Client Python API

Intermediate

This chapter describes how to use the Api class in Python, to interact with the Datamint API. Before continuing, you may want to check the setup-api-key section to easily set up your API key, if you haven’t done so yet.

• Getting Started with the API Client
• Working with Resources
  • Upload resource files
  • List and filter resources
  • Upload with options
  • Attach metadata
  • Download resources
  • Publishing resources
  • Deleting and restoring resources
  • Ranking unlabeled resources
  • Iterate resources and annotations of a dataset
• Working with Annotations
  • Inspect annotations from a resource
  • Filter annotations by status and source
  • Deleted annotations
  • Upload segmentations
  • Multi-class segmentations
  • Volume segmentations
  • Upload geometry annotations (bounding boxes, lines)
  • Upload classification annotations
  • Inspect annotation entities
  • Measuring inter-annotator agreement
• Working with Projects
  • Create and manage projects
  • Project helper methods
  • Project-scoped dataset splits
  • Deleting and restoring projects
• Working with Channels
• Importing External Dataset Formats
• Working with Models
  • Register and list models
  • Log a model manually
  • Inspect versions and metrics
  • Find which projects a model belongs to
  • Model registry (MLflow) operations
  • Clone a model to another project
  • Deploy a registered model
• Working with Validation Studies
  • Create a draft study
  • Add readers and manage resources
• Working with Users