Gaze Detection¶
Class: GazeBlockV1
Source: inference.core.workflows.core_steps.models.foundation.gaze.v1.GazeBlockV1
Run L2CS Gaze detection model on faces in images.
This block can: 1. Detect faces in images and estimate their gaze direction 2. Estimate gaze direction on pre-cropped face images
The gaze direction is represented by yaw and pitch angles in degrees.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/gaze@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
do_run_face_detection |
bool |
Whether to run face detection. Set to False if input images are pre-cropped face images.. | ✅ |
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 Gaze Detection in version v1.
- inputs:
VLM as Detector,Blur Visualization,Classification Label Visualization,Circle Visualization,SIFT Comparison,Crop Visualization,Image Contours,Relative Static Crop,Grid Visualization,VLM as Detector,Image Preprocessing,Perspective Correction,Twilio SMS Notification,Ellipse Visualization,Absolute Static Crop,VLM as Classifier,Stitch Images,Triangle Visualization,Contrast Equalization,Roboflow Dataset Upload,Stability AI Inpainting,QR Code Generator,Roboflow Dataset Upload,Image Slicer,VLM as Classifier,Background Color Visualization,Polygon Zone Visualization,Stability AI Image Generation,Model Monitoring Inference Aggregator,Roboflow Custom Metadata,Webhook Sink,Depth Estimation,Dot Visualization,Bounding Box Visualization,Camera Focus,Line Counter Visualization,Morphological Transformation,SIFT,Reference Path Visualization,Halo Visualization,SIFT Comparison,Icon Visualization,Image Blur,Image Slicer,Polygon Visualization,Pixelate Visualization,Slack Notification,Image Threshold,Image Convert Grayscale,Color Visualization,PTZ Tracking (ONVIF).md),JSON Parser,Label Visualization,Email Notification,Trace Visualization,Identify Outliers,Dynamic Zone,Dynamic Crop,Detections Consensus,Model Comparison Visualization,Email Notification,Corner Visualization,Camera Calibration,Mask Visualization,Local File Sink,Keypoint Visualization,Stability AI Outpainting,Identify Changes - outputs:
SAM 3,Blur Visualization,Circle Visualization,Crop Visualization,OpenAI,Detections Filter,Detections Classes Replacement,Ellipse Visualization,Triangle Visualization,Seg Preview,Roboflow Dataset Upload,Roboflow Dataset Upload,Background Color Visualization,Model Monitoring Inference Aggregator,Segment Anything 2 Model,Template Matching,Webhook Sink,Velocity,Distance Measurement,Dot Visualization,Florence-2 Model,Bounding Box Visualization,Line Counter Visualization,Detections Transformation,Icon Visualization,Florence-2 Model,Detection Offset,Pixelate Visualization,Detections Merge,Byte Tracker,Color Visualization,OpenAI,PTZ Tracking (ONVIF).md),Google Gemini,Label Visualization,Anthropic Claude,Llama 3.2 Vision,Google Gemini,Trace Visualization,Dynamic Zone,Dynamic Crop,Detections Consensus,Model Comparison Visualization,Corner Visualization,Camera Calibration,Keypoint Visualization,Roboflow Custom Metadata
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Gaze Detection in version v1 has.
Bindings
-
input
-
output
face_predictions(keypoint_detection_prediction): Prediction with detected bounding boxes and detected keypoints in form of sv.Detections(...) object.yaw_degrees(float): Float value.pitch_degrees(float): Float value.
Example JSON definition of step Gaze Detection in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/gaze@v1",
"images": "$inputs.image",
"do_run_face_detection": "<block_does_not_provide_example>"
}