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hw4's Introduction

Introduction

The goal of this project is to upscale and improve the quality of low resolution images.

Data Directory

 +- VRDL_HW4
    +- models
        +- checkpoint_srresnet.pth.tar
        +- best_checkpoint_srresnet.pth.tar
    +- dataset
        +- testing_lr_images
            +- testing_lr_images
                +- 00.png
                +- 01.png
                ...
                +- 13.png
        +- training_hr_images
            +- training_hr_images
                +- 2092.png
                +- 8049.png
                +- 8143.png
                ...
    datasets.py
    eval.py
    model.py
    split_train_val.py
    test.py
    train.py
    utils.py

How to train

  1. Download the dataset: (I divide dataset into train and validation data)
    https://drive.google.com/file/d/1n796E-LuV1lxqtXJvYgGQIKCWLpN5deH/view?usp=sharing
 python train.py

Use my model & generate the answer. (high-resolution image)

Use the inference.ipynb on colab to generate the answer: https://colab.research.google.com/drive/1WwW7anJiJ9tDxJ93iKFvCDg9DRxixXYJ#scrollTo=4jL5aZH-2Jtu
You only need to cleck all the cells and you can get the output images in high-resolution image folder

My PSNR score: 27.4716 with 2100 epochs (training time 11hours 40mins)
image

Reference

https://blog.csdn.net/qianbin3200896/article/details/104181552

hw4's People

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