| { | |
| "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20240725.json", | |
| "version": "0.6.4", | |
| "changelog": { | |
| "0.6.4": "enhance metadata with improved descriptions", | |
| "0.6.3": "update to huggingface hosting", | |
| "0.6.2": "enhance readme for nccl timout issue", | |
| "0.6.1": "fix multi-gpu issue", | |
| "0.6.0": "use monai 1.4 and update large files", | |
| "0.5.9": "update to use monai 1.3.1", | |
| "0.5.8": "update readme to add memory warning", | |
| "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": "1.4.0", | |
| "pytorch_version": "2.4.0", | |
| "numpy_version": "1.24.4", | |
| "required_packages_version": { | |
| "cucim-cu12": "24.6.0", | |
| "pandas": "2.2.1", | |
| "torchvision": "0.19.0", | |
| "pytorch-ignite": "0.4.11", | |
| "tensorboard": "2.17.0" | |
| }, | |
| "supported_apps": {}, | |
| "name": "Pathology Tumor Detection", | |
| "task": "Metastatic Tissue Detection in Whole-Slide Pathology Images", | |
| "description": "A deep learning model for detecting metastatic tissue in whole-slide pathology images. The model processes 224x224 pixel RGB patches and provides probability scores for metastasis detection. Trained on the Camelyon16 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" | |
| } | |
| } | |
| } | |
| } | |
| } | |