Segments.ai is the training data platform for computer vision engineers and labeling teams. Our powerful labeling interfaces, easy-to-use management features, and extensive API integrations help you iterate quickly between data labeling, model training and failure case discovery.
Walk through the Python SDK quickstart.
Please refer to the documentation for usage instructions.
Read our blog posts to learn more about the platform.
The most notable changes in v1.0 of the Python SDK compared to v0.73 include:
- Added Python type hints and better auto-generated docs.
- Improved error handling: functions now raise proper exceptions.
- New functions for managing issues and collaborators.
You can upgrade to v1.0 with pip install -—upgrade segments-ai. Please be mindful of following breaking changes:
- The client functions now return classes instead of dicts, so you should access properties using dot-based indexing (e.g.
dataset.description) instead of dict-based indexing (e.g.dataset[’description’]). - Functions now consistently raise exceptions, instead of sometimes silently failing with a print statement. You might want to handle these exceptions with a try-except block.
- Some legacy fields are no longer returned:
dataset.tasks,dataset.task_readme,dataset.data_type. - The default value of the
id_incrementargument inutils.export_dataset()andutils.get_semantic_bitmap()is changed from 1 to 0. - Python 3.6 and lower are no longer supported.
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