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