| | --- |
| | 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/4xLSDIRCompact2) |
| |
|
| | # 4xLSDIRCompact2 |
| |
|
| | Name: 4xLSDIRCompact2 |
| | Author: Philip Hofmann |
| | Release Date: 25.03.2023 |
| | License: CC BY 4.0 |
| | Model Architecture: SRVGGNetCompact |
| | Scale: 4 |
| | Purpose: 4x fast photo upscaler |
| |
|
| | Iterations: CompactC 205’000 & CompactR 150’000 |
| | batch_size: Variable(1-10) |
| | HR_size: 256 |
| | Dataset: LSDIR |
| | Dataset_size: 84991 |
| | OTF Training No |
| | Pretrained_Model_G: 4x_Compact_Pretrain.pth |
| | |
| | Description: 4xLSDIRCompactv2 supersedes the previously released models, it combines all my progress on my compact model. Both CompactC and CompactR had received around 8 hours more training since release with batch size 10 (CompactR had only been up to 5 on release), and these two were then interpolated together. This allows v2 to handle some degradations, while preserving the details of the CompactC model. Examples: https://imgsli.com/MTY0Njgz/0/2 |
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