Malt empowers hackers to create labeled object detection datasets fast! You can quickly navigate through a video to find objects to label, and most impressively you can use a pre-trained TflowLite model to automatically place a bounding box around images!

I built this tool after spending too much time finding and labeling training images for Tensorflow. A common workflow while building new object detection models is to convert a video to a bunch of images, find the images with the object I am trying to label, train a model, then play the model back through a video to visually see what angles are not performing well. Malt incorporates this entire workflow into a single tool. It is particularly helpful to have the pre-trained model auto-label the images and then quickly adjust the bounding boxes that do not tightly fit the object. This project can be installed with pip through PyPi. This is a quick demo of the product:

I hope others will find this tool useful and will be able to provide feedback. I am launching Malt as a beta application. Version 1.0 will have a cleaned-up UI and a few more features.

@matthewlsessions This is a trainer must-have. Looks so cool. Congrats on the launch!

@matthewlsessions That's a brilliant idea - Congratulations on your launch! how long did it take you to develop the tool?

@matthewlsessions This is copl! Congrats on the launch! Cheers!

@audrey_galeon thank you!

Hey @farisa_ottaviano it took about three weeks to build!

@matthewlsessions congrats on the launch 🚀 this looks really nice ✌️