Published March 25, 2019
| Version 1.0.0
Dataset
Open
RefleX: X-ray diffraction images dataset
- 1. Institute of Computing Science, Poznan University of Technology, Poznan, 60-965, Poland
- 2. Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA 22901, USA
Contributors
Other:
- 1. Institute of Computing Science, Poznan University of Technology, Poznan, 60-965, Poland
Description
Image dataset prepared for the RefleX study, described in "Detecting anomalies in X-ray diffraction images using Convolutional Neural Networks". The dataset contains 6311 X-ray diffraction images in 1024x1024 png format (reflex_img_1024_inter_nearest.zip). The repository also contains a file mapping each image to a set of labels (labels.csv) and files describing the assignment of each image to training, validation, and testing sets (labels_train.csv, labels_val.csv, labels_test.csv).
The dataset can be used for multi-label classification. Each diffraction image can exhibit any combination of seven classes: Ice ring, Diffuse Scattering, Background Ring, Non-uniform Detector, Loop Scattering, Strong Background, and Artifact.
Files
labels.csv
Files
(3.6 GB)
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md5:f7d888b5d9e788d2ca2fa592c130db38
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md5:73ab09f51465953dfc3b69622c1789c5
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18.2 kB | Preview Download |
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md5:d4f3daceca73c448b268a7343a76adc9
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144.3 kB | Preview Download |
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md5:d260f427180d64b4a1442bb6362ada33
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18.1 kB | Preview Download |
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md5:1b7a22ee79fe7f0690fa09f2aa9d1b12
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3.6 GB | Preview Download |