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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

KindOtherVersion4x LSDIRCompact CCgrade

Model source

Kind
Other
File size
1.19 MB
Version
v4x LSDIRCompact C
Updated
Oct 26, 2026
Source
Hugging Face

Source description

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

Sources

1 source
Hugging FacePrimaryVersion eeb92fc33deedcb1edca15060738bcc9f7c37535
huggingface.co/Phips/4xLSDIRCompactC/tree/eeb92fc33deedcb1edca15060738bcc9f7c37535

Verified Oct 26

Model artifacts

1 artifact

4xLSDIRCompactC.safetensors

safetensors · 1.19 MB · SHA-256 9c6f73330d41…645f · Hugging Face

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Source excerpts

2 excerpts

--- license: cc-by-4.0 pipeline_tag: image-to-image tags: - pytorch - super-resolution --- [Link to Github Release](https://github.com/Phhofm/models/releases/tag/4xLSDIRCompactC) # 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](https://github.com/Phhofm/models/assets/14755670/68be7b9e-472a-4eab-b0ec-a19346f6ac0d) ![Example2](https://github.com/Phhofm/models/assets/14755670/b3f59497-82e5-48d1-a15e-842ebfbcbf8a) ![Example3](https://github.com/Phhofm/models/assets/14755670/c0ddd288-52fe-4786-841a-264fe5098904) ![Example4](https://github.com/Phhofm/models/assets/14755670/292e2c49-5b99-4255-9068-bb1ed33f58cd) ![Example5](https://github.com/Phhofm/models/assets/14755670/bba3fb8c-d3f8-438a-9e9c-a3517a88ab5b)

Source context: 0 downloads · 0 likes · Pipeline image-to-image · Repo Phips/4xLSDIRCompactC