pytagit 0.1.4

Interactive tool for image tagging with the human in the loop

PyTagit

PyTagit is a human-in-the-loop tool for large-scale image classification.
Install and launch it with:

# install
pip install pytagit

# run the program
pytagit

If you use PyTagit, please cite us:

# citation

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Features

At startup, all images are unclassified. You can assign them via drag-and-drop:

Start by assigning a few examples per class. Then, apply:

• Random Forest or k-NN to classify the rest.
• Visit each class and click to mark correct predictions. Once clicked, the border will become red.
• Repeat the process to reclassify using the verified samples.

For accelerated labeling, use:

Interactive t-SNE

Draw a decision boundary directly on a 2D feature map to assign multiple samples:

Out-of-Distribution Detection

Useful for quality control scenarios: find samples close to a class using feature-based OOD:

To classify all samples, use Random Forest with a confidence threshold of 0.