|0.3.2||Jan 13, 2021|
|0.3.0||Jul 22, 2020|
|0.2.2||Jul 11, 2020|
|0.1.4||Mar 31, 2020|
#23 in Machine learning
46 downloads per month
The crate is a Rust wrapper for AlexeyAB's Darknet.
It provides the following features:
- Provide both training and inference capabilities.
- Load config files and model weights from upstream without modifications.
- Safe type wrappers for C API. It includes network, detection and layer types.
Minimal rustc version: 1.43.0
- Error handling with anyhow
The tiny_yolov3_inference example automatically downloads the YOLOv3 tiny weights, and produces inference results in
cargo run --release --example tiny_yolov3_inference
The run_inference example is an utility program that you can test a combination of model configs and weights on image files. For example, you can test the YOLOv4 mode.
cargo run --release --example run_inference -- \ --label-file darknet/data/coco.names \ --model-cfg darknet/cfg/yolov4.cfg \ --weights yolov4.weights \ darknet/data/*.jpg
Read the example code in
examples/ to understand the actual usage. More model configs and weights can be found here: (https://pjreddie.com/darknet/yolo/).
Add our crate to your
Cargo.toml. You may take a look at the API documentation.
darknet = "^0.3.0"
We suggest earlier users update to newer version from 0.1. There are several memory leakage and several bugs fixed.
enable-cuda: Enable CUDA (expects CUDA 10.x and cuDNN 7.x).
enable-opencv: Enable OpenCV.
enable-cudnn: Enable cuDNN.
runtime: Link to darknet dynamic library. For example,
buildtime-bindgen: Generate bindings from darknet headers.
dylib: Build dynamic library instead of static.
The crate is licensed under MIT.
Huge thanks to jerry73204