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This project is to develop an OBS Python script able to automatically trigger OBS to record videos of the set-up scenes of a given duration in a selected time frame. Additionally, experimental metadata for the recorded experiment can be manually input by the researcher through the OBS graphical interface and exported automatically as a table together with the video.

The script will create the wanted videos and a metadata table matched by a video ID, which if left unchanged, will keep increasing by 1 at every iteration of the script. This video ID can be used to record a unique recording session.

Object Detection with Grouped Instances. See https://github.com/ameroyer/ODGI for the official clean version of the code.

Collection of preprocessing utils for various Computer Vision datasets . Also includes code for integration with TFRecords and tf.data.Dataset pipeline. Mirror of https://github.com/ameroyer/TFDatasets

A test application for controlling a Fluigent Aria (https://www.fluigent.com/de/forschung/instrumente/aria/) device under NIS Elements macro. A python TCP listens NIS macros to remote control the Aria system using the Fluigent's SDK (https://github.com/Fluigent/aria-sdk).

A test application for controlling a Fluigent Aria (https://www.fluigent.com/de/forschung/instrumente/aria/) device under NIS Elements macro. A python TCP listens NIS macros to remote control the Aria system using the Fluigent's SDK (https://github.com/Fluigent/aria-sdk).

Generates Second Order Networks with prescribed second order motif frequencies This is the local version of Nykamp code with our patches used in the Paper Guzman et al. Science 2016

Homogenized Yarn-Level Cloth - microscale simulation and fitting

Code to simulate and analyze IBD-sharing between samples of a two-dimensional population.

Originally created by Christoph Sommer (ISTA) for AIAI meeting 10/06/2024

Probabilistic Image Colorization. Mirror of https://github.com/ameroyer/PIC

MALU - Monitoring and Accounting of License Usage.

Filter cellpose segmentations and create filtered tif and csv output of the segmentation

(ReCA) Recommendation with Context Awareness using Multi-Environment Markov Decision Processes. Mirror of https://github.com/ameroyer/ReCA

The hlab environment. Contains all of our dependencies, custom control and analysis code.

A collection of pipelines that can be used for different bioinformatics analyses on the IST cluster.