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{
"schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20240725.json",
"version": "0.0.4",
"changelog": {
"0.0.4": "enhanced metadata with improved descriptions and task specification",
"0.0.3": "update to huggingface hosting",
"0.0.2": "update large file yml",
"0.0.1": "Initial version"
},
"monai_version": "1.4.0",
"pytorch_version": "2.4.0",
"numpy_version": "1.24.4",
"required_packages_version": {
"pytorch-ignite": "0.4.11",
"pyyaml": "6.0.2"
},
"supported_apps": {},
"name": "Medical Image Classification Template",
"task": "Template for 2D Medical Image Classification",
"description": "A comprehensive template for developing 2D medical image classification models, featuring a modular architecture and standardized training pipeline. The template supports single-channel 128x128 pixel input images and outputs 4-class probability distributions, serving as a foundation for custom medical image classification tasks.",
"authors": "Yun Liu",
"copyright": "Copyright (c) 2023 MONAI Consortium",
"network_data_format": {
"inputs": {
"image": {
"type": "image",
"format": "magnitude",
"modality": "none",
"num_channels": 1,
"spatial_shape": [
128,
128
],
"dtype": "float32",
"value_range": [],
"is_patch_data": false,
"channel_def": {
"0": "image"
}
}
},
"outputs": {
"pred": {
"type": "probabilities",
"format": "classes",
"num_channels": 4,
"spatial_shape": [
1,
4
],
"dtype": "float32",
"value_range": [
0,
1,
2,
3
],
"is_patch_data": false,
"channel_def": {
"0": "background",
"1": "circle",
"2": "triangle",
"3": "rectangle"
}
}
}
}
}
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