If you are curious about the methods in the GUI, try clicking the header icons which should take you to the relevant documentation.Īs always, reach out to us on Gitter chat or open an issue if you have questions, bug reports of feature requests! Oct-07-2021: SimBA version 1.31 release Pre-print: Simple Behavioral Analysis (SimBA) – an open source toolkit for computer classification of complex social behaviors in experimental animalsĪlthough core methods remain, the SimBA code and documentation has sprawled significantly. If you require access to download the legacy branch, please contact us on Gitter for access. If you are using the legacy SimBAxTF branch, please transition to the currently supported branch. To receive support, you must download the most up-to-date SimBA version ( pip install simba-uw-tf-dev). We are are no longer supporting the legacy SimBAxTF branch, which required TensorFlow.
Scenario tutorials Scenario 1: Building classifiers from scratch Scenario 2: Using a classifier on new experimental data Scenario 3: Updating a classifier with further annotated data Scenario 4: Analyzing and adding new Experimental data to a previously started project Installation ⚙️ Tutorial 📚 Resource 💾 API reference Models SimBA visualization examples Labelled images Tracking weights Golden Lab webpage License 📃 References 📜 Contributors 🤼 README.md
SimBA (Simple Behavioral Analysis) Apr-04-2023: SimBA version 1.55 release Oct-07-2021: SimBA version 1.31 release Regions of Interest (ROIs) in SimBA Feb-08-2021: SimBA version 1.3 release Selected New Features June-12-2020: SimBA version 1.2 release New Features April-25-2020: SimBA pre-print manuscript release March-05-2020: SimBA version 1.1 release New Features What is SimBA? Mouse Rat SimBA GUI workflow Pipeline 👷 Documentation: General methods Step 1: Pre-process videos Step 2: Create tracking model and generate pose-estimation data Step 3: Building classfier(s) Step 4: Analysis/Visualization Click here for the full generic tutorial on building classifiers in SimBA.
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