ComfyUI-Grounding

Grounding for dummies, simplest workflow

🎯 8 Nodes Total - 2 Loaders + 2 Detectors + 2 SAM2 + 2 Utilities

🚀 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

Detection 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 with bbox/mask output.

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

Mask Generation Nodes

3. Grounding Mask Loader

Load mask generation models:

• Florence-2 Seg (Base/Large) - Direct segmentation masks
• SA2VA (1B/4B/8B/26B) - Visual grounding with text output

4. Grounding Mask Detector

Direct mask generation from text prompts. Outputs masks, overlaid images, and generated text descriptions.

SAM2 Segmentation Nodes

5. Download and Load SAM2 Model

Load SAM2 models (base/large/small/tiny) for high-quality segmentation.

6. SAM2 Segmentation

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

Utility Nodes

7. Bounding Box Visualizer

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

8. Batch Crop and Pad From Mask

Crops images to mask bounding boxes and pads them to uniform size for batch processing.

Example Workflows

Three ready-to-use workflows in /workflows/:

• normal_grounding.json - Object detection + SAM2 segmentation pipeline
• batch_normal_grounding.json - Batch version for processing multiple images
• mask_grounding.json - Direct mask generation using SA2VA (faster for segmentation)

Load these in ComfyUI to see the nodes in action.

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