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:
S3 Sink,Email Notification,Keypoint Detection Model,Morphological Transformation,VLM As Detector,Path Deviation,SAM 3,Clip Comparison,Qwen-VL,Twilio SMS/MMS Notification,YOLO-World Model,Line Counter,Time in Zone,Polygon Zone Visualization,MoonshotAI Kimi,Stitch OCR Detections,OpenAI-Compatible LLM,VLM As Detector,OpenAI,Heatmap Visualization,Keypoint Visualization,Email Notification,Seg Preview,Llama 3.2 Vision,Stability AI Image Generation,Google Vision OCR,Anthropic Claude,Camera Focus,Label Visualization,SAM 3,Instance Segmentation Model,Path Deviation,Overlap Filter,Local File Sink,Google Gemini,Motion Detection,Byte Tracker,Background Color Visualization,Mask Edge Snap,Instance Segmentation Model,Qwen 3.5 API,Google Gemini,Polygon Visualization,Moondream2,Velocity,SIFT Comparison,Grid Visualization,Detection Event Log,Florence-2 Model,Time in Zone,OCR Model,VLM As Classifier,Detections Filter,Detections Merge,Detections Stabilizer,LMM For Classification,Keypoint Detection Model,Image Preprocessing,SIFT,Roboflow Dataset Upload,Dynamic Zone,Corner Visualization,Stability AI Outpainting,Segment Anything 2 Model,Halo Visualization,Multi-Label Classification Model,Qwen3.5-VL,Time in Zone,Detections List Roll-Up,Blur Visualization,Distance Measurement,Morphological Transformation,Trace Visualization,VLM As Classifier,Stitch OCR Detections,Gaze Detection,Reference Path Visualization,Halo Visualization,Model Comparison Visualization,Dot Visualization,JSON Parser,Pixel Color Count,Background Subtraction,Text Display,Detections Combine,Bounding Rectangle,ByteTrack Tracker,Absolute Static Crop,CSV Formatter,Florence-2 Model,Byte Tracker,Identify Outliers,Icon Visualization,Mask Area Measurement,Object Detection Model,Perspective Correction,SAM 3,BoT-SORT Tracker,Stability AI Inpainting,Image Convert Grayscale,Object Detection Model,Line Counter,QR Code Generator,OpenRouter,Model Monitoring Inference Aggregator,OpenAI,Llama 3.2 Vision,Image Threshold,OC-SORT Tracker,Anthropic Claude,Dynamic Crop,Detections Consensus,Contrast Enhancement,Bounding Box Visualization,Depth Estimation,Detection Offset,Keypoint Detection Model,Image Contours,EasyOCR,Relative Static Crop,Polygon Visualization,Google Gemma API,Template Matching,Qwen 3.6 API,Image Blur,Per-Class Confidence Filter,Anthropic Claude,Triangle Visualization,Object Detection Model,Roboflow Custom Metadata,SIFT Comparison,OpenAI,Slack Notification,Image Stack,Pixelate Visualization,Stitch Images,Single-Label Classification Model,Instance Segmentation Model,OpenAI,Image Slicer,Line Counter Visualization,Image Slicer,Cosine Similarity,Detections Classes Replacement,LMM,Roboflow Dataset Upload,Detections Transformation,Color Visualization,Google Gemini,Classification Label Visualization,Camera Focus,Camera Calibration,Detections Stitch,Byte Tracker,Ellipse Visualization,PTZ Tracking (ONVIF),Identify Changes,SORT Tracker,Mask Visualization,GLM-OCR,Crop Visualization,Circle Visualization,CogVLM,SAM2 Video Tracker,Contrast Equalization,Roboflow Vision Events,Webhook Sink,Twilio SMS Notification,MoonshotAI Kimi,Google Gemma - outputs:
Keypoint Detection Model,Clip Comparison,Morphological Transformation,SAM 3,Qwen-VL,VLM As Detector,Email Notification,Twilio SMS/MMS Notification,YOLO-World Model,MoonshotAI Kimi,Polygon Zone Visualization,OpenAI,VLM As Detector,Heatmap Visualization,Keypoint Visualization,Llama 3.2 Vision,Anthropic Claude,Stability AI Image Generation,Google Vision OCR,Seg Preview,Camera Focus,Label Visualization,SAM 3,Instance Segmentation Model,Qwen3.5,Multi-Label Classification Model,SmolVLM2,Google Gemini,Motion Detection,Background Color Visualization,Mask Edge Snap,Instance Segmentation Model,Qwen 3.5 API,Google Gemini,Polygon Visualization,Moondream2,SIFT Comparison,Florence-2 Model,Barcode Detection,Time in Zone,Single-Label Classification Model,OCR Model,VLM As Classifier,Qwen2.5-VL,Detections Stabilizer,LMM For Classification,Keypoint Detection Model,SIFT,Image Preprocessing,Roboflow Dataset Upload,Corner Visualization,Stability AI Outpainting,Segment Anything 2 Model,Multi-Label Classification Model,Halo Visualization,Qwen3-VL,Qwen3.5-VL,Semantic Segmentation Model,Blur Visualization,Perception Encoder Embedding Model,Morphological Transformation,Trace Visualization,VLM As Classifier,Gaze Detection,Reference Path Visualization,Halo Visualization,Model Comparison Visualization,Dot Visualization,Pixel Color Count,Background Subtraction,QR Code Detection,Text Display,ByteTrack Tracker,Absolute Static Crop,Florence-2 Model,Byte Tracker,Icon Visualization,Object Detection Model,Perspective Correction,SAM 3,BoT-SORT Tracker,Stability AI Inpainting,Image Convert Grayscale,Object Detection Model,OpenRouter,OpenAI,Llama 3.2 Vision,Image Threshold,OC-SORT Tracker,Anthropic Claude,Dynamic Crop,Clip Comparison,Dominant Color,Contrast Enhancement,Bounding Box Visualization,Depth Estimation,Keypoint Detection Model,CLIP Embedding Model,Image Contours,EasyOCR,Relative Static Crop,Multi-Label Classification Model,Polygon Visualization,Google Gemma API,Qwen 3.6 API,Template Matching,Single-Label Classification Model,Image Blur,Anthropic Claude,Triangle Visualization,Object Detection Model,OpenAI,Image Stack,Pixelate Visualization,Single-Label Classification Model,OpenAI,Instance Segmentation Model,Buffer,Stitch Images,Image Slicer,Line Counter Visualization,Image Slicer,Semantic Segmentation Model,LMM,Roboflow Dataset Upload,Color Visualization,Google Gemini,Classification Label Visualization,Camera Focus,Camera Calibration,Detections Stitch,Ellipse Visualization,SORT Tracker,Mask Visualization,GLM-OCR,Crop Visualization,Circle Visualization,CogVLM,SAM2 Video Tracker,Contrast Equalization,Roboflow Vision Events,MoonshotAI Kimi,Google Gemma
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[instance_segmentation_prediction,object_detection_prediction,rle_instance_segmentation_prediction,keypoint_detection_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
}