{
    "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json",
    "version": "0.5.7",
    "changelog": {
        "0.5.7": "update channel_def in metadata",
        "0.5.6": "fix the wrong GPU index issue of multi-node",
        "0.5.5": "modify mgpu logging level",
        "0.5.4": "retrain using an internal pretrained ResNet18",
        "0.5.3": "make the training bundle deterministic",
        "0.5.2": "update TensorRT descriptions",
        "0.5.1": "update the TensorRT part in the README file",
        "0.5.0": "add the command of executing inference with TensorRT models",
        "0.4.9": "adapt to BundleWorkflow interface",
        "0.4.8": "update the readme file with TensorRT convert",
        "0.4.7": "add name tag",
        "0.4.6": "modify dataset key name",
        "0.4.5": "update model weights and perfomance metrics",
        "0.4.4": "restructure readme to match updated template",
        "0.4.3": "fix wrong figure url",
        "0.4.2": "update metadata with new metrics",
        "0.4.1": "Fix inference print logger and froc",
        "0.4.0": "add lesion FROC calculation and wsi_reader",
        "0.3.3": "update to use monai 1.0.1",
        "0.3.2": "enhance readme on commands example",
        "0.3.1": "fix license Copyright error",
        "0.3.0": "update license files",
        "0.2.0": "unify naming",
        "0.1.1": "fix location variable name change",
        "0.1.0": "initialize release of the bundle"
    },
    "monai_version": "1.2.0",
    "pytorch_version": "1.13.1",
    "numpy_version": "1.22.2",
    "optional_packages_version": {
        "cucim": "22.8.1",
        "pandas": "1.3.5",
        "torchvision": "0.14.1"
    },
    "name": "Pathology tumor detection",
    "task": "Pathology metastasis detection",
    "description": "A pre-trained model for metastasis detection on Camelyon 16 dataset.",
    "authors": "MONAI team",
    "copyright": "Copyright (c) MONAI Consortium",
    "data_source": "Camelyon dataset",
    "data_type": "tiff",
    "image_classes": "RGB image with intensity between 0 and 255",
    "label_classes": "binary labels for each patch",
    "pred_classes": "scalar probability",
    "eval_metrics": {
        "accuracy": 0.9,
        "froc": 0.72
    },
    "intended_use": "This is an example, not to be used for diagnostic purposes",
    "references": [
        ""
    ],
    "network_data_format": {
        "inputs": {
            "image": {
                "type": "image",
                "format": "magnitude",
                "num_channels": 3,
                "spatial_shape": [
                    224,
                    224
                ],
                "dtype": "float32",
                "value_range": [
                    0,
                    255
                ],
                "is_patch_data": true,
                "channel_def": {
                    "0": "R",
                    "1": "G",
                    "2": "B"
                }
            }
        },
        "outputs": {
            "pred": {
                "type": "probability",
                "format": "classification",
                "num_channels": 1,
                "spatial_shape": [
                    1,
                    1
                ],
                "dtype": "float32",
                "is_patch_data": true,
                "value_range": [
                    0,
                    1
                ],
                "channel_def": {
                    "0": "metastasis"
                }
            }
        }
    }
}