Perception Encoder Embedding Model

Class: PerceptionEncoderModelBlockV1

Source: inference.core.workflows.core_steps.models.foundation.perception_encoder.v1.PerceptionEncoderModelBlockV1

Use the Meta Perception Encoder model to create semantic embeddings of text and images.

This block accepts an image or string and returns an embedding. The embedding can be used to compare similarity between different images or between images and text.

Type identifier

Use the following identifier in step "type" field: roboflow_core/perception_encoder@v1to add the block as as step in your workflow.

Properties

Name	Type	Description	Refs
name	str	Unique name of step in workflows.	❌
data	str	The string or image to generate an embedding for..	✅
version	str	Variant of Perception Encoder model.	✅

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 Perception Encoder Embedding Model in version v1.

• inputs: Keypoint Detection Model, Halo Visualization, OpenAI, Stability AI Image Generation, Model Comparison Visualization, Keypoint Visualization, Crop Visualization, Image Blur, Bounding Box Visualization, Roboflow Dataset Upload, Mask Visualization, Image Slicer, Instance Segmentation Model, Ellipse Visualization, Email Notification, OpenAI, Slack Notification, VLM as Detector, Twilio SMS Notification, Webhook Sink, Label Visualization, Google Vision OCR, CSV Formatter, Stability AI Outpainting, Single-Label Classification Model, Polygon Visualization, Model Monitoring Inference Aggregator, Roboflow Custom Metadata, Reference Path Visualization, Florence-2 Model, OCR Model, Anthropic Claude, Camera Calibration, Image Preprocessing, Florence-2 Model, Image Contours, Line Counter Visualization, LMM For Classification, Clip Comparison, Corner Visualization, Stitch Images, Depth Estimation, SIFT, Blur Visualization, Image Convert Grayscale, Background Color Visualization, Image Slicer, Dynamic Crop, Local File Sink, Perspective Correction, Stitch OCR Detections, Circle Visualization, Triangle Visualization, Dot Visualization, CogVLM, Object Detection Model, VLM as Classifier, LMM, Color Visualization, OpenAI, Stability AI Inpainting, Classification Label Visualization, Absolute Static Crop, Image Threshold, Llama 3.2 Vision, Pixelate Visualization, Trace Visualization, Camera Focus, Roboflow Dataset Upload, Grid Visualization, Google Gemini, SIFT Comparison, Multi-Label Classification Model, Relative Static Crop, Polygon Zone Visualization
• outputs: Cosine Similarity, Identify Changes, Identify Outliers

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Perception Encoder Embedding Model in version v1 has.

Bindings

• input

  • data (Union[string, image]): The string or image to generate an embedding for..
  • version (string): Variant of Perception Encoder model.

• output

  • embedding (embedding): A list of floating point numbers representing a vector embedding..

Example JSON definition of step Perception Encoder Embedding Model in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/perception_encoder@v1",
    "data": "$inputs.image",
    "version": "PE-Core-B16-224"
}