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

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"
}