--- 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)