Keypoint Visualization¶
Class: KeypointVisualizationBlockV1
Source: inference.core.workflows.core_steps.visualizations.keypoint.v1.KeypointVisualizationBlockV1
The KeypointVisualization
block uses a detections from an
keypoint detection model to draw keypoints on objects using
sv.VertexAnnotator
.
Type identifier¶
Use the following identifier in step "type"
field: roboflow_core/keypoint_visualization@v1
to add the block as
as step in your workflow.
Properties¶
Name | Type | Description | Refs |
---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
copy_image |
bool |
Enable this option to create a copy of the input image for visualization, preserving the original. Use this when stacking multiple visualizations.. | ✅ |
annotator_type |
str |
Type of annotator to be used for keypoint visualization.. | ❌ |
color |
str |
Color of the keypoint.. | ✅ |
text_color |
str |
Text color of the keypoint.. | ✅ |
text_scale |
float |
Scale of the text.. | ✅ |
text_thickness |
int |
Thickness of the text characters.. | ✅ |
text_padding |
int |
Padding around the text in pixels.. | ✅ |
thickness |
int |
Thickness of the outline in pixels.. | ✅ |
radius |
int |
Radius of the keypoint in pixels.. | ✅ |
edges |
List[Any] |
Mapping of keypoints to edges. List of pairs of indices.. | ✅ |
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 Keypoint Visualization
in version v1
.
- inputs:
Grid Visualization
,Image Blur
,Image Preprocessing
,Image Slicer
,OpenAI
,Dynamic Crop
,Absolute Static Crop
,Roboflow Dataset Upload
,Color Visualization
,LMM
,Corner Visualization
,Google Gemini
,Depth Estimation
,Stability AI Outpainting
,Keypoint Visualization
,Keypoint Detection Model
,PTZ Tracking (ONVIF)
.md),Trace Visualization
,Clip Comparison
,Google Vision OCR
,Email Notification
,Keypoint Detection Model
,Single-Label Classification Model
,Model Comparison Visualization
,Dimension Collapse
,Mask Visualization
,Image Slicer
,Model Monitoring Inference Aggregator
,Clip Comparison
,Size Measurement
,Multi-Label Classification Model
,Buffer
,Detections Consensus
,Image Threshold
,Contrast Equalization
,Line Counter
,OpenAI
,Detections Filter
,Morphological Transformation
,Classification Label Visualization
,Relative Static Crop
,Camera Calibration
,Dynamic Zone
,Florence-2 Model
,Blur Visualization
,Stitch Images
,Roboflow Dataset Upload
,JSON Parser
,Triangle Visualization
,Perspective Correction
,SIFT
,Detections Transformation
,Icon Visualization
,Label Visualization
,Stability AI Image Generation
,Stitch OCR Detections
,Pixel Color Count
,CogVLM
,Ellipse Visualization
,SIFT Comparison
,Llama 3.2 Vision
,VLM as Detector
,Line Counter Visualization
,Florence-2 Model
,Line Counter
,SIFT Comparison
,Slack Notification
,Local File Sink
,Distance Measurement
,Image Convert Grayscale
,Detection Offset
,Roboflow Custom Metadata
,Gaze Detection
,Twilio SMS Notification
,Background Color Visualization
,VLM as Classifier
,QR Code Generator
,Identify Changes
,Polygon Zone Visualization
,Anthropic Claude
,VLM as Detector
,Polygon Visualization
,Camera Focus
,Dot Visualization
,LMM For Classification
,Template Matching
,Cosine Similarity
,Detections Classes Replacement
,Instance Segmentation Model
,Identify Outliers
,Circle Visualization
,Bounding Box Visualization
,Image Contours
,OpenAI
,Object Detection Model
,OCR Model
,Halo Visualization
,Reference Path Visualization
,VLM as Classifier
,CSV Formatter
,Pixelate Visualization
,Webhook Sink
,EasyOCR
,Stability AI Inpainting
,Crop Visualization
- outputs:
Image Blur
,Image Preprocessing
,Image Slicer
,OpenAI
,Instance Segmentation Model
,Dynamic Crop
,Multi-Label Classification Model
,Roboflow Dataset Upload
,LMM
,Moondream2
,Absolute Static Crop
,Corner Visualization
,Color Visualization
,Google Gemini
,Depth Estimation
,Keypoint Detection Model
,Stability AI Outpainting
,Keypoint Visualization
,Trace Visualization
,Clip Comparison
,Google Vision OCR
,Keypoint Detection Model
,Single-Label Classification Model
,Time in Zone
,Model Comparison Visualization
,YOLO-World Model
,Mask Visualization
,Image Slicer
,Clip Comparison
,Multi-Label Classification Model
,Buffer
,Image Threshold
,Contrast Equalization
,OpenAI
,Barcode Detection
,Morphological Transformation
,Classification Label Visualization
,Relative Static Crop
,Camera Calibration
,Florence-2 Model
,Stitch Images
,Blur Visualization
,Roboflow Dataset Upload
,Qwen2.5-VL
,Triangle Visualization
,Perspective Correction
,SIFT
,Icon Visualization
,QR Code Detection
,Pixel Color Count
,Stability AI Image Generation
,Label Visualization
,Object Detection Model
,Llama 3.2 Vision
,Ellipse Visualization
,CogVLM
,Detections Stabilizer
,VLM as Detector
,SmolVLM2
,Single-Label Classification Model
,Line Counter Visualization
,Florence-2 Model
,SIFT Comparison
,Image Convert Grayscale
,Gaze Detection
,Perception Encoder Embedding Model
,Background Color Visualization
,VLM as Classifier
,Segment Anything 2 Model
,Polygon Zone Visualization
,Anthropic Claude
,VLM as Detector
,Detections Stitch
,Byte Tracker
,Polygon Visualization
,Camera Focus
,Dot Visualization
,LMM For Classification
,Template Matching
,CLIP Embedding Model
,Instance Segmentation Model
,Circle Visualization
,Bounding Box Visualization
,Image Contours
,OpenAI
,Object Detection Model
,OCR Model
,Dominant Color
,Halo Visualization
,Reference Path Visualization
,VLM as Classifier
,Pixelate Visualization
,EasyOCR
,Stability AI Inpainting
,Crop Visualization
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Keypoint Visualization
in version v1
has.
Bindings
-
input
image
(image
): The image to visualize on..copy_image
(boolean
): Enable this option to create a copy of the input image for visualization, preserving the original. Use this when stacking multiple visualizations..predictions
(keypoint_detection_prediction
): Predictions.color
(string
): Color of the keypoint..text_color
(string
): Text color of the keypoint..text_scale
(float
): Scale of the text..text_thickness
(integer
): Thickness of the text characters..text_padding
(integer
): Padding around the text in pixels..thickness
(integer
): Thickness of the outline in pixels..radius
(integer
): Radius of the keypoint in pixels..edges
(list_of_values
): Mapping of keypoints to edges. List of pairs of indices..
-
output
image
(image
): Image in workflows.
Example JSON definition of step Keypoint Visualization
in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/keypoint_visualization@v1",
"image": "$inputs.image",
"copy_image": true,
"predictions": "$steps.keypoint_detection_model.predictions",
"annotator_type": "<block_does_not_provide_example>",
"color": "#A351FB",
"text_color": "black",
"text_scale": 0.5,
"text_thickness": 1,
"text_padding": 10,
"thickness": 2,
"radius": 10,
"edges": "$inputs.edges"
}