[Link to Github Release](https://github.com/Phhofm/models/releases/tag/4xDRCT-mssim-pretrains)

Since no [DRCT](https://github.com/ming053l/DRCT/tree/main) model releases exist yet, I am releasing my drct-s, drct and drct-l pretrains. 
These can be used to speed up and stabilize early training stages when training new drct models.
Trained with mssim (and augs, and color and lumaloss) on downscaled [nomosuni](https://github.com/muslll/neosr/tree/0ecbeb98dcefd97801da0ea39ca2cd03a87fce21?tab=readme-ov-file#datasets).
Training files are also provided additionally.

## 4xmssim_drct-l_pretrain

**Scale:** 4  
**Architecture:** [DRCT](https://github.com/ming053l/DRCT)  
**Architecture Option:** [DRCT-L](https://github.com/ming053l/DRCT/blob/8c13e63135f494913cd504c073e41ef52250d1d4/options/train/train_DRCT-L_SRx4_ImageNet_from_scratch.yml#L55)  

**Author:** Philip Hofmann  
**License:** CC-BY-0.4  
**Purpose:** Pretrained  
**Subject:** Anime, Photography  
**Input Type:** Images  
**Release Date:** 28.04.2024  

**Dataset:** [nomos_uni](https://github.com/muslll/neosr?tab=readme-ov-file#datasets)  
**Dataset Size:** 2989  
**OTF (on the fly augmentations):** No  
**Pretrained Model:** None (=From Scratch)  
**Iterations:** 108'000  
**Batch Size:** 2-6  
**GT Size:** 128-320  

**Description:** A pretrain to start drct-l model training, since there are no official released drct pretrains yet I trained these myself and release them here.

4xmssim_drct-l_pretrain

[Link to Github Release](https://github.com/Phhofm/models/releases/tag/4xDRCT-mssim-pretrains)

Since no [DRCT](https://github.com/ming053l/DRCT/tree/main) model releases exist yet, I am releasing my drct-s, drct and drct-l pretrains. 
These can be used to speed up and stabilize early training stages when training new drct models.
Trained with mssim (and augs, and color and lumaloss) on downscaled [nomosuni](https://github.com/muslll/neosr/tree/0ecbeb98dcefd97801da0ea39ca2cd03a87fce21?tab=readme-ov-file#datasets).
Training files are also provided additionally.

## 4xmssim_drct_pretrain

**Scale:** 4  
**Architecture:** [DRCT](https://github.com/ming053l/DRCT)  
**Architecture Option:** [DRCT](https://github.com/ming053l/DRCT/blob/8c13e63135f494913cd504c073e41ef52250d1d4/options/train/train_DRCT_SRx4_ImageNet_from_scratch.yml#L55)  

**Author:** Philip Hofmann  
**License:** CC-BY-0.4  
**Purpose:** Pretrained  
**Subject:** Anime, Photography  
**Input Type:** Images  
**Release Date:** 28.04.2024  

**Dataset:** [nomos_uni](https://github.com/muslll/neosr?tab=readme-ov-file#datasets)  
**Dataset Size:** 2989  
**OTF (on the fly augmentations):** No  
**Pretrained Model:** None (=From Scratch)  
**Iterations:** 95'000  
**Batch Size:** 2-6  
**GT Size:** 128-320   

**Description:** A pretrain to start drct model training, since there are no official released drct pretrains yet I trained these myself and release them here.

4xmssim_drct_pretrain

[Link to Github Release](https://github.com/Phhofm/models/releases/tag/4xDRCT-mssim-pretrains)

Since no [DRCT](https://github.com/ming053l/DRCT/tree/main) model releases exist yet, I am releasing my drct-s, drct and drct-l pretrains. 
These can be used to speed up and stabilize early training stages when training new drct models.
Trained with mssim (and augs, and color and lumaloss) on downscaled [nomosuni](https://github.com/muslll/neosr/tree/0ecbeb98dcefd97801da0ea39ca2cd03a87fce21?tab=readme-ov-file#datasets).
Training files are also provided additionally.


## 4xmssim_drct-s_pretrain.pth  

**Scale:** 4  
**Architecture:** [DRCT](https://github.com/ming053l/DRCT)  
**Architecture Option:** [DRCT-S](https://github.com/muslll/neosr/blob/0ecbeb98dcefd97801da0ea39ca2cd03a87fce21/neosr/archs/drct_arch.py#L923)  

**Author:** Philip Hofmann  
**License:** CC-BY-0.4  
**Purpose:** Pretrained  
**Subject:** Anime, Photography  
**Input Type:** Images  
**Release Date:** 28.04.2024  

**Dataset:** [nomos_uni](https://github.com/muslll/neosr?tab=readme-ov-file#datasets)  
**Dataset Size:** 2989  
**OTF (on the fly augmentations):** No  
**Pretrained Model:** None (=From Scratch)  
**Iterations:** 75'000  
**Batch Size:** 6  
**GT Size:** 128-320  

**Description:** A pretrain to start drct-s model training, since there are no official released drct pretrains yet I trained these myself and release them here.

