Face match system for medical purposes - Rust africa hackathon
# Iris — Biometric Infrastructure
**Iris** is a stateless, high-performance face recognition infrastructure built in Rust. It provides a REST API designed for hospital IT systems to identify unresponsive patients in real-time by comparing emergency captures against secure patient databases.
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## Core Philosophy
- **Stateless by Design:** Images are processed in RAM and destroyed immediately after feature extraction. No biometric data ever touches the disk.
- **Infrastructure, Not Storage:** Iris does not store medical records. It returns a mathematical similarity score between two images, allowing hospitals to link to their own secure EMR systems.
- **High Performance:** Powered by Rust and ONNX-accelerated models (YuNet and SFace) for sub-100ms inference.
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## Prerequisites
Before running Iris, ensure you have the following installed:
- **Rust:** Install via rustup
- **OpenCV 4.x:** \* _macOS:_ `brew install opencv`
- _Linux:_ `sudo apt install libopencv-dev`
- _Windows:_ Follow OpenCV-Rust installation guide
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## Installation & Setup
### Clone the Repository
```bash
git clone
github.com
cd iris
```
## Run Web
```bash
cd web
npm install
```
## Run API
```bash
cd ../api
```
## Download AI Models
Iris requires pre-trained ONNX models for detection and recognition. These files are excluded from Git due to size. Run these commands in the project root:
```Bash
chmod +x setup.sh
./setup.sh
```
Or try to do it manually by running the following commands.
```Bash
# Face Detection (YuNet)
curl -L
github.com -o face_detection_yunet_2023mar.onnx
# Face Recognition (SFace)
curl -L
github.com -o face_recognition_sface_2021dec.onnx
```
## Running the API
Start the Server
```Bash
cargo run --release
```
The API will be ava …