Keypoint Visualization¶
Version v1
¶
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 |
The unique name of this step.. | ❌ |
copy_image |
bool |
Duplicate the image contents (vs overwriting the image in place). Deselect for chained visualizations that should stack on previous ones where the intermediate state is not needed.. | ✅ |
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.. | ✅ |
The Refs column marks possibility to parametrise the property with dynamic values available
in workflow
runtime. See Bindings for more info.
Available Connections¶
Check what blocks you can connect to Keypoint Visualization
in version v1
.
- inputs:
Triangle Visualization
,Detections Classes Replacement
,Image Blur
,Detections Filter
,Image Preprocessing
,Keypoint Detection Model
,Line Counter Visualization
,Keypoint Visualization
,Blur Visualization
,Mask Visualization
,Background Color Visualization
,Model Comparison Visualization
,Ellipse Visualization
,Pixelate Visualization
,Corner Visualization
,Camera Focus
,Reference Path Visualization
,Relative Static Crop
,Image Contours
,Image Convert Grayscale
,Crop Visualization
,Stitch Images
,Label Visualization
,Polygon Visualization
,Stability AI Inpainting
,Dynamic Crop
,Trace Visualization
,Polygon Zone Visualization
,SIFT
,Image Threshold
,Color Visualization
,Image Slicer
,Perspective Correction
,Absolute Static Crop
,Bounding Box Visualization
,Halo Visualization
,SIFT Comparison
,Detection Offset
,Circle Visualization
,Dot Visualization
,Detections Transformation
- outputs:
OpenAI
,Clip Comparison
,Keypoint Detection Model
,Florence-2 Model
,Line Counter Visualization
,Barcode Detection
,Model Comparison Visualization
,Background Color Visualization
,Ellipse Visualization
,Corner Visualization
,QR Code Detection
,Anthropic Claude
,Object Detection Model
,Time in zone
,Template Matching
,YOLO-World Model
,Google Vision OCR
,Pixel Color Count
,Stability AI Inpainting
,Single-Label Classification Model
,SIFT
,Dominant Color
,Color Visualization
,Image Slicer
,Bounding Box Visualization
,Perspective Correction
,Halo Visualization
,LMM For Classification
,Roboflow Dataset Upload
,OCR Model
,Mask Visualization
,Dot Visualization
,Triangle Visualization
,Image Blur
,Image Preprocessing
,Keypoint Visualization
,Blur Visualization
,Pixelate Visualization
,Camera Focus
,VLM as Detector
,Multi-Label Classification Model
,Detections Stitch
,Reference Path Visualization
,VLM as Classifier
,Relative Static Crop
,Image Contours
,OpenAI
,Crop Visualization
,Stitch Images
,Image Convert Grayscale
,Google Gemini
,Clip Comparison
,Label Visualization
,Segment Anything 2 Model
,Polygon Visualization
,Dynamic Crop
,Trace Visualization
,Polygon Zone Visualization
,CogVLM
,Image Threshold
,LMM
,Absolute Static Crop
,SIFT Comparison
,Roboflow Dataset Upload
,Circle Visualization
,Instance Segmentation Model
The available connections depend on its binding kinds. Check what binding kinds
Keypoint Visualization
in version v1
has.
Bindings
-
input
image
(image
): The input image for this step..copy_image
(boolean
): Duplicate the image contents (vs overwriting the image in place). Deselect for chained visualizations that should stack on previous ones where the intermediate state is not needed..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..
-
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
}