4xmssim_drct-s_pretrain

[Link to Github Release](https://github.com/Phhofm/models/releases/tag/4xmssim_hma_pretrains)

Since no official [HMA](https://github.com/korouuuuu/HMA) model releases exist yet, I am releasing my [hma](https://github.com/muslll/neosr/blob/a50b56de418c938425fd3606697f62d61dbddfc3/neosr/archs/hma_arch.py#L1148) and [hma_medium](https://github.com/muslll/neosr/blob/a50b56de418c938425fd3606697f62d61dbddfc3/neosr/archs/hma_arch.py#L1386) mssim pretrains.   
These can be used to speed up and stabilize early training stages when training new hma models.  
Trained with mssim on [nomosv2](https://github.com/muslll/neosr/tree/a50b56de418c938425fd3606697f62d61dbddfc3?tab=readme-ov-file#-datasets).  


## 4xmssim_hma_pretrain  

**Scale:** 4  
**Architecture:** [HMA](https://github.com/korouuuuu/HMA)  
**Architecture Option:** [hma](https://github.com/muslll/neosr/blob/a50b56de418c938425fd3606697f62d61dbddfc3/neosr/archs/hma_arch.py#L1148)  

**Author:** Philip Hofmann  
**License:** CC-BY-0.4  
**Purpose:** Pretrained  
**Subject:** Photography  
**Input Type:** Images  
**Release Date:** 19.07.2024  

**Dataset:** [nomosv2](https://github.com/muslll/neosr/tree/a50b56de418c938425fd3606697f62d61dbddfc3?tab=readme-ov-file#-datasets)  
**Dataset Size:** 6000  
**OTF (on the fly augmentations):** No  
**Pretrained Model:** None (=From Scratch)  
**Iterations:** 205'000  
**Batch Size:** 4  
**Patch Size:** 96  

**Description:** A pretrain to start hma model training.  

---

## 4xmssim_hma_medium_pretrain  

**Scale:** 4  
**Architecture:** [HMA](https://github.com/korouuuuu/HMA)  
**Architecture Option:** [hma_medium](https://github.com/muslll/neosr/blob/a50b56de418c938425fd3606697f62d61dbddfc3/neosr/archs/hma_arch.py#L1386)  

**Author:** Philip Hofmann  
**License:** CC-BY-0.4  
**Purpose:** Pretrained  
**Subject:** Photography  
**Input Type:** Images  
**Release Date:** 19.07.2024  

**Dataset:** [nomosv2](https://github.com/muslll/neosr/tree/a50b56de418c938425fd3606697f62d61dbddfc3?tab=readme-ov-file#-datasets)  
**Dataset Size:** 6000  
**OTF (on the fly augmentations):** No  
**Pretrained Model:** None (=From Scratch)  
**Iterations:** 150'000  
**Batch Size:** 4  
**Patch Size:** 48  

**Description:** A pretrain to start hma_medium model training.  

---

**Showcase:**  
[slow.pics](https://slow.pics/c/Eoq18VDx)

 4xmssim_hma_pretrains

4xmssim_realplksr_dysample_pretrain  
Scale: 4  
Architecture: [RealPLKSR with Dysample](https://github.com/muslll/neosr/?tab=readme-ov-file#supported-archs)  
Architecture Option: [realplksr](https://github.com/muslll/neosr/blob/master/neosr/archs/realplksr_arch.py)  

Author: Philip Hofmann  
License: CC-BY-0.4  
Purpose: Pretrained  
Subject: Photography  
Input Type: Images  
Release Date: 27.06.2024  

Dataset: [nomosv2](https://github.com/muslll/neosr/?tab=readme-ov-file#-datasets)  
Dataset Size: 6000  
OTF (on the fly augmentations): No  
Pretrained Model: None (=From Scratch)  
Iterations: 200'000  
Batch Size: 8  
GT Size: 192, 512  

Description: [Dysample](https://arxiv.org/pdf/2308.15085) had been recently added to RealPLKSR, which from what I had seen can resolve or help avoid the checkerboard / grid pattern on inference outputs. So with the [commits from three days ago, the 24.06.24, on neosr](https://github.com/muslll/neosr/commits/master/?since=2024-06-24&until=2024-06-24), I wanted to create a 4x photo pretrain I can then use to train more realplksr models with dysample specifically to stabilize training at the beginning.

Showcase:  
[Imgsli](https://imgsli.com/Mjc0OTA1)  
[Slowpics](https://slow.pics/c/I9grkcqM)

4xmssim_realplksr_dysample_pretrain

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