> For the complete documentation index, see [llms.txt](https://docs.roboflow.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/perception-encoder.md).

# Perception Encoder

Perception Encoder는 Meta의 vision-language embedding 모델입니다. 이미지를 텍스트와 함께 공유 embedding space로 매핑하여 유사도 검색, zero-shot 분류, 검색을 지원합니다.

{% hint style="info" %}
Perception Encoder는 Serverless Hosted API에서 사용할 수 없습니다. 다음에서 실행하세요: a [Dedicated Deployment](/roboflow/roboflow-ko/deploy/dedicated-deployments.md) 또는 [자체 호스팅 Inference](https://inference.roboflow.com/).
{% endhint %}

Perception Encoder 엔드포인트 3개를 지원합니다:

* `/perception_encoder/embed_image` — 이미지를 임베드
* `/perception_encoder/embed_text` — 문자열을 임베드
* `/perception_encoder/compare` — 이미지와 텍스트 프롬프트 목록 간의 유사도를 계산

## 코드 샘플

의존성을 설치하세요:

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

아래 샘플은 이미지를 다음으로 전송합니다: `/perception_encoder/embed_image` 그리고 embedding shape를 출력합니다. Set `URL` 를 Dedicated Deployment URL 또는 로컬 Inference 서버로 설정하세요. 다음을 전달하세요 [Roboflow API Key](https://app.roboflow.com/settings/api) 를 `API_KEY` 환경 변수.

```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]}")
```

위 코드는 embedding shape를 터미널에 출력합니다:

```
임베딩 길이: 1024
첫 번째 값: [0.0545, -0.0338, -0.0355, -0.0062, 0.0154]
```

{% hint style="info" %}
설정하세요 `URL` 를 배포 대상에 맞게:

* `http://localhost:9001` 로컬 [Inference](https://inference.roboflow.com/) 서버용.
* 귀하의 [Dedicated Deployment](/roboflow/roboflow-ko/deploy/dedicated-deployments.md) 개인 엔드포인트용 URL.
  {% endhint %}


---

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