61 lines
1.8 KiB
Rust
61 lines
1.8 KiB
Rust
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#[macro_use] extern crate log;
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#[macro_use(s)] extern crate ndarray;
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extern crate stopwatch;
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use stopwatch::{Stopwatch};
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use simplelog::*;
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use v4l::{Buffer, CaptureDevice, MappedBufferStream};
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use image;
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mod visualhaar;
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// use std::fs::File;
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static mut CAMERA: Option<CaptureDevice> = None;
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fn main() {
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CombinedLogger::init(
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vec![
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TermLogger::new(LevelFilter::Info, Config::default(), TerminalMode::Mixed),
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// WriteLogger::new(LevelFilter::Info, Config::default(), File::create("my_rust_binary.log").unwrap()),
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]
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).unwrap();
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warn!("test");
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let haar = visualhaar::HaarClassifier::from_xml("haarcascade_frontalface_alt2.xml").unwrap();
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// println!("Haar: {:?}", haar);
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let sw = Stopwatch::start_new();
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let frame = image::open("/home/ruben/Documents/Projecten/2020/rust/lena_orig.png");
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// let vec: Vec<u8> = frame.data().to_vec();
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// Convert to Nannou ImageBuffer
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// let img_buffer: Option<image::ImageBuffer<image::Rgb<u8>, Vec<u8>>> = image::ImageBuffer::from_raw(640,480, frame.data().to_vec());
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match frame {
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Err(e) => {
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// no imagebuffer for this update. set haar outcomes to empy
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error!("{:?}",e);
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}
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Ok(ib) => {
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// let
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// ib.map( nannou::image::DynamicImage::ImageRgb8);
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// let ib_bw = nannou::image::imageops::grayscale(&ib);
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// _model.image = Some(nannou::image::DynamicImage::ImageLuma8(ib_bw));
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let i = ib.as_rgb8().unwrap().clone();
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let image = haar.scan_image(i).unwrap().dynamic_img;
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image.save("/home/ruben/Documents/Projecten/2020/rust/lena_orig-output.png");
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info!("Scanning for faces took {}ms", sw.elapsed_ms());
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// _model.image = Some(nannou::image::DynamicImage::ImageRgb8(ib));
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}
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}
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}
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