# Perception Encoder

Perception Encoder is Meta's vision-language embedding model. It maps images and text into a shared embedding space for similarity search, zero-shot classification, and retrieval.

{% hint style="info" %}
Perception Encoder is not available on the Serverless Hosted API. Run it on a [Dedicated Deployment](/deploy/dedicated-deployments.md) or [self-hosted Inference](https://inference.roboflow.com/).
{% endhint %}

We support three Perception Encoder endpoints:

* `/perception_encoder/embed_image` — embed an image
* `/perception_encoder/embed_text` — embed a string
* `/perception_encoder/compare` — compute similarity between an image and a list of text prompts

## Code sample

Install dependencies:

```bash
pip install requests opencv-python
```

The sample below sends an image to `/perception_encoder/embed_image` and prints the embedding shape. Set `URL` to your Dedicated Deployment URL or a local Inference server. Pass your [Roboflow API Key](https://app.roboflow.com/settings/api) via the `API_KEY` environment variable.

```python
import base64
import os
import urllib.request

import cv2
import requests

URL = "https://your-deployment.roboflow.cloud"

image_url = "https://media.roboflow.com/notebooks/examples/dog.jpeg"
image_path = "dog.jpeg"
urllib.request.urlretrieve(image_url, image_path)

image = cv2.imread(image_path)
_, buffer = cv2.imencode(".jpg", image)
image_base64 = base64.b64encode(buffer).decode("utf-8")

response = requests.post(
    f"{URL}/perception_encoder/embed_image",
    json={
        "api_key": os.getenv("API_KEY"),
        "image": {"type": "base64", "value": image_base64},
    },
)
result = response.json()
embedding = result["embeddings"][0]
print(f"Embedding length: {len(embedding)}")
print(f"First values: {embedding[:5]}")
```

The code above prints the embedding shape to the terminal:

```
Embedding length: 1024
First values: [0.0545, -0.0338, -0.0355, -0.0062, 0.0154]
```

{% hint style="info" %}
Set `URL` to match your deployment target:

* `http://localhost:9001` for a local [Inference](https://inference.roboflow.com/) server.
* Your [Dedicated Deployment](/deploy/dedicated-deployments.md) URL for a private endpoint.
  {% endhint %}


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.roboflow.com/deploy/supported-models/perception-encoder.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.