Semantic Segmentation Model¶
v2¶
Class: RoboflowSemanticSegmentationModelBlockV2 (there are multiple versions of this block)
Warning: This block has multiple versions. Please refer to the specific version for details. You can learn more about how versions work here: Versioning
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@v2to 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.. | ✅ |
confidence_mode |
str |
How confidence thresholds are determined.. | ✅ |
custom_confidence |
float |
Custom confidence threshold for predictions.. | ✅ |
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 v2.
- inputs:
Image Preprocessing,Single-Label Classification Model,Anthropic Claude,Image Slicer,Dynamic Crop,Bounding Box Visualization,Object Detection Model,Absolute Static Crop,SIFT Comparison,Stitch Images,Stitch OCR Detections,OpenAI,Instance Segmentation Model,Email Notification,Stability AI Inpainting,EasyOCR,Llama 3.2 Vision,Florence-2 Model,Roboflow Custom Metadata,Auto Rotate on Edges,Keypoint Detection Model,Stability AI Outpainting,Model Comparison Visualization,Slack Notification,Line Counter Visualization,Camera Calibration,Single-Label Classification Model,Clip Comparison,VLM As Detector,CogVLM,Camera Focus,Corner Visualization,Ellipse Visualization,PP-OCR,Morphological Transformation,Anthropic Claude,Roboflow Visual Search,Color Visualization,Instance Segmentation Model,OpenAI,Triangle Visualization,Object Detection Model,Image Contours,Image Threshold,Current Time,Roboflow Visual Search Classifier,QR Code Generator,OpenAI-Compatible LLM,Florence-2 Model,Semantic Segmentation Model,Polygon Zone Visualization,Stitch OCR Detections,Roboflow Asset Library Attributes,Microsoft SQL Server Sink,VLM As Classifier,Camera Focus,Image Convert Grayscale,Label Visualization,Llama 3.2 Vision,Stability AI Image Generation,Instance Segmentation Model,MQTT Writer,Roboflow Dataset Upload,Local File Sink,Identify Outliers,Semantic Segmentation Model,Google Gemini,Event Writer,Depth Estimation,Google Gemini,OpenAI,Trace Visualization,Twilio SMS Notification,LMM For Classification,Object Detection Model,Webhook Sink,Halo Visualization,Mask Visualization,Pixelate Visualization,Twilio SMS/MMS Notification,MoonshotAI Kimi,Dot Visualization,Multi-Label Classification Model,OPC UA Writer Sink,Google Gemini,Keypoint Visualization,LMM,Image Slicer,OCR Model,Circle Visualization,Contrast Enhancement,Relative Static Crop,Morphological Transformation,Email Notification,Halo Visualization,Cosmos 3,Polygon Visualization,Qwen-VL,PLC Writer,Google Gemma,Crop Visualization,Qwen 3.5 API,Model Monitoring Inference Aggregator,Keypoint Detection Model,Icon Visualization,Heatmap Visualization,Single-Label Classification Model,Multi-Label Classification Model,Google Gemma API,Instance Segmentation Model,Detections Consensus,CSV Formatter,Image Blur,Background Color Visualization,Grid Visualization,Blur Visualization,GLM-OCR,Anthropic Claude,Reference Path Visualization,Classification Label Visualization,Google Vision OCR,Perspective Correction,Background Subtraction,Polygon Visualization,Contrast Equalization,SIFT,Qwen 3.6 API,Text Display,MoonshotAI Kimi,OpenRouter,Qwen3.5-VL,Roboflow Vision Events,Identify Changes,Keypoint Detection Model,OpenAI,Multi-Label Classification Model,S3 Sink,Roboflow Dataset Upload - outputs:
SAM 3,Cosmos 3,Single-Label Classification Model,Qwen-VL,Model Monitoring Inference Aggregator,Object Detection Model,Qwen3-VL,Qwen3.5,Keypoint Detection Model,Single-Label Classification Model,Object Detection Model,Webhook Sink,Instance Segmentation Model,Multi-Label Classification Model,Mask Visualization,Instance Segmentation Model,SAM3 Video Tracker,Object Detection Model,Multi-Label Classification Model,SAM 3,SAM 3,GLM-OCR,Instance Segmentation Model,Qwen2.5-VL,Semantic Segmentation Model,SmolVLM2,Moondream2,Instance Segmentation Model,Keypoint Detection Model,Qwen3.5-VL,Keypoint Detection Model,Multi-Label Classification Model,Semantic Segmentation Model,SAM2 Video Tracker,Single-Label Classification Model
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Semantic Segmentation Model in version v2 has.
