Upload classification_template version 0.0.4
Browse files- configs/metadata.json +5 -4
configs/metadata.json
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@@ -1,7 +1,8 @@
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{
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"schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20240725.json",
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"version": "0.0.
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"changelog": {
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"0.0.3": "update to huggingface hosting",
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"0.0.2": "update large file yml",
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"0.0.1": "Initial version"
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@@ -14,9 +15,9 @@
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"pyyaml": "6.0.2"
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},
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"supported_apps": {},
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"name": "Classification Template",
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"task": "
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"description": "
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"authors": "Yun Liu",
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"copyright": "Copyright (c) 2023 MONAI Consortium",
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"network_data_format": {
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{
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"schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20240725.json",
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"version": "0.0.4",
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"changelog": {
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"0.0.4": "enhanced metadata with improved descriptions and task specification",
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"0.0.3": "update to huggingface hosting",
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"0.0.2": "update large file yml",
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"0.0.1": "Initial version"
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"pyyaml": "6.0.2"
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},
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"supported_apps": {},
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"name": "Medical Image Classification Template",
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"task": "Template for 2D Medical Image Classification",
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"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.",
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"authors": "Yun Liu",
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"copyright": "Copyright (c) 2023 MONAI Consortium",
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"network_data_format": {
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