P

python

Video processing pipeline for the pre-processing of fish-eye distorted videos for behavioral analysis. The videos need to be renamed, cropped, and corrected for distortion before being used in the behavioral analysis pipeline for training and prediction.

Make the measurements of PIN lateralization automated by measuring the intensity at the basal and lateral side of each cell in the endodermis of the rot tip of Arabidopsis.

Conversion and visualization of TSOAX data

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

Introductory workshop for the use of Jupyter notebooks for image analysis pipelines by the Imaging and Optics Facility (IOF) team at ISTA.

A brief illustration of how Marimo can be useful for image analysis pipelines and user-ready deliverable applications. Originally presented at BioOptics meeting 2024

This program allows a series of tests over illumination sources for Zeiss widefield and confocal microscopes running Zen Blue. It is possibe to test:

Short term stability: According to QUAREP-LiMi full test is completed in 5 minutes for each illumination line, testing powers every second. Long term stability: The QUAREP-LiMi protocol stablishes 2h tests per line, with measurement intervals of 30s. To allow this for multiple lines this program interleaves the tests for all lines every interval, allowing the full check to be completed in a single run. Linearity (response): To analyze the linearity -or response curve- of each light source the powers are measured for a series of set powers. These tests can be performed for the desired lines and for different test conditions.

Collection of Imaris Python(3) Extensions from the Imaging and Optics Facility (IOF), Institute of Science and Technology Austria (ISTA)

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.

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

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