SLEAP v1.1.3
Release of SLEAP v1.1.3.
Includes several bug fixes and documentation improvements.
Full changelog
- #498: Fix training when frames have no instances (fixes #480).
- #503: Fix errors occurring sometimes after training (fixes part of #500)
- #505: Add miscellaneous utilities/fixes
- Add
--open-in-gui
flag tosleap-track
to launch GUI on predictions - Add
PredictedInstance.numpy()
to convert predicted instances to numpy arrays - Fix visualization during single instance training
- Add
Skeleton.find_neighbors()
to return parents and children of a node - Fix serialization of
MediaVideo
after loading fromsleap.load_video()
orsleap.load_file()
. - Add
Instance.fill_missing()
to initialize missing nodes (e.g., after importing from DLC)
- Add
- #501/#519/#524: Fix multi-size video support in training and inference (fixes #510, #516, #517)
- #523: Fix using
sleap-track
with zipped model folders - Revamped docs and notebooks to clarify the Colab-based workflow (especially Training and inference on your own data using Google Drive), which are now linked from the GUI as well
- Fix regression in v1.1.2 (#528)
Installing
We recommend using Miniconda to install and manage your Python environments. This will also make GPU support work transparently without installing additional dependencies.
Using Conda (Windows/Linux)
- Delete any existing environment and start fresh (recommended):
conda env remove -n sleap
- Create new environment
sleap
(recommended):
conda create -n sleap -c sleap sleap=1.1.3
Or to update inside an existing environment:
conda install -c sleap sleap=1.1.3
Using PyPI (Windows/Linux/Mac)
- Create a new conda environment (recommended):
conda create -n sleap python=3.6
conda activate sleap
- Install from PyPI:
pip install sleap==1.1.3
Or to upgrade an existing installation:
pip install --upgrade --force-reinstall sleap==1.1.3
From source (development)
- Clone the repository at this tag:
git clone https://github.com/murthylab/sleap --branch v1.1.3 sleap_v1.1.3
cd sleap_v1.1.3
- Install conda environment and activate:
conda install -f environment.yml -n sleap_v1.1.3
conda activate sleap_v1.1.3
- Changes made in the code will be immediately reflected when running SLEAP in this environment.