> 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/supported-models/l2cs-net.md).

# L2Cs-Net

L2Cs-Net は、顔を検出し、各顔の yaw と pitch の角度を予測する gaze direction estimation model です。弊社の [Serverless Hosted API](/roboflow/roboflow-jp/deploy/serverless-hosted-api-v2.md).

## コードサンプル

次を呼び出します: `/gaze/gaze_detection` endpoint を直接使って `curl`:

```bash
curl --location 'https://serverless.roboflow.com/gaze/gaze_detection' \
  --header 'Content-Type: application/json' \
  --data '{
    "api_key": "YOUR_API_KEY",
    "image": {"type": "url", "value": "https://media.roboflow.com/inference/man.jpg"}
  }'
```

SDK から同じ呼び出しを行います。インストールしてください:

```bash
pip install inference-sdk
```

以下のコードサンプルは `detect_gazes`は、同じ `/gaze/gaze_detection` endpoint にアクセスします。あなたの [Roboflow API Key](https://app.roboflow.com/settings/api) を `API_KEY` env variable。

```python
import os
import urllib.request
from inference_sdk import InferenceHTTPClient

image_url = "https://media.roboflow.com/inference/man.jpg"
image_path = "man.jpg"
urllib.request.urlretrieve(image_url, image_path)

client = InferenceHTTPClient(
    api_url="https://serverless.roboflow.com",
    api_key=os.getenv("API_KEY"),
).select_api_v1()

result = client.detect_gazes(image_path)

for prediction in result[0]["predictions"]:
    face = prediction["face"]
    yaw = prediction["yaw"]
    pitch = prediction["pitch"]
    print(f"Face at ({face['x']}, {face['y']}) - yaw: {yaw:.3f}, pitch: {pitch:.3f}")
```

{% hint style="info" %}
設定 `api_url` をデプロイ先に合わせて設定してください:

* `https://serverless.roboflow.com` は Serverless Hosted API 用です。
* `http://localhost:9001` ローカルの [Inference](https://inference.roboflow.com/) サーバー用です。
* あなたの [Dedicated Deployment](/roboflow/roboflow-jp/deploy/dedicated-deployments.md) の URL はプライベートエンドポイント用です。
  {% endhint %}

レスポンスには、次を含むリストが含まれています: `predictions` （それぞれが次を持ちます `face` bounding box, `landmarks`, `yaw`、および `pitch` （ラジアン単位）、 `time`, `time_face_det`、および `time_gaze_det`.

self-hosted deployments と追加の例については、次を参照してください: [Roboflow Inference docs](https://inference.roboflow.com/).


---

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