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Download HipRay/README.md from VictorButoi/flexray-data: direct link, hf CLI and curl.
- Browser
- Download file 1.29 kB
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https://huggingface.co/datasets/VictorButoi/flexray-data/resolve/main/HipRay/README.md
- Command line
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hf download hf://datasets/VictorButoi/flexray-data/HipRay/README.md
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curl -L -o README.md https://huggingface.co/datasets/VictorButoi/flexray-data/resolve/main/HipRay/README.md
1.29 kB
HipRay (hip joint radiographs)
Part of the FleXray data release. Repackaged from the original distribution at https://data.mendeley.com/datasets/zm6bxzhmfz/1 under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
Citation: Gut, D. X-ray images of the hip joints. Mendeley Data, V1 (2021). doi:10.17632/zm6bxzhmfz.1
Contents
- 139 samples (test: 21, train: 97, val: 21); one image and one label per sample.
images/*.png: 16-bit grayscale PNG, intensities in [0, 65535] map linearly to [0, 1].labels/: dense index map (PNG). Label ids/channels:0: background1: femurs2: hipsdataset.yml:fxr-datasetmanifest (schema version 1). Splits are the ones used in the FleXray paper;metadata.original_shapeis the source image shape.
Preprocessing
Every image was min-max normalized to [0, 1] per image, padded to a square with zeros (centered) and resized to 256 x 256 (area interpolation for images, nearest for labels). Labels were remapped from the source annotation to the dataset-native names listed above; the FleXray package maps those names into its label protocol at training time.
Usage
python -m pip install "flexray[train]"
fxr-dataset validate dataset.yml
fxr-dataset pack dataset.yml /data/flexray/HipRay