# nannou_laser [](https://travis-ci.org/nannou-org/nannou_laser) [](https://crates.io/crates/nannou_laser) [](https://github.com/nannou-org/nannou_laser/blob/master/LICENSE-MIT) [](https://docs.rs/nannou_laser/)
A cross-platform laser DAC detection and streaming API.
**nannou_laser** aims to be a higher-level API around a variety of laser protocols
providing a unified interface for detecting DACs and streaming data to them.
## Features
- **DAC Detection**: Detect all DACs available to the system.
- **Specify maximum latency**: Choose how much latency you wish to allow for
achieving the right balance between stream stability and low-latency to suit
the DAC.
- **Frame Streams**: Stream data to the DAC as a sequence of 2D vector images
without worrying about details like path optimisation, etc.
- **Raw Streams**: While frame streams are convenient, sometimes direct access
to the lower-level raw DAC stream is required (e.g. when visualising a raw
audio stream). This can be accessed via the **RawStream** API.
- **Frame Optimisation**: **nannou_laser** implements the full suite of
optimisations covered in *Accurate and Efficient Drawing Method for Laser
Projection* by Purkhet Abderyim et al. These include Graph optimisation, draw
order optimisation, blanking delays and sharp angle delays. See [the
paper](https://art-science.org/journal/v7n4/v7n4pp155/artsci-v7n4pp155.pdf)
for more details.
- **Custom frame rate**: Choose the rate at which you wish to present frames.
**nannou_laser** will determine the number of points used to draw each frame
using the connected DAC's points-per-second.
*Note: Higher level features like pattern generators and frame graphs are out of
scope for nannou_laser, though could be built downstream. The priority for this
crate is easy laser DAC detection and high-quality, high-performance data
streams.*
## Supported Protocols
Currently, **nannou_laser** only supports the open source [Ether Dream
DAC](https://ether-dream.com/) protocol. The plan is to progressively add
support for more protocols as they are needed by ourselves and users throughout
the lifetime of the project.
## License
Licensed under either of
* Apache License, Version 2.0, ([LICENSE-APACHE](LICENSE-APACHE) or
http://www.apache.org/licenses/LICENSE-2.0)
* MIT license ([LICENSE-MIT](LICENSE-MIT) or
http://opensource.org/licenses/MIT)
at your option.
**Contributions**
Unless you explicitly state otherwise, any contribution intentionally submitted
for inclusion in the work by you, as defined in the Apache-2.0 license, shall be
dual licensed as above, without any additional terms or conditions.