{
    "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_generator_20220718.json",
    "version": "0.3.0",
    "changelog": {
        "0.3.0": "Update for 1.0",
        "0.2.0": "Unify naming",
        "0.1.0": "Initial version"
    },
    "monai_version": "1.0.0",
    "pytorch_version": "1.10.0",
    "numpy_version": "1.21.0",
    "optional_packages_version": {
        "pytorch-ignite": "0.4.8",
        "pillow": "8.4.0"
    },
    "task": "Generate random hand images from the MedNIST dataset",
    "description": "This example of a GAN generator produces hand xray images like those in the MedNIST dataset",
    "authors": "MONAI Team",
    "copyright": "Copyright (c) MONAI Consortium",
    "intended_use": "This is an example of a GAN with generator discriminator networks using MONAI, suitable for demonstration purposes only.",
    "data_source": "MedNIST dataset kindly made available by Dr. Bradley J. Erickson M.D., Ph.D. (Department of Radiology, Mayo Clinic)",
    "data_type": "jpeg",
    "network_data_format": {
        "inputs": {
            "latent": {
                "type": "tuples",
                "format": "latent",
                "num_channels": 0,
                "spatial_shape": [
                    64
                ],
                "dtype": "float32",
                "value_range": [
                    0,
                    1
                ],
                "is_patch_data": false,
                "channel_def": {}
            }
        },
        "outputs": {
            "pred": {
                "type": "image",
                "format": "magnitude",
                "num_channels": 1,
                "spatial_shape": [
                    64,
                    64
                ],
                "dtype": "float32",
                "value_range": [
                    0,
                    1
                ],
                "is_patch_data": false,
                "channel_def": {
                    "0": "image"
                }
            }
        }
    }
}