# Documentation ## Documentation - [Introduction](https://docs.segments.ai/readme.md) - [Getting started](https://docs.segments.ai/tutorials/getting-started.md): This tutorial shows how you can create a dataset, upload some images in it, label and review them, and finally create a dataset release to export your data. - [Python SDK quickstart](https://docs.segments.ai/tutorials/python-sdk-quickstart.md): On the Segments.ai web platform you can create datasets, upload samples, create releases and download labels. All of these - and more - can also be done programmatically with the Python SDK. - [Model-assisted labeling](https://docs.segments.ai/tutorials/model-assisted-labeling.md) - [Label images](https://docs.segments.ai/how-to-annotate/label-images.md) - [View and navigate in the image interfaces](https://docs.segments.ai/how-to-annotate/label-images/view-and-navigate-in-the-image-interfaces.md) - [Image interface settings](https://docs.segments.ai/how-to-annotate/label-images/image-interface-settings.md) - [Image segmentation interface](https://docs.segments.ai/how-to-annotate/label-images/image-segmentation-interface.md) - [Image vector interface](https://docs.segments.ai/how-to-annotate/label-images/image-vector-interface.md) - [Label 3D point clouds](https://docs.segments.ai/how-to-annotate/label-3d-point-clouds.md) - [View and navigate in the 3D interface](https://docs.segments.ai/how-to-annotate/label-3d-point-clouds/view-and-navigate-in-the-3d-interface.md) - [Upload, view, and overlay images](https://docs.segments.ai/how-to-annotate/label-3d-point-clouds/upload-view-and-overlay-images.md) - [3D interface settings](https://docs.segments.ai/how-to-annotate/label-3d-point-clouds/3d-interface-settings.md) - [3D point cloud cuboid interface](https://docs.segments.ai/how-to-annotate/label-3d-point-clouds/3d-point-cloud-cuboid-interface.md) - [3D point cloud vector interface](https://docs.segments.ai/how-to-annotate/label-3d-point-clouds/3d-point-cloud-vector-interface.md) - [3D point cloud segmentation interface](https://docs.segments.ai/how-to-annotate/label-3d-point-clouds/3d-point-cloud-segmentation-interface.md) - [Merged point cloud view (for static objects)](https://docs.segments.ai/how-to-annotate/label-3d-point-clouds/merged-point-cloud-view-for-static-objects.md) - [Batch mode (for dynamic objects)](https://docs.segments.ai/how-to-annotate/label-3d-point-clouds/batch-mode-for-dynamic-objects.md) - [Smart cuboid propagation](https://docs.segments.ai/how-to-annotate/label-3d-point-clouds/smart-cuboid-propagation.md) - [Tips for labeling cuboid sequences](https://docs.segments.ai/how-to-annotate/label-3d-point-clouds/tips-for-labeling-cuboid-sequences.md): This page describes some tips and tricks to label cuboids in point cloud sequences faster. - [Label sequences of data](https://docs.segments.ai/how-to-annotate/label-sequences-of-data.md) - [Track timeline](https://docs.segments.ai/how-to-annotate/label-sequences-of-data/track-timeline.md) - [Use track IDs in sequences](https://docs.segments.ai/how-to-annotate/label-sequences-of-data/use-track-ids-in-sequences.md) - [Use keyframe interpolation](https://docs.segments.ai/how-to-annotate/label-sequences-of-data/use-keyframe-interpolation.md) - [Playback](https://docs.segments.ai/how-to-annotate/label-sequences-of-data/playback.md) - [Prefetch](https://docs.segments.ai/how-to-annotate/label-sequences-of-data/prefetch.md) - [Label multi-sensor data](https://docs.segments.ai/how-to-annotate/label-multi-sensor-data.md) - [3D to 2D Projection](https://docs.segments.ai/how-to-annotate/label-multi-sensor-data/3d-to-2d-projection.md) - [Sensors list](https://docs.segments.ai/how-to-annotate/label-multi-sensor-data/sensors-list.md) - [Annotate object links](https://docs.segments.ai/how-to-annotate/annotate-object-links.md) - [Use the warning system](https://docs.segments.ai/how-to-annotate/use-the-warning-system.md) - [Customize hotkeys](https://docs.segments.ai/how-to-annotate/customize-hotkeys.md) - [Object filtering](https://docs.segments.ai/how-to-annotate/object-filtering.md) - [Object