In this workshop, we will present examples of what can be done with DeepLabCut, and attendees will make a start in labelling their own videos.
Amsterdam Movement Sciences
DeepLabCut is a newly developed, open-source toolbox code that builds on a state-of-the-art machine learning to allow a user to train a deep neural network with limited training data to precisely track user-defined landmarks in videos. It has mainly been applied in animal research (e.g. fruit flies, cheetahs, mice) but has also already been used for tracking movements in sports and pathologic conditions as well as for tracking muscle properties in ultrasound images. The advantage of this toolbox is that it is well-documented, and easy to use (for users afraid of coding, a full graphical user interface is even present). In this workshop, we will present examples of what can be done with DeepLabCut, and attendees will make a start in labelling their own videos in a cloud-based environment. (Max. 20 participants, first come first serve).
Start date: | |
---|---|
End date: | |
Time: | |
End time: | |
Max Participants: | 20 |
Location: | Online event |