diff --git a/README.md b/README.md
index d62b52d..cb72674 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,6 @@
# ComfyUI-Grounding
-**Grounding for dummies, simplest workflow**
+**Grounding toolbox**
@@ -24,12 +24,11 @@ Switch between 19+ detection models with a single dropdown. One node for everyth
### SA2VA Vision-Language Segmentation
-Unique feature: generates segmentation masks AND text descriptions from prompts.
+When Florence2 isn't enough. Sa2va has VERY advanced semantic understanding and reasoning capabilities.
### SAM2 Support
-High-quality segmentation with multiple SAM2 variants and precision options.
@@ -45,52 +44,16 @@ Control label separation: use periods for multiple labels, commas for single com
## Installation
-```bash
-cd ComfyUI/custom_nodes/
-git clone https://github.com/PozzettiAndrea/ComfyUI-Grounding
-cd ComfyUI-Grounding
-pip install -r requirements.txt
-```
-
**On first ComfyUI startup:**
- Example assets auto-copied to `ComfyUI/input/`
- Example workflows auto-copied to user workflows with "ComfyUI-Grounding_" prefix
-**Optional: Flash Attention (faster inference)**
-```bash
-pip install flash-attn --no-build-isolation
-```
-Requires CUDA GPU, takes 5-10 minutes to compile. Significantly speeds up Florence-2 and SA2VA models.
-
## 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
-
+#### 1. Grounding Model (down)Loader
+Load any of 15+ models from a single dropdown. See footnotes for full list
#### 2. Grounding Detector
Universal detector for all models with bbox/mask output.
@@ -112,33 +75,18 @@ Universal detector for all models with bbox/mask output.
- 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
+#### 3. Grounding Mask (down)Loader
Load mask generation models:
**Florence-2 Segmentation (2 models)**
-- Base (0.23B params) - microsoft/Florence-2-base
-- Large (0.77B params) - microsoft/Florence-2-large
- Direct segmentation masks from text prompts
**SA2VA Vision-Language (4 models)**
-- 1B - ByteDance/Sa2VA-1B
-- 4B - ByteDance/Sa2VA-4B
-- 8B - ByteDance/Sa2VA-8B
-- 26B - ByteDance/Sa2VA-26B
-- Visual grounding with detailed text descriptions
+- Visual grounding with advanced semantic understanding
- Requires `trust_remote_code=True`
- Supports fp16/bf16/fp32 precision options
@@ -151,28 +99,18 @@ Direct mask generation from text prompts. Outputs masks, overlaid images, and ge
### SAM2 Segmentation Nodes
-#### 5. Download and Load SAM2 Model
+#### 5. SAM2 Model (down)Loader
Load SAM2 models for high-quality segmentation:
-**SAM2 (4 variants)**
-- sam2_hiera_base_plus.safetensors
-- sam2_hiera_large.safetensors
-- sam2_hiera_small.safetensors
-- sam2_hiera_tiny.safetensors
-
-**SAM2.1 (4 variants - improved)**
-- sam2.1_hiera_base_plus.safetensors
-- sam2.1_hiera_large.safetensors
-- sam2.1_hiera_small.safetensors
-- sam2.1_hiera_tiny.safetensors
+**SAM2/2.1 (4 variants)**
Auto-downloads from HuggingFace (Kijai/sam2-safetensors) if not found locally.
Supports fp16/bf16/fp32 precision and 3 segmentor modes: single_image, video, automaskgenerator.
-#### 6. SAM2 Segmentation
+#### 6. SAM2 Segment
Segment using bboxes from grounding models or point coordinates.
@@ -220,12 +158,6 @@ Load these in ComfyUI to see the nodes in action.
- Instant reload on subsequent uses
- Cache key includes model type and configuration
-## Tips
-
-**Prompt Format:**
-- Use periods for multiple labels → `"laser. crocodile."`
-- Use commas to keep a single label → `"laser, crocodile"`
-
## Credits
- [GroundingDINO](https://github.com/IDEA-Research/GroundingDINO) - IDEA-Research
@@ -235,4 +167,30 @@ Load these in ComfyUI to see the nodes in action.
## License
-MIT License
\ No newline at end of file
+MIT License
+
+## Footnotes
+Full list of models:
+
+
+
+ 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
+
\ No newline at end of file
diff --git a/__init__.py b/__init__.py
index c6bacc3..ffbff9d 100644
--- a/__init__.py
+++ b/__init__.py
@@ -48,8 +48,8 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"GroundingModelLoader": "Grounding Model (down)Loader",
"GroundingDetector": "Grounding Detector",
"BboxVisualizer": "Bounding Box Visualizer",
- "DownloadAndLoadSAM2Model": "(Down)Load SAM2Model",
- "Sam2Segmentation": "Sam2 Segmentation",
+ "DownloadAndLoadSAM2Model": "SAM2Model (down)Loader",
+ "Sam2Segmentation": "Sam2 Segment",
"GroundingMaskModelLoader": "Grounding Mask Model (down)Loader",
"GroundingMaskDetector": "Grounding Mask Detector",
"BatchCropAndPadFromMask": "Batch Crop and Pad From Mask",
diff --git a/docs/simple.png b/docs/simple.png
index e2b3857..b70925f 100644
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