Semantic Segmentation Model¶
Class: RoboflowSemanticSegmentationModelBlockV1
Run inference on a semantic segmentation model hosted on or uploaded to Roboflow.
Semantic segmentation assigns a class label to every pixel in the image, producing a dense segmentation mask rather than per-object bounding boxes or instance masks.
You can query any model that is private to your account, or any public model available on Roboflow Universe.
You will need to set your Roboflow API key in your Inference environment to use this block. To learn more about setting your Roboflow API key, refer to the Inference documentation.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/roboflow_semantic_segmentation_model@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
model_id |
str |
Roboflow model identifier.. | ✅ |
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 Semantic Segmentation Model in version v1.
- inputs:
Stitch Images,Image Threshold,Stability AI Inpainting,Corner Visualization,Image Blur,Ellipse Visualization,Perspective Correction,Depth Estimation,Camera Calibration,Absolute Static Crop,Multi-Label Classification Model,Stability AI Image Generation,Grid Visualization,Background Color Visualization,Dynamic Crop,Image Slicer,Image Preprocessing,Relative Static Crop,Contrast Equalization,Background Subtraction,Morphological Transformation,Line Counter Visualization,SIFT,SIFT Comparison,Trace Visualization,Keypoint Visualization,Halo Visualization,Dot Visualization,Keypoint Detection Model,Pixelate Visualization,Single-Label Classification Model,Circle Visualization,Image Convert Grayscale,Icon Visualization,QR Code Generator,Semantic Segmentation Model,Halo Visualization,Camera Focus,Polygon Visualization,Color Visualization,Text Display,Reference Path Visualization,Object Detection Model,Instance Segmentation Model,Crop Visualization,Mask Visualization,Heatmap Visualization,Triangle Visualization,Blur Visualization,Bounding Box Visualization,Label Visualization,Classification Label Visualization,Camera Focus,Polygon Visualization,Image Slicer,Image Contours,Model Comparison Visualization,Stability AI Outpainting,Polygon Zone Visualization - outputs:
Keypoint Detection Model,SAM 3,Object Detection Model,SAM 3,Multi-Label Classification Model,SAM 3,Qwen2.5-VL,Single-Label Classification Model,Object Detection Model,Instance Segmentation Model,Qwen3.5-VL,Instance Segmentation Model,Qwen3-VL,Mask Visualization,Multi-Label Classification Model,Webhook Sink,GLM-OCR,Model Monitoring Inference Aggregator,Single-Label Classification Model,Keypoint Detection Model,SmolVLM2,Moondream2,Semantic Segmentation Model
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Semantic Segmentation Model in version v1 has.
Bindings
-
input
images(image): The image to infer on..model_id(roboflow_model_id): Roboflow model identifier..
-
output
inference_id(inference_id): Inference identifier.predictions(semantic_segmentation_prediction): Prediction with per-pixel class label and confidence for semantic segmentation.model_id(roboflow_model_id): Roboflow model id.
Example JSON definition of step Semantic Segmentation Model in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/roboflow_semantic_segmentation_model@v1",
"images": "$inputs.image",
"model_id": "my_project/3"
}