DeepDanbooru

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DeepDanbooru is an AI-based multi-label image classification system that estimates tags for anime-style girl images. It is implemented using TensorFlow and is open-source.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is DeepDanbooru?

DeepDanbooru is an AI-based multi-label image classification system specifically designed for anime-style girl images. Built with TensorFlow, it provides a robust solution for estimating tags on visual content. The system is open-source and available on GitHub, allowing developers and researchers to access and modify its codebase. Users can prepare their own datasets or utilize tools like DanbooruDownloader to acquire data. It supports creating training projects, downloading tags from Danbooru, filtering datasets, and training custom models. The tool is ideal for those looking to categorize and analyze large collections of anime imagery with AI-driven tagging.

Best used for

Ideal for developers and data scientists who need to automatically classify anime-style images, train custom image tagging models, and analyze large visual datasets. Especially valuable for researchers or content creators working with anime imagery who require precise, AI-driven multi-label annotation.

Common actions

classify images

tag images

train AI models

analyze anime images

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Capabilities

Key features

AI image classification
Multi-label tagging
TensorFlow implementation
Custom model training
Danbooru tag integration
Dataset preparation tools

Target Audience

developerdata scientist

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What kind of images can DeepDanbooru classify?

DeepDanbooru is specifically designed for AI-based multi-label classification of anime-style girl images. While it's possible to adapt it, its core functionality and training are optimized for this particular visual content.

What are the technical requirements to run DeepDanbooru?

DeepDanbooru requires Python 3.11 and several packages including Click, numpy, requests, scikit-image, six, and TensorFlow. Users can install these dependencies via a provided requirements.txt file or directly with pip, optionally including TensorFlow.

Can I use my own dataset with DeepDanbooru?

Yes, DeepDanbooru supports using custom datasets. You need to structure your data with images in specific subfolders and provide a SQLite database file containing post metadata, including image IDs, MD5 hashes, file extensions, and tag strings.

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Coding & Development › Open Source & Models

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