ComfyUI-Grounding

Grounding for dummies, simplest workflow

🎯 3 Nodes Total - Loader → Detector → Visualizer

🚀 5 Model Families - GroundingDINO, MM-GroundingDINO, OWLv2, Florence-2, YOLO-World

💾 Smart Caching - Instant reload

📦 Batch Processing - Multiple images at once

🎭 Built-in Masks - No separate BboxToMask node needed

Quick Start

cd ComfyUI/custom_nodes/
git clone https://github.com/PozzettiAndrea/ComfyUI-Grounding
cd ComfyUI-Grounding
pip install -r requirements.txt

The Nodes

1. Grounding Model Loader

Load any of 15+ models from a single dropdown.

1. GroundingDINO: SwinT OGC (694MB) - IDEA-Research/grounding-dino-tiny
2. GroundingDINO: SwinB (938MB) - IDEA-Research/grounding-dino-base
3. MM-GroundingDINO: Tiny O365+GoldG (50.4 mAP) - openmmlab-community/mm_grounding_dino_tiny_o365v1_goldg
4. MM-GroundingDINO: Tiny O365+GoldG+GRIT (50.5 mAP) - openmmlab-community/mm_grounding_dino_tiny_o365v1_goldg_grit
5. MM-GroundingDINO: Tiny O365+GoldG+V3Det (50.6 mAP) - openmmlab-community/mm_grounding_dino_tiny_o365v1_goldg_v3det
6. MM-GroundingDINO: Base O365+GoldG+V3Det (52.5 mAP) - openmmlab-community/mm_grounding_dino_base_o365v1_goldg_v3det
7. MM-GroundingDINO: Base All Datasets (59.5 mAP) - openmmlab-community/mm_grounding_dino_base_all
8. MM-GroundingDINO: Large O365v2+OIv6+GoldG (53.0 mAP) - openmmlab-community/mm_grounding_dino_large_o365v2_oiv6_goldg
9. MM-GroundingDINO: Large All Datasets (60.3 mAP) - openmmlab-community/mm_grounding_dino_large_all
10. OWLv2: Base Patch16 - google/owlv2-base-patch16
11. OWLv2: Large Patch14 - google/owlv2-large-patch14
12. OWLv2: Base Patch16 Ensemble - google/owlv2-base-patch16-ensemble
13. OWLv2: Large Patch14 Ensemble - google/owlv2-large-patch14-ensemble
14. Florence-2: Base (0.23B params) - microsoft/Florence-2-base
15. Florence-2: Large (0.77B params) - microsoft/Florence-2-large
16. YOLO-World: v8s (Small) - yolov8s-worldv2.pt
17. YOLO-World: v8m (Medium) - yolov8m-worldv2.pt
18. YOLO-World: v8l (Large) - yolov8l-worldv2.pt
19. YOLO-World: v8x (Extra Large) - yolov8x-worldv2.pt

2. Grounding Detector

Universal detector for all models.

Key Features

• Overrides standard text label splitting. It splits only at ".", otherwise label is what you write
• Enable single_box_mode for single detection
• First load: Downloads model
• Second load: Instant from cache
• Models stored in ComfyUI standard folders:
  • GroundingDINO → models/grounding-dino/
  • Florence-2 & OWLv2 → models/LLM/
  • YOLO-World → models/yolo_world/
  • SAM2 → models/sam2/
• Process multiple images in one pass
• All nodes support batches

Florence-2 Attention Modes

• eager - Most compatible (default)
• sdpa - Faster on PyTorch 2.0+
• flash_attention_2 - Fastest on A100/H100

3. Bounding Box Visualizer

Re-draw bboxes on images with custom line width. Optional since detector already returns annotated images.

4. SAM2 Integration

DownloadAndLoadSAM2Model - Load SAM2 models (base/large/small/tiny) Sam2Segmentation - Segment using bboxes from grounding models or point coordinates

• Supports batch processing
• Models cached in memory for instant reload
• Compatible with all grounding model outputs

Tips

Prompt Format:

• Use periods for multiple labels → "laser. crocodile."
• Use commas to keep a single label → "laser, crocodile"

Credits

• GroundingDINO - IDEA-Research
• OWLv2 - Google Research
• Florence-2 - Microsoft Research
• YOLO-World - Ultralytics

License

MIT License