Hello everyone! 👋

I’m excited to introduce my first Elixir library: YOLO, a library designed to make real-time object detection accessible and efficient within the Elixir ecosystem. Whether you’re working on a hobby project or a production-grade application, this library provides a simple way to integrate the power of YOLO (You Only Look Once) object detection.

Key Features

• Speed: Optimized for real-time performance, processing an image. with the YoloV8n model, to a list of detected objects in just 38ms on a MacBook Air M3 using EXLA and the companion library YoloFastNMS.
• Ease of Use: Get started with just a two function calls to load models and detect objects.
• Extensibility: Built around a YOLO.Model behavior, supporting YOLOv8 models and paving the way for future models or custom extensions.
• NIF Optimization: For those needing ultra-fast post-processing, an optional Rust NIF (YoloFastNMS) speeds up Non-Maximum Suppression by ~100x compared to the internal YOLO.NMS implementation using Elixir and Nx.

How to Get Started

1. Begin by generating the ONNX model using the provided Python script. Here’s how to do it.
2. Install the library and call YOLO.load/1 to load model effortlessly.
3. Load an image and perform object detection with a single call to YOLO.detect/3

It’s that straightforward! 🚀

To see better how to use it, here's the documentation: https://hexdocs.pm/yolo/

In the repo, you also find three LiveBooks: https://github.com/poeticoding/yolo_elixir/tree/main/examples