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

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"
}