| 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/2xHFA2kAVCCompact) | |
| # 2xHFA2kAVCCompact | |
| Name: 2xHFA2kAVCCompact | |
| Author: Philip Hofmann | |
| Release Date: 18.06.2023 | |
| License: CC BY 4.0 | |
| Network: SRVGGNet | |
| Scale: 2 | |
| Purpose: Fast 2x anime upscaling model that handles AVC (h264) degradation | |
| Iterations: 111,000 | |
| batch_size: 4 | |
| HR_size: 256 | |
| Dataset: HFA2k_h264 | |
| Number of train images: 2568 | |
| OTF Training: No | |
| Pretrained_Model_G: None | |
| Description: A 2x Compact anime upscale model that handles AVC (h264) degradation. Applied h264 crf 20-28 degradation together with bicubic, bilinear, box and lanczos downsampling on the HFA2k dataset with Kim's dataset destroyer. | |
|  | |
|  | |