{ "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" } ] }