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:
Morphological Transformation,Classification Label Visualization,Crop Visualization,Stability AI Outpainting,Blur Visualization,Reference Path Visualization,OpenAI,Anthropic Claude,Camera Focus,Instance Segmentation Model,Model Comparison Visualization,Florence-2 Model,Trace Visualization,Label Visualization,Image Convert Grayscale,Florence-2 Model,Text Display,Qwen-VL,Llama 3.2 Vision,Image Blur,Keypoint Detection Model,Absolute Static Crop,CSV Formatter,Keypoint Detection Model,LMM,Qwen 3.5 API,Qwen 3.6 API,Camera Focus,Multi-Label Classification Model,Clip Comparison,Google Gemma API,Contrast Enhancement,Halo Visualization,Color Visualization,Morphological Transformation,MoonshotAI Kimi,Stitch OCR Detections,Event Writer,Stability AI Inpainting,Roboflow Asset Library Attributes,Microsoft SQL Server Sink,OpenAI,Roboflow Vision Events,Identify Outliers,CogVLM,Detections Consensus,Object Detection Model,OPC UA Writer Sink,Semantic Segmentation Model,Dynamic Crop,Bounding Box Visualization,Qwen3.5-VL,OpenAI,OCR Model,Single-Label Classification Model,Slack Notification,OpenRouter,SIFT Comparison,Pixelate Visualization,Google Vision OCR,Google Gemma,Halo Visualization,Stitch OCR Detections,GLM-OCR,Image Threshold,Stitch Images,Twilio SMS/MMS Notification,Icon Visualization,VLM As Classifier,MoonshotAI Kimi,Single-Label Classification Model,Google Gemini,Single-Label Classification Model,Webhook Sink,Instance Segmentation Model,QR Code Generator,MQTT Writer,Ellipse Visualization,Object Detection Model,Anthropic Claude,Keypoint Detection Model,Dot Visualization,Perspective Correction,Instance Segmentation Model,Roboflow Dataset Upload,SIFT,Google Gemini,EasyOCR,Local File Sink,Triangle Visualization,Contrast Equalization,Polygon Visualization,OpenAI,Heatmap Visualization,Google Gemini,LMM For Classification,VLM As Detector,Llama 3.2 Vision,Multi-Label Classification Model,Polygon Visualization,Email Notification,Identify Changes,Mask Visualization,Anthropic Claude,Keypoint Visualization,Background Subtraction,Multi-Label Classification Model,Twilio SMS Notification,Email Notification,Semantic Segmentation Model,Image Slicer,Image Contours,Line Counter Visualization,Image Preprocessing,Depth Estimation,Current Time,Corner Visualization,Polygon Zone Visualization,Camera Calibration,Roboflow Dataset Upload,Grid Visualization,Stability AI Image Generation,S3 Sink,Circle Visualization,Image Slicer,Roboflow Custom Metadata,Relative Static Crop,Instance Segmentation Model,Model Monitoring Inference Aggregator,OpenAI-Compatible LLM,Object Detection Model,Background Color Visualization - outputs:
Multi-Label Classification Model,Mask Visualization,GLM-OCR,Single-Label Classification Model,Single-Label Classification Model,Webhook Sink,Multi-Label Classification Model,Instance Segmentation Model,Instance Segmentation Model,Semantic Segmentation Model,Object Detection Model,SmolVLM2,Keypoint Detection Model,Object Detection Model,Instance Segmentation Model,SAM 3,Semantic Segmentation Model,Qwen-VL,Keypoint Detection Model,Qwen3.5-VL,Qwen3.5,Keypoint Detection Model,Moondream2,Qwen2.5-VL,SAM 3,SAM 3,SAM2 Video Tracker,Single-Label Classification Model,Qwen3-VL,Multi-Label Classification Model,Instance Segmentation Model,Model Monitoring Inference Aggregator,Object Detection Model,SAM3 Video Tracker
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,Polygon Visualization,Multi-Label Classification Model,Mask Visualization,Image Threshold,Stability AI Inpainting,Stitch Images,Classification Label Visualization,Morphological Transformation,Crop Visualization,Icon Visualization,Stability AI Outpainting,Blur Visualization,Reference Path Visualization,Single-Label Classification Model,Keypoint Visualization,Single-Label Classification Model,Background Subtraction,Camera Focus,Instance Segmentation Model,QR Code Generator,Instance Segmentation Model,Pixelate Visualization,Model Comparison Visualization,Semantic Segmentation Model,Trace Visualization,Image Slicer,Ellipse Visualization,Object Detection Model,Image Contours,Line Counter Visualization,Keypoint Detection Model,Dot Visualization,Perspective Correction,Image Preprocessing,Image Convert Grayscale,Label Visualization,Dynamic Crop,Instance Segmentation Model,Semantic Segmentation Model,Text Display,Depth Estimation,Bounding Box Visualization,Image Blur,Absolute Static Crop,SIFT,Keypoint Detection Model,Corner Visualization,Polygon Zone Visualization,Camera Calibration,Grid Visualization,Stability AI Image Generation,Triangle Visualization,Camera Focus,Contrast Equalization,Circle Visualization,Polygon Visualization,Image Slicer,Relative Static Crop,Heatmap Visualization,Multi-Label Classification Model,Object Detection Model,Contrast Enhancement,Halo Visualization,Color Visualization,Morphological Transformation,SIFT Comparison,Background Color Visualization - outputs:
Multi-Label Classification Model,Mask Visualization,GLM-OCR,Single-Label Classification Model,Single-Label Classification Model,Webhook Sink,Multi-Label Classification Model,Instance Segmentation Model,Instance Segmentation Model,Semantic Segmentation Model,Object Detection Model,SmolVLM2,Keypoint Detection Model,Object Detection Model,Instance Segmentation Model,SAM 3,Semantic Segmentation Model,Qwen-VL,Keypoint Detection Model,Qwen3.5-VL,Qwen3.5,Keypoint Detection Model,Moondream2,Qwen2.5-VL,SAM 3,SAM 3,SAM2 Video Tracker,Single-Label Classification Model,Qwen3-VL,Multi-Label Classification Model,Instance Segmentation Model,Model Monitoring Inference Aggregator,Object Detection Model,SAM3 Video Tracker
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"
}