23 releases (10 breaking)
0.12.8 | May 6, 2024 |
---|---|
0.11.1 | May 5, 2024 |
0.8.1 | Mar 16, 2024 |
#475 in Game dev
Used in 2 crates
110KB
1.5K
SLoC
bevy_ort 🪨
a bevy plugin for the ort library
> modnet inference example
capabilities
- load ONNX models as ORT session assets
- initialize ORT with default execution providers
- modnet bevy image <-> ort tensor IO (with feature
modnet
) - batched modnet preprocessing
- compute task pool inference scheduling
models
- lightglue (feature matching)
- modnet (photographic portrait matting)
- yolo_v8 (object detection)
- flame (parametric head model)
library usage
use bevy::prelude::*;
use bevy_ort::{
BevyOrtPlugin,
models::flame::{
FlameInput,
FlameOutput,
Flame,
FlamePlugin,
},
};
fn main() {
App::new()
.add_plugins((
DefaultPlugins,
BevyOrtPlugin,
FlamePlugin,
))
.add_systems(Startup, load_flame)
.add_systems(Startup, setup)
.add_systems(Update, on_flame_output)
.run();
}
fn load_flame(
asset_server: Res<AssetServer>,
mut flame: ResMut<Flame>,
) {
flame.onnx = asset_server.load("models/flame.onnx");
}
fn setup(
mut commands: Commands,
) {
commands.spawn(FlameInput::default());
commands.spawn(Camera3dBundle::default());
}
#[derive(Debug, Component, Reflect)]
struct HandledFlameOutput;
fn on_flame_output(
mut commands: Commands,
flame_outputs: Query<
(
Entity,
&FlameOutput,
),
Without<HandledFlameOutput>,
>,
) {
for (entity, flame_output) in flame_outputs.iter() {
commands.entity(entity)
.insert(HandledFlameOutput);
println!("{:?}", flame_output);
}
}
run the example person segmentation model (modnet)
cargo run
use an accelerated execution provider:
- windows -
cargo run --features ort/cuda
orcargo run --features ort/openvino
- macos -
cargo run --features ort/coreml
- linux -
cargo run --features ort/tensorrt
orcargo run --features ort/openvino
see complete list of ort features here: https://github.com/pykeio/ort/blob/0aec4030a5f3470e4ee6c6f4e7e52d4e495ec27a/Cargo.toml#L54
note: if you use
pip install onnxruntime
, you may need to runORT_STRATEGY=system cargo run
, see: https://docs.rs/ort/latest/ort/#how-to-get-binaries
compatible bevy versions
bevy_ort |
bevy |
---|---|
0.1.0 |
0.13 |
credits
license
This software is dual-licensed under the MIT License and the GNU General Public License version 3 (GPL-3.0).
You may choose to use this software under the terms of the MIT License OR the GNU General Public License version 3 (GPL-3.0), except as stipulated below:
The use of the yolo_v8
feature within this software is specifically governed by the GNU General Public License version 3 (GPL-3.0). By using the yolo_v8
feature, you agree to comply with the terms and conditions of the GPL-3.0.
For more details on the licenses, please refer to the LICENSE.MIT and LICENSE.GPL-3.0 files included with this software.
Dependencies
~59–99MB
~1.5M SLoC