Whistler segmentation training dataset
<p>Generated whistlers with pixel-segmented separate masks for each trace.</p> <p>File naming:<br> - train_images.tar.gz contains all the train images (>10 GB)<br> - example_images.zip contains 5 spectrograms and the corresponding segmentation masks. (~5 MB))<br> - {id}_rothera_{n}_y.png, {id}_rothera_x.png, where {id} is a unique ID to match the masks and the spectrogram image, {n} enumerates the whistler traces within a spectrogram. Files ending _y.png are the bitmask images, while the _x.png files are the spectrograms.</p> <p>Opening the bitmasks in a regular image viewer might show only a black image. In this case, opening as a matrix (eg via matplotlib or opencv in python), converting to binary values, and visualizing them can help.</p> <p>To be updated upon acceptance of our research paper.</p>
ShareScore
32/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0
ScienceDex for faculty
Your academic CV and NIH biosketch
Make your CV in your school's format and your NIH biosketch from it, then download both as Word files.