IDEA-Research/DINO

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

2834 stars · 309 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Official PyTorch implementation of DINO, a state-of-the-art end-to-end object detection model based on DETR with improved denoising anchor boxes (ICLR 2023). It provides model code, training scripts, and pretrained checkpoints for COCO object detection.

Use cases

• train a state-of-the-art object detection model on COCO
• run DETR-style transformer object detection inference
• reproduce ICLR 2023 DINO paper results
• fine-tune a pretrained object detector on custom images
• compare detection model baselines for research

When to choose

• you need a top-performing end-to-end transformer-based object detector
• you want to reproduce or build on published DINO research results
• you need pretrained COCO detection checkpoints

When to avoid

• you need open-vocabulary/text-prompted detection (use Grounding DINO instead)
• you need image segmentation (use Mask DINO or Semantic-SAM)
• you want a lightweight detector for edge or mobile deployment

Facets

library · maturity maintenance

computer-vision machine-learning deep-learning computer-vision deep-learning machine-learning python object-detection detr transformer-detection pytorch research-code iclr-2023 linux gpu

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markdown · JSON · MCP: product_card(name="IDEA-Research/DINO")