locking](https://docs.segments.ai/how-to-annotate/object-locking.md) - [Add collaborators to a dataset](https://docs.segments.ai/guides/add-collaborators-to-a-dataset.md) - [Create an organization](https://docs.segments.ai/guides/create-an-organization.md): Organizations are shared accounts where teams can easily collaborate across many datasets. - [Dataset configuration](https://docs.segments.ai/guides/configure-label-editor.md) - [Configure the label editor](https://docs.segments.ai/guides/configure-label-editor/configure-the-label-editor.md) - [Configure rules](https://docs.segments.ai/guides/configure-label-editor/configure-rules.md): In the dataset settings, rules can be configured to help spot potential issues early by raising warnings. Currently, the rules that can be added are only applicable to cuboids. - [Configure region of interest](https://docs.segments.ai/guides/configure-label-editor/configure-region-of-interest.md): In 3D point cloud datasets, you can now define a Region of Interest to focus labeling efforts on a limited zone centered around the ego vehicle. The Region of Interest can be configured in the dataset - [Dataset tags](https://docs.segments.ai/guides/configure-label-editor/dataset-tags.md) - [Customize label queue](https://docs.segments.ai/guides/customize-label-queue.md) - [Search within a dataset](https://docs.segments.ai/guides/search-functionality.md): With the search bar, you can search for samples by their name, metadata attributes, and label content. - [Clone a dataset](https://docs.segments.ai/guides/clone-a-dataset.md) - [Work with issues](https://docs.segments.ai/guides/work-with-issues.md) - [Bulk change label status](https://docs.segments.ai/guides/bulk-change-label-status.md) - [Manage QA processes](https://docs.segments.ai/guides/manage-qa-processes.md): How Segments.ai helps to streamline QA, how to set up a linting process and which additional features can be leveraged - [Open a sample in read-only mode](https://docs.segments.ai/guides/open-a-sample-in-read-only-mode.md) - [Caching assets](https://docs.segments.ai/guides/caching-assets.md) - [Import data](https://docs.segments.ai/how-to-integrate/import-data.md) - [Cloud integrations](https://docs.segments.ai/how-to-integrate/import-data/cloud-integration.md) - [Export data](https://docs.segments.ai/how-to-integrate/export.md) - [Structure of the release file](https://docs.segments.ai/how-to-integrate/export/structure-of-the-release-file.md) - [Exporting image annotations to different formats](https://docs.segments.ai/how-to-integrate/export/exporting-image-annotations-to-different-formats.md) - [Create an API key](https://docs.segments.ai/how-to-integrate/create-an-api-key.md) - [Upload model predictions](https://docs.segments.ai/how-to-integrate/upload-model-predictions.md) - [Set up webhooks](https://docs.segments.ai/how-to-integrate/webhooks.md): Listen for events on your account so your integration can automatically trigger reactions. - [Main concepts](https://docs.segments.ai/background/main-concepts.md) - [Sequences](https://docs.segments.ai/background/sequences.md) - [Label queue mechanics](https://docs.segments.ai/background/label-queue-mechanics.md): The label and review queue make it easy for teams to efficiently work on a dataset together. - [Labeling metrics](https://docs.segments.ai/background/labeling-metrics.md) - [3D Tiles](https://docs.segments.ai/background/3d-tiles.md) - [WebGPU in Linux](https://docs.segments.ai/background/webgpu-in-linux.md) - [Security](https://docs.segments.ai/background/security.md) - [Task types](https://docs.segments.ai/reference/sample-and-label-types.md) - [Sample formats](https://docs.segments.ai/reference/sample-types.md) - [Supported file formats](https://docs.segments.ai/reference/sample-types/supported-file-formats.md) - [Label formats](https://docs.segments.ai/reference/label-types.md) - [Categories and attributes](https://docs.segments.ai/reference/categories-and-attributes.md) - [API](https://docs.segments.ai/reference/api.md) --- # Agent Instructions This documentation is published with GitBook. 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