Stability AI Inpainting

Class: StabilityAIInpaintingBlockV1

Source: inference.core.workflows.core_steps.models.foundation.stability_ai.inpainting.v1.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: Line Counter, Keypoint Detection Model, Halo Visualization, OpenAI, Stability AI Image Generation, Model Comparison Visualization, Keypoint Visualization, Crop Visualization, Image Blur, Bounding Box Visualization, Distance Measurement, Line Counter, Roboflow Dataset Upload, Template Matching, Mask Visualization, Image Slicer, Detections Classes Replacement, Instance Segmentation Model, Instance Segmentation Model, VLM as Classifier, JSON Parser, Ellipse Visualization, Email Notification, Bounding Rectangle, OpenAI, Dynamic Zone, Slack Notification, VLM as Detector, Twilio SMS Notification, Webhook Sink, Label Visualization, Google Vision OCR, Stability AI Outpainting, CSV Formatter, Single-Label Classification Model, Polygon Visualization, Velocity, Identify Changes, Model Monitoring Inference Aggregator, Roboflow Custom Metadata, Reference Path Visualization, Florence-2 Model, OCR Model, Detections Transformation, Anthropic Claude, VLM as Detector, Camera Calibration, Image Preprocessing, Image Contours, Line Counter Visualization, Florence-2 Model, LMM For Classification, Corner Visualization, Clip Comparison, Pixel Color Count, Stitch Images, Depth Estimation, SIFT, Time in Zone, Blur Visualization, Image Convert Grayscale, Background Color Visualization, Image Slicer, Dynamic Crop, Local File Sink, Perspective Correction, Stitch OCR Detections, Circle Visualization, Triangle Visualization, Dot Visualization, Detections Filter, SIFT Comparison, CogVLM, Path Deviation, Object Detection Model, Segment Anything 2 Model, VLM as Classifier, LMM, Color Visualization, Stability AI Inpainting, Classification Label Visualization, OpenAI, Detection Offset, Absolute Static Crop, Image Threshold, Detections Consensus, Time in Zone, Llama 3.2 Vision, Pixelate Visualization, Trace Visualization, Detections Stabilizer, Camera Focus, Roboflow Dataset Upload, Grid Visualization, Google Gemini, PTZ Tracking (ONVIF).md), SIFT Comparison, Multi-Label Classification Model, Relative Static Crop, Detections Stitch, Path Deviation, Polygon Zone Visualization, Identify Outliers
• outputs: Keypoint Detection Model, Gaze Detection, Halo Visualization, OpenAI, Stability AI Image Generation, Model Comparison Visualization, Keypoint Visualization, Crop Visualization, Image Blur, Bounding Box Visualization, Roboflow Dataset Upload, Template Matching, Mask Visualization, SmolVLM2, VLM as Classifier, Image Slicer, Instance Segmentation Model, Instance Segmentation Model, QR Code Detection, CLIP Embedding Model, Ellipse Visualization, OpenAI, VLM as Detector, Qwen2.5-VL, Label Visualization, Google Vision OCR, Stability AI Outpainting, Single-Label Classification Model, Buffer, Polygon Visualization, Barcode Detection, Dominant Color, Reference Path Visualization, Florence-2 Model, OCR Model, VLM as Detector, Anthropic Claude, Image Preprocessing, Line Counter Visualization, Florence-2 Model, Image Contours, Camera Calibration, Single-Label Classification Model, LMM For Classification, Clip Comparison, Corner Visualization, Pixel Color Count, Stitch Images, SIFT, Depth Estimation, Time in Zone, Perception Encoder Embedding Model, Blur Visualization, Image Convert Grayscale, Image Slicer, Background Color Visualization, Dynamic Crop, Perspective Correction, Circle Visualization, Triangle Visualization, Dot Visualization, CogVLM, Multi-Label Classification Model, Object Detection Model, Segment Anything 2 Model, VLM as Classifier, LMM, Color Visualization, OpenAI, Classification Label Visualization, Stability AI Inpainting, Byte Tracker, Moondream2, Absolute Static Crop, Image Threshold, Keypoint Detection Model, Llama 3.2 Vision, Pixelate Visualization, Trace Visualization, Detections Stabilizer, Camera Focus, Roboflow Dataset Upload, Clip Comparison, YOLO-World Model, Google Gemini, SIFT Comparison, Multi-Label Classification Model, Relative Static Crop, Detections Stitch, Object Detection Model, Polygon Zone Visualization

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[secret, string]): 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
}