Developer API

sleap.instance	Data structures for all labeled data contained with a SLEAP project.
sleap.message	Module with classes for sending and receiving messages between processes.
sleap.skeleton	Implementation of skeleton data structure and API.
sleap.util	A miscellaneous set of utility functions.
sleap.io.asyncvideo	Support for loading video frames (by chunk) in background process.
sleap.io.convert	Command line utility for converting between various dataset formats.
sleap.io.dataset	A SLEAP dataset collects labeled video frames, together with required metadata.
sleap.io.legacy	Module for legacy LEAP dataset.
sleap.io.pathutils	Utilities for working with file paths.
sleap.io.video	Video reading and writing interfaces for different formats.
sleap.io.videowriter	Module for writing avi/mp4 videos.
sleap.io.visuals	Module for generating videos with visual annotation overlays.
sleap.io.format.adaptor	File format adaptor base class.
sleap.io.format.coco	Adaptor for reading COCO keypoint detection datasets.
sleap.io.format.deeplabcut	Adaptor for reading DeepLabCut datasets.
sleap.io.format.deepposekit	Adaptor for reading DeepPoseKit datasets (HDF5).
sleap.io.format.dispatch	Dispatcher for dynamically supporting multiple dataset file formats.
sleap.io.format.filehandle	File object which can be passed to adaptors.
sleap.io.format.genericjson	Adaptor for reading and writing any generic JSON file.
sleap.io.format.hdf5	Adaptor for reading/writing SLEAP datasets as HDF5 (including slp).
sleap.io.format.labels_json	Adaptor for reading/writing old, JSON dataset format (kind of deprecated).
sleap.io.format.leap_matlab	Adaptor to read (not write) LEAP MATLAB data files.
sleap.io.format.main	Read/write for multiple dataset formats.
sleap.io.format.sleap_analysis	Adaptor to read and write analysis HDF5 files.
sleap.io.format.text	Adaptor for reading and writing any generic text file.
sleap.nn.callbacks	Training-related tf.keras callbacks.
sleap.nn.evals	Evaluation utilities for measuring pose estimation accuracy.
sleap.nn.heads	Model head definitions for defining model output types.
sleap.nn.inference	Inference pipelines and utilities.
sleap.nn.losses	Custom loss functions and metrics.
sleap.nn.model	This module defines the main SLEAP model class for defining a trainable model.
sleap.nn.monitor	GUI for monitoring training progress interactively.
sleap.nn.paf_grouping	This module provides a set of utilities for grouping peaks based on PAFs.
sleap.nn.peak_finding	This module contains TensorFlow-based peak finding methods.
sleap.nn.system	Utilities for working with the physical system (e.g., GPUs).
sleap.nn.tracking	Tracking tools for linking grouped instances over time.
sleap.nn.training	Training functionality and high level APIs.
sleap.nn.utils	This module contains generic utilities used for training and inference.
sleap.nn.viz	Visualization and plotting utilities.
sleap.nn.tracker.components	Functions/classes used by multiple trackers.
sleap.nn.tracker.kalman	Module to use Kalman filters for tracking instance identities.
sleap.nn.config.data
sleap.nn.config.model
sleap.nn.config.optimization
sleap.nn.config.outputs
sleap.nn.config.training_job	Serializable configuration classes for specifying all training job parameters.
sleap.nn.config.utils	Utilities for config building and validation.
sleap.nn.architectures.common	Common utilities for architecture and model building.
sleap.nn.architectures.encoder_decoder	Generic encoder-decoder fully convolutional backbones.
sleap.nn.architectures.hourglass	This module provides a generalized implementation of (stacked) hourglass.
sleap.nn.architectures.hrnet	(Higher)HRNet backbone.
sleap.nn.architectures.leap	This module provides a generalized implementation of the LEAP CNN.
sleap.nn.architectures.pretrained_encoders	Encoder-decoder backbones with pretrained encoder models.
sleap.nn.architectures.resnet	ResNet-based backbones.
sleap.nn.architectures.unet	This module provides a generalized implementation of UNet.
sleap.nn.architectures.upsampling	This module defines common upsampling layer stack configurations.
sleap.nn.data.augmentation	Transformers for applying data augmentation.
sleap.nn.data.confidence_maps	Transformers for confidence map generation.
sleap.nn.data.dataset_ops	Transformers for dataset (multi-example) operations, e.g., shuffling and batching.
sleap.nn.data.edge_maps	Transformers for generating edge confidence maps and part affinity fields.
sleap.nn.data.general	General purpose transformers for common pipeline processing tasks.
sleap.nn.data.grouping	Group inference results (“examples”) by frame.
sleap.nn.data.inference	Transformers for performing inference.
sleap.nn.data.instance_centroids	Transformers for finding instance centroids.
sleap.nn.data.instance_cropping	Transformers for cropping instances for topdown processing.
sleap.nn.data.normalization	Transformers for normalizing data formats.
sleap.nn.data.offset_regression	Utilities for creating offset regression maps.
sleap.nn.data.pipelines	This module defines high level pipeline configurations from providers/transformers.
sleap.nn.data.providers	Data providers for pipeline I/O.
sleap.nn.data.resizing	Transformers for image resizing and padding.
sleap.nn.data.training	Transformers and utilities for training-related operations.
sleap.nn.data.utils	Miscellaneous utility functions for data processing.
sleap.info.align	Functions to align instances.
sleap.info.feature_suggestions	Module for generating lists of frames using frame features, pca, kmeans, etc.
sleap.info.labels	Command line utility which prints data about labels file.
sleap.info.metrics	Module for producing prediction metrics for SLEAP datasets.
sleap.info.summary	Module for getting a series which gives some statistic based on labeling data for each frame of some labeled video.
sleap.info.trackcleaner	CLI for TrackCleaner (mostly deprecated).
sleap.info.write_tracking_h5	Generate an HDF5 file with track occupancy and point location data.