> 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/serverless/video-inference/use-clip.md).

# CLIP 사용

CLIP은 다음과 같이 사용할 수 있는 zero-shot 분류 모델입니다:

1. 이미지를 분류합니다;
2. 이미지를 군집화합니다;
3. 텍스트 프롬프트와 이미지 간의 유사도를 비교합니다;
4. 두 이미지 간의 유사도를 비교하는 등.

Roboflow Video Inference API는 비디오의 프레임에 대해 원시 CLIP 임베딩(선택한 모델에 따라 512 또는 768 차원)을 반환하거나, 텍스트 또는 이미지 벡터를 비교하여 각 프레임에 대한 코사인 유사도 점수를 반환할 수 있습니다.

### Video Inference API에서 CLIP 사용하기

먼저 Roboflow Python 패키지를 설치하세요:

```bash
pip install roboflow
```

다음으로, 새 Python 파일을 만들고 아래 코드를 추가하세요:

```python
from roboflow import Roboflow, CLIPModel

rf = Roboflow(api_key="API_KEY")
model = CLIPModel()

job_id, signed_url, expire_time = model.predict_video(
    "football-video.mp4",
    fps=5,
    prediction_type="batch-video",
)

results = model.poll_until_video_results(job_id)

print(results)
```

위에서 다음을 바꾸세요:

* `API_KEY`: Roboflow API key로
* `PROJECT_NAME`: Roboflow project ID로
* `MODEL_ID`: Roboflow model ID로

[API key를 가져오는 방법 알아보기](https://docs.roboflow.com/api-reference/authentication#retrieve-an-api-key).

[model ID를 가져오는 방법 알아보기](https://docs.roboflow.com/api-reference/workspace-and-project-ids).


---

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