od_opencv 0.10.1

Object detection utilities in Rust programming language for YOLO-based neural networks in OpenCV ecosystem
Documentation 
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use std::time::Instant;

use od_opencv::{Model, DnnBackend, DnnTarget};

use opencv::{
    core::{Scalar, Vector},
    imgcodecs::imread,
    imgcodecs::imwrite,
    imgproc::LINE_4,
    imgproc::rectangle,
};

fn main() {
    // Print OpenCV version
    let cv_version = opencv::core::get_version_string().unwrap();
    println!("OpenCV version: {}", cv_version);

    let classes_labels: Vec<&str> = vec!["person", "bicycle", "car", "motorbike", "aeroplane", "bus", "train", "truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrella", "handbag", "tie", "suitcase", "frisbee", "skis", "snowboard", "sports ball", "kite", "baseball bat", "baseball glove", "skateboard", "surfboard", "tennis racket", "bottle", "wine glass", "cup", "fork", "knife", "spoon", "bowl", "banana", "apple", "sandwich", "orange", "broccoli", "carrot", "hot dog", "pizza", "donut", "cake", "chair", "sofa", "pottedplant", "bed", "diningtable", "toilet", "tvmonitor", "laptop", "mouse", "remote", "keyboard", "cell phone", "microwave", "oven", "toaster", "sink", "refrigerator", "book", "clock", "vase", "scissors", "teddy bear", "hair drier", "toothbrush"];

    let net_width = 416;
    let net_height = 416;

    let mut model = Model::darknet("pretrained/yolov3-tiny.cfg", "pretrained/yolov3-tiny.weights", (net_width, net_height), DnnBackend::Cuda, DnnTarget::Cuda).unwrap();
    let mut frame = imread("images/dog.jpg", 1).unwrap();
    let start = Instant::now();
    let (bboxes, class_ids, confidences) = model.forward(&frame, 0.25, 0.4).unwrap();
    println!("Inference time: {:?}", start.elapsed());
    for (i, bbox) in bboxes.iter().enumerate() {
        rectangle(&mut frame, *bbox, Scalar::from((0.0, 255.0, 0.0)), 2, LINE_4, 0).unwrap();
        println!("Class: {}", classes_labels[class_ids[i]]);
        println!("\tBounding box: {:?}", bbox);
        println!("\tConfidences: {}", confidences[i]);
    }
    imwrite("images/dog_yolov3_tiny.jpg", &frame, &Vector::new()).unwrap();
}