4xLSDIRCompactC / README.md
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metadata
license: cc-by-4.0
pipeline_tag: image-to-image
tags:
  - pytorch
  - super-resolution

Link to Github Release

4xLSDIRCompactC

Name: 4xLSDIRCompactC
Author: Philip Hofmann
Release Date: 17.03.2023
License: CC BY 4.0
Network: SRVGGNetCompact
Scale: 4
Purpose: 4x photo upscaler that handler jpg compression

Iterations: 190000
batch_size: Variable(1-5)
HR_size: 256
Dataset: LSDIR
Dataset_size: 84991
OTF Training No
Pretrained_Model_G: 4xLSDIRCompact.pth

Description: Trying to extend my previous model to be able to handle compression (JPG 100-30) by manually altering the training dataset, since 4xLSDIRCompact cant handle compression. Use this instead of 4xLSDIRCompact if your photo has compression (like an image from the web).


Here is a comparison to show that 4xLSDIRCompact cannot handle compression artifacts, and that these two models will produce better output for that specific scenario. These models are not ‘better’ than the previous one, they are just meant to handle a different use case: https://imgsli.com/MTYyODY3

Example1 Example2 Example3 Example4 Example5