1x-Archiver-Soft.json

{
    "name": "Archiver Soft",
    "author": "loganavter",
    "license": "MIT",
    "tags": [
        "denoise",
        "restoration",
        "dehalo",
        "cartoon"
    ],
    "description": "A light-touch restoration model from the Archivist suite, designed for high-quality sources. It focuses on gentle denoising while preserving the original film grain aesthetic. CAVEAT: In some scenarios, a standard DRUNet might yield subjectively better results. Always compare on your specific footage.\n\nThis model is optimized for input resolutions between 720p and 1080p. Using it on significantly different resolutions may produce suboptimal results.\n\nAll Archivist models are trained on a custom dataset generated by a physics-based degradation simulator. Recommended Workflow: Use Archivist to fix physical defects, then pass the result through DRUNet (low strength) to stabilize.",
    "date": "2025-12-17",
    "architecture": "esrgan",
    "size": [
        "48nf",
        "16nb"
    ],
    "scale": 1,
    "inputChannels": 3,
    "outputChannels": 3,
    "resources": [
        {
            "platform": "pytorch",
            "type": "pth",
            "size": 2721289,
            "sha256": "d02616fa398617e2b8ac67cedd5ba265b9ae52372799a75467a9e0d4dd4641f1",
            "urls": [
                "https://github.com/Loganavter/Archivist-Project-Denoiser/releases/download/v1.0/1x-Archivist_Soft.pth"
            ]
        }
    ],
    "trainingIterations": 453000,
    "trainingHRSize": 256,
    "trainingOTF": true,
    "dataset": "Custom dataset (~1800 images) of classic cel animation (1940s-1980s) processed with the Project Degrader physics-based pipeline.",
    "datasetSize": 1800,
    "images": [
        {
            "type": "paired",
            "caption": "Test case: Light noise and grain preservation",
            "LR": "https://imgsli.com/i/f667ebba-4728-4514-bac6-ccb7e14c03b1.jpg",
            "SR": "https://imgsli.com/i/3a42eb2f-f798-4916-b4b7-8eec3ae8d002.jpg"
        }
    ]
}