DeepDanbooru is a deep learning tool for tagging anime-style images with Danbooru-style tags. It uses a pre-trained convolutional neural network to analyze images and predict tags identifying characters, attributes, and artwork details.
The project provides a complete pipeline for training custom tag recognition models. Users can prepare datasets by downloading tag definitions from a remote Danbooru server using authenticated API requests, then store image-tag pairs in a structured SQLite database. The training workflow supports filtering datasets by rating or score criteria, configuring hyperparameters, and running optimization to recognize user-defined tags.
The tool also includes a command-line interface for repeated command execution with configurable intervals, enabling automated continuous workflows.