Bindings
-
input
images(image): The image to infer on..model_id(roboflow_model_id): Roboflow model identifier..confidence_mode(string): How confidence thresholds are determined..custom_confidence(float_zero_to_one): Custom confidence threshold for predictions..
-
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 v2
{
"name": "<your_step_name_here>",
"type": "roboflow_core/roboflow_semantic_segmentation_model@v2",
"images": "$inputs.image",
"model_id": "my_project/3",
"confidence_mode": "<block_does_not_provide_example>",
"custom_confidence": 0.3
}
v1¶
Class: RoboflowSemanticSegmentationModelBlockV1 (there are multiple versions of this block)
Warning: This block has multiple versions. Please refer to the specific version for details. You can learn more about how versions work here: Versioning
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:
Halo Visualization,Trace Visualization,Polygon Visualization,Image Preprocessing,Single-Label Classification Model,Camera Focus,Corner Visualization,Ellipse Visualization,Dynamic Crop,Crop Visualization,Image Slicer,Morphological Transformation,Bounding Box Visualization,Keypoint Detection Model,Roboflow Visual Search,Icon Visualization,Heatmap Visualization,Object Detection Model,Single-Label Classification Model,Color Visualization,Halo Visualization,Multi-Label Classification Model,Mask Visualization,Instance Segmentation Model,Absolute Static Crop,Pixelate Visualization,Image Blur,Triangle Visualization,Background Color Visualization,Dot Visualization,Grid Visualization,SIFT Comparison,Object Detection Model,Image Contours,Image Threshold,Blur Visualization,Stitch Images,Instance Segmentation Model,Roboflow Visual Search Classifier,Stability AI Inpainting,QR Code Generator,Reference Path Visualization,Semantic Segmentation Model,Polygon Zone Visualization,Keypoint Visualization,Classification Label Visualization,Perspective Correction,Background Subtraction,Camera Focus,Image Convert Grayscale,Label Visualization,Contrast Equalization,Polygon Visualization,Auto Rotate on Edges,SIFT,Stability AI Image Generation,Text Display,Image Slicer,Instance Segmentation Model,Circle Visualization,Model Comparison Visualization,Stability AI Outpainting,Keypoint Detection Model,Line Counter Visualization,Camera Calibration,Multi-Label Classification Model,Contrast Enhancement,Relative Static Crop,Semantic Segmentation Model,Depth Estimation,Morphological Transformation - outputs:
SAM 3,Cosmos 3,Single-Label Classification Model,Qwen-VL,Model Monitoring Inference Aggregator,Object Detection Model,Qwen3-VL,Qwen3.5,Keypoint Detection Model,Single-Label Classification Model,Object Detection Model,Webhook Sink,Instance Segmentation Model,Multi-Label Classification Model,Mask Visualization,Instance Segmentation Model,SAM3 Video Tracker,Object Detection Model,Multi-Label Classification Model,SAM 3,SAM 3,GLM-OCR,Instance Segmentation Model,Qwen2.5-VL,Semantic Segmentation Model,SmolVLM2,Moondream2,Instance Segmentation Model,Keypoint Detection Model,Qwen3.5-VL,Keypoint Detection Model,Multi-Label Classification Model,Semantic Segmentation Model,SAM2 Video Tracker,Single-Label Classification 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"
}