> 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-hi/deploy/supported-models/yolo11.md).

# YOLO11

हम अपने माध्यम से YOLO11 इन्फरेंसिंग का समर्थन करते हैं [Serverless Hosted API](/roboflow/roboflow-hi/deploy/serverless-hosted-api-v2.md). YOLO11 COCO पर pretrained दो task variants में उपलब्ध है:

* ऑब्जेक्ट डिटेक्शन (640 और 1280 इनपुट आकार)
* इंस्टेंस सेगमेंटेशन (640 इनपुट आकार)

self-hosted deployment के लिए, देखें [Roboflow Inference](https://inference.roboflow.com/).

## कोड उदाहरण

Dependencies इंस्टॉल करें:

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

नीचे दिया गया प्रत्येक sample Serverless Hosted API के माध्यम से inference चलाता है, response को इससे decode करता है [`supervision`](https://supervision.roboflow.com/), और एक annotated image को disk पर लिखता है। अपना [Roboflow API Key](https://app.roboflow.com/settings/api) के माध्यम से `API_KEY` environment variable.

### Object detection

Run `yolov11n-640` को एक sample image पर उपयोग करें और boxes तथा labels को annotate करें।

```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)

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

image = cv2.imread(image_path)
results = client.infer(image, model_id="yolov11n-640")
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("cars-highway-annotated.png", annotated)
```

<figure><img src="/files/3228046efe632ff67751a5c6b8766d236e3be895" alt=""><figcaption></figcaption></figure>

### Instance segmentation

Run `yolov11n-seg-640` को एक sample image पर उपयोग करें और masks तथा labels को annotate करें।

```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/bicycle.png"
image_path = "bicycle.png"
urllib.request.urlretrieve(image_url, image_path)

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

image = cv2.imread(image_path)
results = client.infer(image, model_id="yolov11n-seg-640")
detections = sv.Detections.from_inference(results)

mask_annotator = sv.MaskAnnotator()
label_annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER_OF_MASS)

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

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

<figure><img src="/files/93bf077f4c880b3ccc43f61ff8860d7c2a335844" alt=""><figcaption></figcaption></figure>

## डिफ़ॉल्ट COCO aliases

आप निम्नलिखित में से किसी भी alias को के रूप में pass कर सकते हैं `model_id`. The `inference-sdk` प्रत्येक alias को एक pretrained Roboflow Universe model पर resolve करता है।

| Task         | Alias              |
| ------------ | ------------------ |
| Detection    | `yolov11n-640`     |
| Detection    | `yolov11s-640`     |
| Detection    | `yolov11m-640`     |
| Detection    | `yolov11l-640`     |
| Detection    | `yolov11x-640`     |
| Detection    | `yolov11n-1280`    |
| Detection    | `yolov11s-1280`    |
| Detection    | `yolov11m-1280`    |
| Detection    | `yolov11l-1280`    |
| Detection    | `yolov11x-1280`    |
| Segmentation | `yolov11n-seg-640` |
| Segmentation | `yolov11s-seg-640` |
| Segmentation | `yolov11m-seg-640` |
| Segmentation | `yolov11l-seg-640` |
| Segmentation | `yolov11x-seg-640` |

The `yolo11*` prefix variants same models पर resolve होते हैं।

{% hint style="info" %}
सेट करें `api_url` को अपने deployment target से मिलाने के लिए:

* `https://serverless.roboflow.com` Serverless Hosted API के लिए।
* `http://localhost:9001` एक स्थानीय [Inference](https://inference.roboflow.com/) सर्वर।
* आपका [Dedicated Deployment](/roboflow/roboflow-hi/deploy/dedicated-deployments.md) एक private endpoint के लिए URL।
  {% endhint %}


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