> 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/yololite.md).

# YOLOLite

YOLOlite는 Roboflow의 경량 객체 탐지 모델 계열로, 낮은 지연 시간의 배포와 엣지 하드웨어를 위해 설계되었습니다. YOLOlite를 한 [Project](/roboflow/roboflow-ko/workspaces/key-concepts.md) Roboflow에서 학습하고, 당사의 [Serverless Hosted API](/roboflow/roboflow-ko/deploy/serverless-hosted-api-v2.md).

셀프 호스팅 배포는 다음을 참조하세요 [Roboflow Inference](https://inference.roboflow.com/).

YOLOlite 입력 크기는 Roboflow에서 학습하는 동안 구성됩니다.

## 사용 가능한 변형

YOLOlite는 두 가지 스케일링 계열로 제공됩니다: 표준 세트와 엣지 최적화 세트입니다. 각 계열은 다섯 가지 크기로 제공됩니다.

| 계열   | 변형                                                                                             |
| ---- | ---------------------------------------------------------------------------------------------- |
| 표준   | `yololite-n`, `yololite-s`, `yololite-m`, `yololite-l`, `yololite-xl`                          |
| Edge | `yololite-edge-n`, `yololite-edge-s`, `yololite-edge-m`, `yololite-edge-l`, `yololite-edge-xl` |

Project에서 YOLOlite 모델을 학습할 때 변형을 선택합니다. 학습된 모델은 이후 귀하의 Serverless Hosted API에서 `workspace/project/version` 경로.

## 코드 샘플

설치하세요. [Inference SDK](https://inference.roboflow.com/inference_helpers/inference_sdk/) 및 [supervision](https://supervision.roboflow.com/):

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

다음 예시는 Roboflow Project에서 학습된 YOLOlite 모델에 대해 탐지를 실행하고, 응답을 `supervision`, 상자와 레이블을 그리고 주석이 포함된 PNG를 저장합니다. 바꾸세요 `your-project/1` 자신의 `project/version`. 귀하의 [Roboflow API Key](https://app.roboflow.com/settings/api) 를 `API_KEY` 환경 변수.

```python
import os
import urllib.request

import cv2
import supervision as sv
from inference_sdk import InferenceHTTPClient

image_url = "https://storage.googleapis.com/com-roboflow-marketing/notebooks/examples/cars-highway.png"
image_path = "cars-highway.png"
urllib.request.urlretrieve(image_url, image_path)

image = cv2.imread(image_path)

client = InferenceHTTPClient(
    api_url="https://serverless.roboflow.com",
    api_key=os.getenv("API_KEY"),
)
results = client.infer(image, model_id="your-project/1")

detections = sv.Detections.from_inference(results)

box_annotator = sv.BoxAnnotator()
label_annotator = sv.LabelAnnotator()

annotated = box_annotator.annotate(scene=image.copy(), detections=detections)
annotated = label_annotator.annotate(scene=annotated, detections=detections)

cv2.imwrite("annotated.png", annotated)
```

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

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


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## 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, and the optional `goal` query parameter:

```
GET https://docs.roboflow.com/roboflow/roboflow-ko/deploy/supported-models/yololite.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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.