DatamintAPI

Contents

  • Installation
    • Next Steps
  • Setup API key
    • Method 1: Command-line tool (recommended)
    • Method 2: Environment variable
    • Method 3: APIHandler constructor
  • Command-line tools
    • Configuring the Datamint settings
    • Uploading DICOMs/resources to Datamint server
      • Example using include and exclude extensions options:
      • Uploading segmentations along with the resources
      • All available options
  • Client Python API
    • Upload DICOMs or other resources
      • Upload resource files
      • Group up resources using channels
      • Upload, anonymize and add a label
      • Changing the uploaded filename
    • Download resources
    • Publishing resources
    • Upload segmentation
  • Running Experiments
    • Manual logging
      • Manual Summary logging
      • Manual Model details logging
    • Best Practices
  • Pytorch integration
    • Dataset

Python Modules Reference

  • datamint.APIHandler
    • APIHandler
      • APIHandler.add_annotations()
      • APIHandler.add_frame_category_annotation()
      • APIHandler.add_image_category_annotation()
      • APIHandler.add_line_annotation()
      • APIHandler.create_project()
      • APIHandler.create_user()
      • APIHandler.delete_project()
      • APIHandler.delete_resources()
      • APIHandler.download_project()
      • APIHandler.download_resource_file()
      • APIHandler.download_resource_frame()
      • APIHandler.get_annotation_worklist()
      • APIHandler.get_annotation_worklist_by_id()
      • APIHandler.get_annotations()
      • APIHandler.get_channels()
      • APIHandler.get_datasets()
      • APIHandler.get_experiment_by_name()
      • APIHandler.get_project_by_id()
      • APIHandler.get_project_by_name()
      • APIHandler.get_projects()
      • APIHandler.get_resource_annotations()
      • APIHandler.get_resources()
      • APIHandler.get_resources_by_ids()
      • APIHandler.get_resources_by_project()
      • APIHandler.get_users()
      • APIHandler.publish_resources()
      • APIHandler.update_annotation_worklist()
      • APIHandler.upload_resources()
      • APIHandler.upload_segmentations()
    • DatamintException
    • ResourceFields
    • ResourceNotFoundError
    • ResourceStatus
  • Dataset Classes
    • DatamintDataset
      • DatamintDataset.__getitem__()
      • DatamintDataset.frame_categories_set
      • DatamintDataset.frame_labels_set
      • DatamintDataset.get_annotations()
      • DatamintDataset.get_dataloader()
      • DatamintDataset.get_framelabel_distribution()
      • DatamintDataset.get_segmentationlabel_distribution()
      • DatamintDataset.image_categories_set
      • DatamintDataset.image_labels_set
      • DatamintDataset.segmentation_labels_set
    • DatamintBaseDataset
      • DatamintBaseDataset.__getitem__()
      • DatamintBaseDataset.__repr__()
      • DatamintBaseDataset.frame_categories_set
      • DatamintBaseDataset.frame_labels_set
      • DatamintBaseDataset.get_annotations()
      • DatamintBaseDataset.get_dataloader()
      • DatamintBaseDataset.get_framelabel_distribution()
      • DatamintBaseDataset.get_segmentationlabel_distribution()
      • DatamintBaseDataset.image_categories_set
      • DatamintBaseDataset.image_labels_set
      • DatamintBaseDataset.segmentation_labels_set
    • DatamintDatasetException
  • datamint.Experiment
    • Experiment
      • Experiment.finish()
      • Experiment.get_dataset()
      • Experiment.get_enviroment_info()
      • Experiment.log_classification_predictions()
      • Experiment.log_dataset_stats()
      • Experiment.log_metric()
      • Experiment.log_metrics()
      • Experiment.log_model()
      • Experiment.log_segmentation_predictions()
      • Experiment.log_semantic_seg_predictions()
      • Experiment.log_summary()
      • Experiment.set_model()
      • Experiment.update_summary_metrics()
DatamintAPI
  • Documentation
  • View page source

Datamint

Documentation

Version: 1.3.0

From inception to completion, Datamint is your reliable partner. It assists from the very first day when you make your data available to your team, right up to the moment you’re set to launch your model.

Datamint

  • Homepage

  • Datamint Platform

  • Github

Contents

  • Installation
    • Next Steps
  • Setup API key
    • Method 1: Command-line tool (recommended)
    • Method 2: Environment variable
    • Method 3: APIHandler constructor
  • Command-line tools
    • Configuring the Datamint settings
    • Uploading DICOMs/resources to Datamint server
  • Client Python API
    • Upload DICOMs or other resources
    • Download resources
    • Publishing resources
    • Upload segmentation
  • Running Experiments
    • Manual logging
    • Best Practices
  • Pytorch integration
    • Dataset

Python Modules Reference

  • datamint.APIHandler
  • Dataset Classes
  • datamint.Experiment

Indices and tables

  • Index

  • Module Index

  • Search Page

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