### introduction

**dataset.py+augmentation.py** 

- Designed for training the siamldes(NM+LP)

**homo_dataset**
- Designed for training the homo-estimator(HOMO) on POT dataset (wich gives images with perspective transformation)

- this file implements the similarity transform augmentation on homography dataset like POT, we don't add pespective transformation for the samples

**unsupervised_dataset.py+homo_augmentation_non_homodata**

- Designed for training the homo-estimator(HOMO) on synthetic or normal dataset without poly label and perspective scenes.

**semi_supervised_dataset.py+homo_augmentation_e2e.py** 

- Designed for training the end-to-end model(NM+LP+HOMO)

