{ "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" } } } } }