Create QA.md

QA.md

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+# Frequently Asked Questions
+
+### 1. How to reproduce your results in the [PIRM18-SR Challenge](https://www.pirm2018.org/PIRM-SR.html) (with low perceptual index)?
+
+First, the released ESRGAN model in the GitHub (`RRDB_ESRGAN_x4.pth`) is **different** from the model we submitted in the competition.
+We found that the lower perceptual index does not always guarantee a better visual quality.
+The aims for the competition and our ESRGAN work will be a bit different.
+We think the aim for the competition is the lower perceptual index and the aim for our ESRGAN work is the better visual quality.
+
+Therefore, in the PIRM18-SR Challenge competition, we used several tricks for the best perceptual index (see Section 4.5 in the [paper](https://arxiv.org/abs/1809.00219)).
+
+Here, we provid the models and codes used in the competition, which is able to produce the results on the `PIRM test dataset` (we use MATLAB 2016b/2017a):
+
+| Group       | Perceptual index         | RMSE  |
+| ------------- |:-------------:| -----:|
+| SuperSR     | 1.978 | 15.30 |
+
+> 1. Download the model and codes from [GoogleDrive](https://drive.google.com/file/d/1l0gBRMqhVLpL_-7R7aN-q-3hnv5ADFSM/view?usp=sharing)
+> 2. Put LR input images in the `LR` folder
+> 3. Run `python test.py`
+> 4. Run `main_reverse_filter.m` in MATLAB as a post processing
+> 5. The results on my computer are: Perceptual index: **1.9777** and RMSE: **15.304**
+
+
+### 2. How do you get the perceptual index in your ESRGAN paper?
+In our paper, we provide the perceptual index in two places.
+
+1). In the Fig. 2, the perceptual index on PIRM self validation dataset is obtained with the **model we submitted in the competition**. 
+Since the pupose of this figure is to show the perception-distortion plane. And we also use the post-precessing here same as in the competition.
+
+2). In the Fig.7, the perceptual indexs are provided as references and they are tested on the data generated by the released ESRGAN model `RRDB_ESRGAN_x4.pth` in the GiuHub.
+Also, there is **no** post-processing when testing the ESRGAN model for better visual quality.