Heatmap Visualization¶
Class: HeatmapVisualizationBlockV1
Source: inference.core.workflows.core_steps.visualizations.heatmap.v1.HeatmapVisualizationBlockV1
Draw heatmaps on an image based on provided detections. Heat accumulates over time and is drawn as a semi-transparent overlay of blurred circles.
How This Block Works¶
This block takes an image and detection predictions and draws a heatmap. The block:
- Takes an image and predictions as input.
- Accumulates heat based on the position of detections.
- Draws a semi-transparent overlay of blurred circles representing the heat.
Common Use Cases¶
- Density Analysis: Visualize the density of objects in a scene.
- Traffic Monitoring: Identify high-traffic areas.
- Retail Analytics: Analyze foot traffic in stores.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/heatmap_visualization@v1to 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.. | ✅ |
position |
str |
The position of the heatmap relative to the detection.. | ✅ |
opacity |
float |
Opacity of the overlay mask, between 0 and 1.. | ✅ |
radius |
int |
Radius of the heat circle.. | ✅ |
kernel_size |
int |
Kernel size for blurring the heatmap.. | ✅ |
top_hue |
int |
Hue at the top of the heatmap. Defaults to 0 (red).. | ✅ |
low_hue |
int |
Hue at the bottom of the heatmap. Defaults to 125 (blue).. | ✅ |
ignore_stationary |
bool |
If True, only moving objects (based on tracker ID) will contribute to the heatmap.. | ✅ |
motion_threshold |
int |
Minimum movement in pixels required to consider an object as moving.. | ✅ |
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 Heatmap Visualization in version v1.
- inputs:
Roboflow Dataset Upload,Line Counter Visualization,Mask Edge Snap,OCR Model,Image Slicer,Gaze Detection,Instance Segmentation Model,Distance Measurement,Color Visualization,Bounding Rectangle,Ellipse Visualization,Polygon Visualization,ByteTrack Tracker,Relative Static Crop,Byte Tracker,Detections Consensus,Detections Classes Replacement,Webhook Sink,Trace Visualization,Object Detection Model,Camera Focus,Stitch OCR Detections,Qwen 3.5 API,OpenAI,SAM 3,Image Threshold,Heatmap Visualization,SORT Tracker,Florence-2 Model,Halo Visualization,Detections Transformation,Path Deviation,GLM-OCR,Dot Visualization,S3 Sink,Path Deviation,Twilio SMS Notification,Seg Preview,Model Monitoring Inference Aggregator,Google Gemini,Roboflow Dataset Upload,Dynamic Zone,VLM As Classifier,Pixelate Visualization,Line Counter,Twilio SMS/MMS Notification,Polygon Zone Visualization,Motion Detection,Blur Visualization,Background Subtraction,Text Display,CSV Formatter,Stability AI Image Generation,Detections Merge,Perspective Correction,Overlap Filter,Anthropic Claude,Bounding Box Visualization,Velocity,Depth Estimation,Line Counter,Stability AI Inpainting,Polygon Visualization,SIFT,Roboflow Vision Events,VLM As Detector,Google Gemini,Label Visualization,Grid Visualization,Qwen3.5-VL,Contrast Equalization,Per-Class Confidence Filter,Triangle Visualization,Halo Visualization,Circle Visualization,Segment Anything 2 Model,Mask Visualization,OpenAI,MoonshotAI Kimi,Llama 3.2 Vision,Email Notification,Slack Notification,Detections Stitch,Detections Stabilizer,Object Detection Model,Stability AI Outpainting,Email Notification,Google Gemma API,Google Vision OCR,Identify Outliers,Image Preprocessing,Google Gemini,EasyOCR,Detections Combine,Object Detection Model,Cosine Similarity,SAM2 Video Tracker,Detection Event Log,Byte Tracker,OpenAI,Anthropic Claude,Time in Zone,Model Comparison Visualization,Roboflow Custom Metadata,YOLO-World Model,Detection Offset,Instance Segmentation Model,Single-Label Classification Model,VLM As Classifier,Detections List Roll-Up,Template Matching,Mask Area Measurement,Stitch Images,Qwen 3.6 API,SIFT Comparison,Morphological Transformation,Instance Segmentation Model,CogVLM,Crop Visualization,Camera Calibration,Florence-2 Model,Time in Zone,OC-SORT Tracker,SAM 3,Icon Visualization,Local File Sink,Detections Filter,Image Contours,JSON Parser,Keypoint Detection Model,Time in Zone,Reference Path Visualization,Anthropic Claude,Clip Comparison,VLM As Detector,LMM,Pixel Color Count,Identify Changes,Classification Label Visualization,Image Slicer,Absolute Static Crop,Image Blur,Byte Tracker,Multi-Label Classification Model,Image Convert Grayscale,SAM 3,OpenAI,Corner Visualization,Dynamic Crop,Moondream2,Keypoint Visualization,Keypoint Detection Model,QR Code Generator,Camera Focus,LMM For Classification,Morphological Transformation,Keypoint Detection Model,Contrast Enhancement,Background Color Visualization,PTZ Tracking (ONVIF),Stitch OCR Detections,SIFT Comparison - outputs:
Roboflow Dataset Upload,Line Counter Visualization,Mask Edge Snap,OCR Model,Image Slicer,Gaze Detection,Qwen2.5-VL,Instance Segmentation Model,Color Visualization,Multi-Label Classification Model,Ellipse Visualization,Polygon Visualization,ByteTrack Tracker,Single-Label Classification Model,Relative Static Crop,Barcode Detection,Trace Visualization,Object Detection Model,Qwen 3.5 API,Camera Focus,OpenAI,Buffer,SAM 3,Image Threshold,Heatmap Visualization,SORT Tracker,Florence-2 Model,Halo Visualization,GLM-OCR,Dot Visualization,Semantic Segmentation Model,Seg Preview,Google Gemini,Roboflow Dataset Upload,Clip Comparison,VLM As Classifier,Pixelate Visualization,Twilio SMS/MMS Notification,Polygon Zone Visualization,Motion Detection,Blur Visualization,Background Subtraction,Text Display,Stability AI Image Generation,Perspective Correction,Anthropic Claude,Bounding Box Visualization,Depth Estimation,Stability AI Inpainting,Polygon Visualization,SmolVLM2,SIFT,Roboflow Vision Events,VLM As Detector,Google Gemini,Label Visualization,Qwen3.5-VL,Contrast Equalization,Triangle Visualization,Halo Visualization,Circle Visualization,Segment Anything 2 Model,Mask Visualization,Dominant Color,OpenAI,MoonshotAI Kimi,Llama 3.2 Vision,Email Notification,CLIP Embedding Model,Detections Stabilizer,Detections Stitch,Object Detection Model,Stability AI Outpainting,Google Gemma API,Google Vision OCR,Google Gemini,Image Preprocessing,EasyOCR,Object Detection Model,OpenAI,SAM2 Video Tracker,Byte Tracker,Anthropic Claude,Qwen3-VL,Model Comparison Visualization,YOLO-World Model,Instance Segmentation Model,Perception Encoder Embedding Model,Semantic Segmentation Model,Single-Label Classification Model,VLM As Classifier,Template Matching,Stitch Images,Qwen 3.6 API,SIFT Comparison,Morphological Transformation,Instance Segmentation Model,CogVLM,Crop Visualization,Florence-2 Model,Camera Calibration,Multi-Label Classification Model,Time in Zone,OC-SORT Tracker,SAM 3,QR Code Detection,Icon Visualization,Image Contours,Keypoint Detection Model,Reference Path Visualization,Anthropic Claude,Clip Comparison,VLM As Detector,LMM,Pixel Color Count,Multi-Label Classification Model,Image Slicer,Absolute Static Crop,Classification Label Visualization,Image Blur,Image Convert Grayscale,SAM 3,Single-Label Classification Model,OpenAI,Corner Visualization,Dynamic Crop,Keypoint Detection Model,Moondream2,Keypoint Visualization,Camera Focus,LMM For Classification,Morphological Transformation,Keypoint Detection Model,Contrast Enhancement,Background Color Visualization
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Heatmap 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(Union[object_detection_prediction,rle_instance_segmentation_prediction,keypoint_detection_prediction,instance_segmentation_prediction]): Model predictions to visualize..metadata(video_metadata): Video metadata containing video_identifier to maintain separate state for different videos..position(string): The position of the heatmap relative to the detection..opacity(float): Opacity of the overlay mask, between 0 and 1..radius(integer): Radius of the heat circle..kernel_size(integer): Kernel size for blurring the heatmap..top_hue(integer): Hue at the top of the heatmap. Defaults to 0 (red)..low_hue(integer): Hue at the bottom of the heatmap. Defaults to 125 (blue)..ignore_stationary(boolean): If True, only moving objects (based on tracker ID) will contribute to the heatmap..motion_threshold(integer): Minimum movement in pixels required to consider an object as moving..
-
output
image(image): Image in workflows.
Example JSON definition of step Heatmap Visualization in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/heatmap_visualization@v1",
"image": "$inputs.image",
"copy_image": true,
"predictions": "$steps.object_detection_model.predictions",
"metadata": "$inputs.video_metadata",
"position": "BOTTOM_CENTER",
"opacity": 0.2,
"radius": 40,
"kernel_size": 25,
"top_hue": 0,
"low_hue": 125,
"ignore_stationary": true,
"motion_threshold": 25
}