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{
"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"
}
}
}
}
}
|