Stability AI Inpainting¶
Class: StabilityAIInpaintingBlockV1
The block wraps Stability AI inpainting API and let users use instance segmentation results to change the content of images in a creative way.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/stability_ai_inpainting@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
prompt |
str |
Prompt to inpainting model (what you wish to see).. | ✅ |
negative_prompt |
str |
Negative prompt to inpainting model (what you do not wish to see).. | ✅ |
api_key |
str |
Your Stability AI API key.. | ✅ |
invert_segmentation_mask |
bool |
Invert segmentation mask to inpaint background instead of foreground.. | ✅ |
preset |
StabilityAIPresets |
Optional preset to apply when outpainting the image (what you wish to see). If not provided, the image will be outpainted without any preset. Avaliable presets: 3d-model, analog-film, anime, cinematic, comic-book, digital-art, enhance, fantasy-art, isometric, line-art, low-poly, modeling-compound, neon-punk, origami, photographic, pixel-art, tile-texture. | ❌ |
seed |
int |
A specific value that is used to guide the 'randomness' of the generation. If not provided, a random seed is used. Must be a number between 0 and 4294967294. | ✅ |
The Refs column marks possibility to parametrise the property with dynamic values available
in workflow runtime. See Bindings for more info.
Available Connections¶
Compatible Blocks
Check what blocks you can connect to Stability AI Inpainting in version v1.
- inputs:
Detections Filter,Grid Visualization,Detections Stitch,Detections Classes Replacement,Circle Visualization,Path Deviation,Time in Zone,Model Monitoring Inference Aggregator,Roboflow Dataset Upload,QR Code Generator,Template Matching,Image Slicer,Dot Visualization,Single-Label Classification Model,Blur Visualization,Slack Notification,Perspective Correction,Roboflow Dataset Upload,Anthropic Claude,Background Color Visualization,OpenAI,Florence-2 Model,Object Detection Model,Llama 3.2 Vision,Bounding Rectangle,Dynamic Crop,Crop Visualization,OCR Model,EasyOCR,Trace Visualization,Velocity,Keypoint Detection Model,Image Threshold,Triangle Visualization,Reference Path Visualization,Model Comparison Visualization,Detection Offset,Polygon Visualization,Identify Changes,Corner Visualization,Image Slicer,Florence-2 Model,Image Blur,SIFT Comparison,Bounding Box Visualization,Line Counter,Dynamic Zone,Stitch OCR Detections,Keypoint Visualization,Detections Transformation,Image Convert Grayscale,Detections Combine,Clip Comparison,Line Counter Visualization,SIFT,Icon Visualization,Stability AI Inpainting,VLM as Detector,Google Vision OCR,Distance Measurement,Polygon Zone Visualization,OpenAI,Line Counter,Webhook Sink,Camera Calibration,Instance Segmentation Model,CogVLM,Time in Zone,Mask Visualization,Camera Focus,Twilio SMS Notification,Detections Consensus,SIFT Comparison,Stability AI Outpainting,Classification Label Visualization,Multi-Label Classification Model,LMM,Image Preprocessing,Time in Zone,Color Visualization,Morphological Transformation,JSON Parser,Depth Estimation,LMM For Classification,Detections Stabilizer,Ellipse Visualization,Instance Segmentation Model,Stability AI Image Generation,Segment Anything 2 Model,VLM as Classifier,VLM as Detector,Email Notification,Halo Visualization,Stitch Images,Local File Sink,Roboflow Custom Metadata,Absolute Static Crop,Google Gemini,VLM as Classifier,Image Contours,Pixelate Visualization,CSV Formatter,PTZ Tracking (ONVIF).md),Pixel Color Count,Path Deviation,Label Visualization,OpenAI,Identify Outliers,Contrast Equalization,Relative Static Crop - outputs:
CLIP Embedding Model,Detections Stitch,Circle Visualization,Time in Zone,Template Matching,Roboflow Dataset Upload,Image Slicer,Dot Visualization,Gaze Detection,Perception Encoder Embedding Model,Single-Label Classification Model,Blur Visualization,Clip Comparison,Perspective Correction,Roboflow Dataset Upload,Anthropic Claude,Background Color Visualization,OpenAI,Florence-2 Model,Object Detection Model,Keypoint Detection Model,Llama 3.2 Vision,Dynamic Crop,Crop Visualization,Barcode Detection,OCR Model,EasyOCR,Trace Visualization,Keypoint Detection Model,Image Threshold,Triangle Visualization,Reference Path Visualization,QR Code Detection,Model Comparison Visualization,Polygon Visualization,Corner Visualization,Image Slicer,Florence-2 Model,Image Blur,SmolVLM2,SIFT Comparison,Moondream2,Bounding Box Visualization,Buffer,Keypoint Visualization,Multi-Label Classification Model,Image Convert Grayscale,Byte Tracker,YOLO-World Model,Clip Comparison,Line Counter Visualization,SIFT,Icon Visualization,Stability AI Inpainting,VLM as Detector,Google Vision OCR,Polygon Zone Visualization,OpenAI,Instance Segmentation Model,CogVLM,Camera Calibration,Mask Visualization,Camera Focus,Stability AI Outpainting,Classification Label Visualization,Multi-Label Classification Model,LMM,Image Preprocessing,Morphological Transformation,Color Visualization,Depth Estimation,LMM For Classification,Detections Stabilizer,Instance Segmentation Model,Dominant Color,Ellipse Visualization,Stability AI Image Generation,Segment Anything 2 Model,Qwen2.5-VL,VLM as Classifier,VLM as Detector,Stitch Images,Halo Visualization,Absolute Static Crop,Google Gemini,VLM as Classifier,Object Detection Model,Pixelate Visualization,Image Contours,Pixel Color Count,Label Visualization,OpenAI,Single-Label Classification Model,Contrast Equalization,Relative Static Crop
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Stability AI Inpainting in version v1 has.
Bindings
-
input
image(image): The image to inpaint..segmentation_mask(instance_segmentation_prediction): Model predictions from segmentation model..prompt(string): Prompt to inpainting model (what you wish to see)..negative_prompt(string): Negative prompt to inpainting model (what you do not wish to see)..api_key(Union[string,secret]): Your Stability AI API key..invert_segmentation_mask(boolean): Invert segmentation mask to inpaint background instead of foreground..seed(integer): A specific value that is used to guide the 'randomness' of the generation. If not provided, a random seed is used. Must be a number between 0 and 4294967294.
-
output
image(image): Image in workflows.
Example JSON definition of step Stability AI Inpainting in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/stability_ai_inpainting@v1",
"image": "$inputs.image",
"segmentation_mask": "$steps.model.predictions",
"prompt": "my prompt",
"negative_prompt": "my prompt",
"api_key": "xxx-xxx",
"invert_segmentation_mask": "<block_does_not_provide_example>",
"preset": "3d-model",
"seed": 200
}