const taskData = {
    datasets: [
        {
            description: "ImageNet-1K is a image classification dataset in which images are used to train image-feature-extraction models.",
            id: "imagenet-1k",
        },
    ],
    demo: {
        inputs: [
            {
                filename: "mask-generation-input.png",
                type: "img",
            },
        ],
        outputs: [
            {
                table: [
                    ["Dimension 1", "Dimension 2", "Dimension 3"],
                    ["0.21236686408519745", "1.0919708013534546", "0.8512550592422485"],
                    ["0.809657871723175", "-0.18544459342956543", "-0.7851548194885254"],
                    ["1.3103108406066895", "-0.2479034662246704", "-0.9107287526130676"],
                    ["1.8536205291748047", "-0.36419737339019775", "0.09717650711536407"],
                ],
                type: "tabular",
            },
        ],
    },
    metrics: [],
    models: [
        {
            description: "A powerful image feature extraction model.",
            id: "timm/vit_large_patch14_dinov2.lvd142m",
        },
        {
            description: "A strong image feature extraction model.",
            id: "nvidia/MambaVision-T-1K",
        },
        {
            description: "A robust image feature extraction model.",
            id: "facebook/dino-vitb16",
        },
        {
            description: "Cutting-edge image feature extraction model.",
            id: "apple/aimv2-large-patch14-336-distilled",
        },
        {
            description: "Strong image feature extraction model that can be used on images and documents.",
            id: "OpenGVLab/InternViT-6B-448px-V1-2",
        },
    ],
    spaces: [
        {
            description: "A leaderboard to evaluate different image-feature-extraction models on classification performances",
            id: "timm/leaderboard",
        },
    ],
    summary: "Image feature extraction is the task of extracting features learnt in a computer vision model.",
    widgetModels: [],
};
export default taskData;
