dingkeyan93/DISTS
cd DISTS_tensorflow
python DISTS_tf.py --ref <ref_path> --dist <dist_path>
```

### ====== Matlab ======

**Requirements:** 
- Matlab>=2019b

**Usage:** 
```bash
git clone https://github.com/dingkeyan93/DISTS
run demo.m
help DISTS
```

### Citation
```
@article{ding2020iqa,
  title={Image Quality Assessment: Unifying Structure and Texture Similarity},
  author={Ding, Keyan and Ma, Kede and Wang, Shiqi and Simoncelli, Eero P.},
  journal = {CoRR},
  volume = {abs/2004.07728},
  year={2020},
  url = {https://arxiv.org/abs/2004.07728}
}
```