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Add YOLOv8-OBB https://youtu.be/Z7Z9pHF8wJc (#7780)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Muhammad Rizwan Munawar <chr043416@gmail.com>
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Glenn Jocher 2024-01-24 19:28:02 +01:00 • committed by GitHub
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docs/en/hub/inference-api.md
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@ -1,7 +1,7 @@
---
comments: true
description: Access object detection capabilities of YOLOv8 via our RESTful API. Learn how to use the YOLO Inference API with Python or CLI for swift object detection.
keywords: Ultralytics, YOLOv8, Inference API, object detection, RESTful API, Python, CLI, Quickstart
description: Access object detection capabilities of YOLOv8 via our RESTful API. Learn how to use the YOLO Inference API with Python or cURL for swift object detection.
keywords: Ultralytics, YOLOv8, Inference API, object detection, RESTful API, Python, cURL, Quickstart
---
# YOLO Inference API
@ -44,9 +44,9 @@ print(response.json())
In this example, replace `API_KEY` with your actual API key, `MODEL_ID` with the desired model ID, and `path/to/image.jpg` with the path to the image you want to analyze.
## Example Usage with CLI
## Example Usage with cURL
You can use the YOLO Inference API with the command-line interface (CLI) by utilizing the `curl` command. Replace `API_KEY` with your actual API key, `MODEL_ID` with the desired model ID, and `image.jpg` with the path to the image you want to analyze:
You can use the YOLO Inference API with client URL (cURL) by utilizing the `curl` command. Replace `API_KEY` with your actual API key, `MODEL_ID` with the desired model ID, and `image.jpg` with the path to the image you want to analyze:
```bash
curl -X POST "https://api.ultralytics.com/v1/predict/MODEL_ID" \
@ -103,11 +103,11 @@ The JSON list contains information about the detected objects, their coordinates
### Detect Model Format
YOLO detection models, such as `yolov8n.pt`, can return JSON responses from local inference, CLI inference, and Python inference. All of these methods produce the same JSON response format.
YOLO detection models, such as `yolov8n.pt`, can return JSON responses from local inference, cURL inference, and Python inference. All of these methods produce the same JSON response format.
!!! Example "Detect Model JSON Response"
=== "Local"
=== "`ultralytics`"
```python
from ultralytics import YOLO
@ -122,7 +122,7 @@ YOLO detection models, such as `yolov8n.pt`, can return JSON responses from loca
print(results[0].tojson())
```
=== "CLI"
=== "cURL"
```bash
curl -X POST "https://api.ultralytics.com/v1/predict/MODEL_ID" \
@ -201,11 +201,11 @@ YOLO detection models, such as `yolov8n.pt`, can return JSON responses from loca
### Segment Model Format
YOLO segmentation models, such as `yolov8n-seg.pt`, can return JSON responses from local inference, CLI inference, and Python inference. All of these methods produce the same JSON response format.
YOLO segmentation models, such as `yolov8n-seg.pt`, can return JSON responses from local inference, cURL inference, and Python inference. All of these methods produce the same JSON response format.
!!! Example "Segment Model JSON Response"
=== "Local"
=== "`ultralytics`"
```python
from ultralytics import YOLO
@ -220,7 +220,7 @@ YOLO segmentation models, such as `yolov8n-seg.pt`, can return JSON responses fr
print(results[0].tojson())
```
=== "CLI"
=== "cURL"
```bash
curl -X POST "https://api.ultralytics.com/v1/predict/MODEL_ID" \
@ -342,11 +342,11 @@ YOLO segmentation models, such as `yolov8n-seg.pt`, can return JSON responses fr
### Pose Model Format
YOLO pose models, such as `yolov8n-pose.pt`, can return JSON responses from local inference, CLI inference, and Python inference. All of these methods produce the same JSON response format.
YOLO pose models, such as `yolov8n-pose.pt`, can return JSON responses from local inference, cURL inference, and Python inference. All of these methods produce the same JSON response format.
!!! Example "Pose Model JSON Response"
=== "Local"
=== "`ultralytics`"
```python
from ultralytics import YOLO
@ -361,7 +361,7 @@ YOLO pose models, such as `yolov8n-pose.pt`, can return JSON responses from loca
print(results[0].tojson())
```
=== "CLI"
=== "cURL"
```bash
curl -X POST "https://api.ultralytics.com/v1/predict/MODEL_ID" \