Tag images with labels
Find similar images using tags and images
Simulate wearing clothes on images
Generate 3D depth map visualization from an image
Detect if an image is AI-generated
Browse Danbooru images with filters and sorting
Facial expressions, 3D landmarks, embeddings, recognition.
Generate depth map from an image
Extract text from images using OCR
Compute normals for images and videos
Generate saliency maps from RGB and depth images
Apply ZCA Whitening to images
streamlit application to for ANPR/ALPR
DeepDanbooru is an AI-powered tool designed to tag images with labels automatically. It leverages deep learning to analyze and categorize visual content, making it a valuable resource for organizing and searching image collections. DeepDanbooru is particularly popular for its ability to efficiently process large batches of images and apply relevant tags based on their content.
• AI-Powered Tagging: Automatically identifies and applies tags to images based on their content.
• Customizable Models: Supports the use of pre-trained models or custom-trained models for specific tagging needs.
• Integration with Danbooru: Designed to work seamlessly with Danbooru databases, allowing for easy migration and use of existing metadata.
• Efficiency: Can process multiple images quickly, making it suitable for large-scale tagging operations.
• Developer-Friendly: Includes an API for integration into custom workflows or applications.
What is the difference between DeepDanbooru and Danbooru?
DeepDanbooru is an AI-powered tagging tool built to work alongside Danbooru databases, while Danbooru itself is a booru-style imageboard and tagging platform.
Can DeepDanbooru process multiple images at once?
Yes, DeepDanbooru is designed to handle bulk image processing, making it efficient for large collections.
How accurate is DeepDanbooru's tagging?
The accuracy of DeepDanbooru depends on the quality of the AI model used. While it can achieve high accuracy, some tags may require manual review and adjustment to ensure correctness.