Grounding DINO: Open-set object detection with vision-language grounding
Zero-shot object detection from text prompts.
Learn more about GroundingDINO
Grounding DINO is a vision-language transformer model for object detection that extends DINO with grounding capabilities through pre-training on image-text pairs. It uses a transformer architecture that jointly processes visual features and language embeddings to align object regions with textual descriptions. The model supports zero-shot detection by accepting arbitrary class names as text input, enabling detection of objects outside its training distribution. Common applications include open-world object detection, automated dataset annotation, and integration with segmentation models for instance-level tasks.
Vision-language alignment
Integrates DINO's detection backbone with grounded pre-training to directly map image regions to natural language descriptions, enabling detection based on arbitrary text queries rather than fixed class sets.
Zero-shot detection capability
Detects object classes not present in training data by leveraging language understanding, allowing the model to generalize to novel categories specified at inference time.
Transformer-based architecture
Uses a transformer encoder-decoder design that processes both visual and textual information jointly, enabling flexible reasoning about object-language relationships without separate classification heads per class.
pip install groundingdino-pyAlpha release reports 56.7 AP on COCO using multi-dataset training; release notes do not specify breaking changes, requirements, or upgrade steps.
- –Verify model compatibility if upgrading from v0.1.0-alpha; no migration guidance is provided in the notes.
- –Expect models trained on O365, VG, RefCOCO, COCO, OpenImage, Cap4M, and ODinW-35 datasets with reported benchmark performance.
Initial alpha release provides a pretrained Grounding DINO checkpoint; release notes do not specify breaking changes, requirements, or setup steps.
- –Download the released checkpoint to begin using Grounding DINO for object detection with text prompts.
- –Expect API instability and potential breaking changes in future releases given alpha maturity status.
Related Repositories
Discover similar tools and frameworks used by developers
presentation-ai
AI-powered slide generator with multi-model integration and themes.
pytorch
Python framework for differentiable tensor computation and deep learning.
whisper.cpp
Lightweight, cross-platform speech recognition engine delivering real-time transcription with minimal dependencies and optimized inference performance.
StabilityMatrix
Multi-backend inference UI manager with embedded dependencies.
crewAI
Python framework for autonomous multi-agent AI collaboration.