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{
"name": "4xNomos2_hq_mosr",
"author": "helaman",
"license": "CC-BY-4.0",
"tags": [
"general-upscaler",
"photo"
],
"description": "[Link to Github Release](https://github.com/Phhofm/models/releases/tag/4xNomos2_hq_mosr)\n\n# 4xNomos2_hq_mosr \nScale: 4 \nArchitecture: [MoSR](https://github.com/umzi2/MoSR) \nArchitecture Option: [mosr](https://github.com/umzi2/MoSR/blob/95c5bf73cca014493fe952c2fbc0bdbe593da08f/neosr/archs/mosr_arch.py#L117) \n\nAuthor: Philip Hofmann \nLicense: CC-BY-0.4 \nPurpose: Upscaler \nSubject: Photography \nInput Type: Images \nRelease Date: 25.08.2024 \n\nDataset: [nomosv2](https://github.com/muslll/neosr/?tab=readme-ov-file#-datasets) \nDataset Size: 6000 \nOTF (on the fly augmentations): No \nPretrained Model: [4xmssim_mosr_pretrain](https://github.com/Phhofm/models/releases/tag/4xmssim_mosr_pretrain) \nIterations: 190'000 \nBatch Size: 6 \nPatch Size: 64 \n\nDescription: \nA 4x [MoSR](https://github.com/umzi2/MoSR) upscaling model, meant for non-degraded input, since this model was trained on non-degraded input to give good quality output. \n\nIf your input is degraded, use a 1x degrade model first. So for example if your input is a .jpg file, you could use a 1x dejpg model first. \n\nModel Showcase: [Slowpics](https://slow.pics/c/cqGJb0gT)",
"date": "2024-08-25",
"architecture": "mosr",
"size": null,
"scale": 4,
"inputChannels": 3,
"outputChannels": 3,
"resources": [
{
"platform": "pytorch",
"type": "pth",
"size": 17213494,
"sha256": "c60dbfc7e6f7d27e03517d1bec3f3cbd16e8cd4288eefd1358952f73f8497ddc",
"urls": [
"https://github.com/Phhofm/models/releases/download/4xNomos2_hq_mosr/4xNomos2_hq_mosr.pth"
]
},
{
"platform": "onnx",
"type": "onnx",
"size": 17288863,
"sha256": "f31fde6bd0e3475759aa5677d37b43b4e660d75e3629cd096bbc590feb746808",
"urls": [
"https://github.com/Phhofm/models/releases/download/4xNomos2_hq_mosr/4xNomos2_hq_mosr_fp32.onnx"
]
}
],
"trainingIterations": 190000,
"trainingBatchSize": 6,
"trainingHRSize": 256,
"trainingOTF": false,
"dataset": "nomosv2",
"datasetSize": 6000,
"pretrainedModelG": "4x-mssim-mosr-pretrain",
"images": [
{
"type": "paired",
"LR": "https://i.slow.pics/ZIKbM9eP.webp",
"SR": "https://i.slow.pics/PIgZDy6T.webp"
},
{
"type": "paired",
"LR": "https://i.slow.pics/s1hij4Od.webp",
"SR": "https://i.slow.pics/3Acn0SYs.webp"
},
{
"type": "paired",
"LR": "https://i.slow.pics/uPad2heK.webp",
"SR": "https://i.slow.pics/PqaMMYN4.webp"
},
{
"type": "paired",
"LR": "https://i.slow.pics/atbpBswr.webp",
"SR": "https://i.slow.pics/yctDsFPC.webp"
},
{
"type": "paired",
"LR": "https://i.slow.pics/tYQ5KasA.webp",
"SR": "https://i.slow.pics/dWMOLSM3.webp"
},
{
"type": "paired",
"LR": "https://i.slow.pics/oBi3wXy1.webp",
"SR": "https://i.slow.pics/ESWD90pQ.webp"
},
{
"type": "paired",
"LR": "https://i.slow.pics/6jejJasv.webp",
"SR": "https://i.slow.pics/xBV1feGZ.webp"
},
{
"type": "paired",
"LR": "https://i.slow.pics/DgqCdj3C.webp",
"SR": "https://i.slow.pics/haiROW2m.webp"
},
{
"type": "paired",
"LR": "https://i.slow.pics/57pqAXqU.webp",
"SR": "https://i.slow.pics/e3DTrXnD.webp"
}
]
} |