- Fill all fields in
settings.pyin the sectionBefore uploading to instance. - Implement the
convert_and_upload_supervisely_project()function inconvert.py. - Run
main.pyto upload the dataset to the Supervisely instance. - Check the result in the web interface, select an image for preview and check if annotations are having correct colors.
- Fill all required fields in
settings.pyin the sectionAfter uploading to instance. - If needed fill in optional fields in
settings.pyin the sectionAfter uploading to instance. - Run
main.pyto change thecustom_dataof the project and build the required files in the repository. - Fill necessary fields in
options.pyto configure visualizations. - Commit and push changes to the repository.
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The AeroScapes Semantic Segmentation Dataset
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