Skip to content

achie27/super-resolution

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

6 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

REQUIREMENTS

This is written in Python 3.6. The following packages are needed -

numpy
torch
torchvision
cv2
Pillow

USAGE

Pretrained models

  1. Use this link to download all the pretrained models.
  2. Put the contents of each folder, named by the model, in architecture/{model}/pretrained_models/

Super-resolving images or videos

  1. Configure settings, in main.py, for input and output folders.
  2. Put all the images and videos to be SR'ed in settings['input']
  3. Choose the model to be used
  4. Run main.py
  5. Find all the upscaled media in settings['output']

Benchmarking

  1. Configure settings in test_quality.py for test_dataset_folder and output_dataset_folder
  2. Download this benchmarking dataset and extract its contents in setting['test_dataset_folder'].
  3. Change other settings if need be.
  4. Run test_quality.py

My Hardware Specs

Intel Core i7-7700HQ CPU @ 2.80 GHZ
NVIDIA GeForce GTX 1050 Ti (4GB)
8GB DDR4 RAM

About

Super-resolves images using ESRGAN, SRCNN etc

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages