# MyYoloInference

**Repository Path**: mrsoymilk/MyYoloInference

## Basic Information

- **Project Name**: MyYoloInference
- **Description**: fork from github, Inference of Yolo11 .onnx model using OpenCV 
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-04-18
- **Last Updated**: 2025-04-21

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Yolo Inference

## Support

- YOLO Classify Inference
- YOLO Detect Inference
- YOLO Segment Inference
- YOLO Pose Inference
- YOLO Obb Inference

## Requirement

1. `.onnx` format
2. Use OpenCV(>= 4.8, Otherwise, some parts may need to be modified)

## Vendor

- [Netron is a viewer for neural network, deep learning and machine learning models.](https://netron.app/)
- [JSON Editor Online](https://jsoneditoronline.org)
- [cpp-base64](https://github.com/ReneNyffenegger/cpp-base64)
- [Base64 to Image Decode](https://www.rapidtables.com/web/tools/base64-to-image.html)

## Usage

```bash
mkdir build
cd build
cmake ..
make -j7
./test_explict      # explic usage of MyYoloInference library
./test_implict      # implic usage of MyYoloInference library
./test_binary_input # binary image in, json format string out
./test_video your_model your_video # video test
```

## Result

### classify

![yolo11 classify](README/result-classify.jpg)

### detect

![yolo11 detect](README/result-detect.jpg)

### segment

![yolo11 segment](README/result-segment.jpg)

### pose

![yolo11 pose](README/result-pose.jpg)

### obb

![yolo11 obb](README/result-obb.jpg)

### video

![video test](README/ikun.gif)

## Other Tools

install yolo:

```bash
pip install ultralytics
```

to onnx format:

```bash
yolo export model=yolo11n-seg.pt format=onnx
```

use Netron:

![onnx info](README/onnx-info.jpg)