2 unstable releases

0.2.0 Oct 28, 2023
0.1.0 Jun 28, 2021

#840 in Hardware support

27 downloads per month
Used in eye

MIT license

69KB
1.5K SLoC

eye-hal

eye-hal strives to provide a hardware abstraction layer (HAL) for camera-like devices in Rust. This includes common consumer grade RGB/YUV webcams as well as more sophisticated (infrared, mono) hardware. All output buffer types should be supported, even multi-planar buffers.

Apart from buffer capturing, eye-hal also provides an abstraction for hardware control. An example use-case would be white-balance or focus control.

Design

All platform (aka backend) specific code goes into src/platform. The rest should be platform agnostic code. Traits shared between platform implementations go into src/traits.rs.

There are three main entities when it comes to a HAL implementation:

  • Context A platform specific context used to query devices and general system information. It is also used to actually open a device by acquiring a handle.
  • Device This represents the sensor hardware itself. It can be used to manipulate hardware controls such as focus, white balance or gain levels. The main functionality however is in the start_stream() function, where you can create an input stream for capturing buffers.
  • Stream A stream is an entitiy which provides access to the buffers captured by the camera sensor. Only one buffer is available at any time - this is a design decision made in the current code. Whenever possible, we try to implement the stream as a zero-copy mechanism (only a view of the buffer data is returned to the caller).

Usage

Below you can find a quick example usage of this crate. It introduces the basics necessary for frame capturing.

use eye_hal::PlatformContext;
use eye_hal::traits::{Context, Device, Stream};

fn main() -> Result<()> {
    // Create a context
    let ctx = PlatformContext::default();

    // Query for available devices.
    let devices = ctx.devices()?;

    // First, we need a capture device to read images from. For this example, let's just choose
    // whatever device is first in the list.
    let dev = ctx.open_device(&devices[0])?;

    // Query for available streams and just choose the first one.
    let streams = dev.streams()?;
    let stream_desc = streams[0].clone();
    println!("Stream: {:?}", stream_desc);

    // Since we want to capture images, we need to access the native image stream of the device.
    // The backend will internally select a suitable implementation for the platform stream. On
    // Linux for example, most devices support memory-mapped buffers.
    let mut stream = dev.start_stream(&stream_desc)?;

    // Here we create a loop and just capture images as long as the device produces them. Normally,
    // this loop will run forever unless we unplug the camera or exit the program.
    loop {
        let frame = stream
            .next()
            .expect("Stream is dead")
            .expect("Failed to capture frame");
    }
}

Have a look at the provided examples for more sample applications.

Dependencies

~0–3MB
~51K SLoC