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
Modellquelle
- Art
- Other
- Dateigröße
- 1,19 MB
- Version
- v4x LSDIRCompact C
- Aktualisiert
- 26. Okt. 2026
- Quelle
- Hugging Face
Quellenbeschreibung
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
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Quellen
1 QuelleVerifiziert 26. Okt.
Modellartefakte
1 Artefakt
Modellartefakte
1 Artefakt4xLSDIRCompactC.safetensors
safetensors · 1,19 MB · SHA-256 9c6f73330d41…645f · Hugging Face
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2 Auszüge--- 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     
Source context: 0 downloads · 0 likes · Pipeline image-to-image · Repo Phips/4xLSDIRCompactC
