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

# CLIP を使用

CLIP はゼロショット分類モデルで、次の用途に使えます:

1. 画像を分類する;
2. 画像をクラスタリングする;
3. テキストプロンプトと画像の類似度を比較する;
4. 2枚の画像の類似度を比較する、など。

Roboflow Video Inference API は、動画内の各フレームに対する生の CLIP 埋め込みを返したり（選択したモデルに応じて 512 次元または 768 次元）、テキストまたは画像ベクトルを比較して各フレームのコサイン類似度スコアを返したりできます。

### Video Inference API で CLIP を使う

まず、Roboflow Python パッケージをインストールします:

```bash
pip install roboflow
```

次に、新しい Python ファイルを作成し、以下のコードを追加します:

```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)
```

上記で、以下を置き換えます:

* `API_KEY`：を、Roboflow API key に置き換えます
* `PROJECT_NAME`：を、Roboflow project ID に置き換えます。
* `MODEL_ID`：を、Roboflow model ID に置き換えます。

[API key の取得方法を確認する](https://docs.roboflow.com/api-reference/authentication#retrieve-an-api-key).

[model ID の取得方法を確認する](https://docs.roboflow.com/api-reference/workspace-and-project-ids).


---

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