diff --git a/CHANGELOG.md b/CHANGELOG.md new file mode 100644 index 0000000..4cbac93 --- /dev/null +++ b/CHANGELOG.md @@ -0,0 +1,21 @@ +## v0.0.4 - 2024-06-30 + +### Added + +- Add X struct to handle input and preprocessing +- Add Ops struct to manage common operations +- Use SIMD (fast_image_resize) to accelerate model pre-processing and post-processing.YOLOv8-seg post-processing (~120ms => ~20ms), Depth-Anything post-processing (~23ms => ~2ms). + +### Deprecated +- Mark `Ops::descale_mask()` as deprecated. + + +### Fixed + +### Changed + +### Removed + +### Refactored + +### Others diff --git a/README.md b/README.md index 3720986..69a093f 100644 --- a/README.md +++ b/README.md @@ -1,43 +1,39 @@ # usls +[![Static Badge](https://img.shields.io/crates/v/usls.svg?style=for-the-badge&logo=rust)](https://crates.io/crates/usls) [![Static Badge](https://img.shields.io/badge/Documents-usls-blue?style=for-the-badge&logo=docs.rs)](https://docs.rs/usls) [![Static Badge](https://img.shields.io/badge/GitHub-black?style=for-the-badge&logo=github)](https://github.com/jamjamjon/usls) ![Static Badge](https://img.shields.io/crates/d/usls?style=for-the-badge) + + A Rust library integrated with **ONNXRuntime**, providing a collection of **Computer Vison** and **Vision-Language** models including [YOLOv5](https://github.com/ultralytics/yolov5), [YOLOv8](https://github.com/ultralytics/ultralytics), [YOLOv9](https://github.com/WongKinYiu/yolov9), [YOLOv10](https://github.com/THU-MIG/yolov10), [RTDETR](https://arxiv.org/abs/2304.08069), [CLIP](https://github.com/openai/CLIP), [DINOv2](https://github.com/facebookresearch/dinov2), [FastSAM](https://github.com/CASIA-IVA-Lab/FastSAM), [YOLO-World](https://github.com/AILab-CVC/YOLO-World), [BLIP](https://arxiv.org/abs/2201.12086), [PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR), [Depth-Anything](https://github.com/LiheYoung/Depth-Anything), [MODNet](https://github.com/ZHKKKe/MODNet) and others. -## Recently Updated - - -| YOLOv8-Obb | -| :----------------------------: | -|| | Depth-Anything | | :----------------------------: | || +| YOLOP-v2 | Text-Detection | +| :----------------------------: | :------------------------------: | +|| | | Portrait Matting | | :----------------------------: | || +| YOLOv8-Obb | +| :----------------------------: | +|| -| YOLOP-v2 | Face-Parsing | Text-Detection | -| :----------------------------: | :------------------------------: | :------------------------------: | -|| | | - - -- 2024/06/30: **Accelerate model pre-processing and post-processing using SIMD**. YOLOv8-seg post-processing (~120ms => ~20ms), Depth-Anything post-processing (~23ms => ~2ms). - ## Supported Models | Model | Task / Type | Example | CUDA
f32 | CUDA
f16 | TensorRT
f32 | TensorRT
f16 | | :---------------------------------------------------------------: | :-------------------------: | :----------------------: | :-----------: | :-----------: | :------------------------: | :-----------------------: | -| [YOLOv5](https://github.com/ultralytics/yolov5) | Object Detection
Instance Segmentation
Classification | [demo](examples/yolov5) | ✅ | ✅ | ✅ | ✅ | -| [YOLOv8-obb](https://github.com/ultralytics/ultralytics) | Object Detection
Instance Segmentation
Classification
Oriented Object Detection
Keypoint Detection | [demo](examples/yolov8) | ✅ | ✅ | ✅ | ✅ | +| [YOLOv5](https://github.com/ultralytics/yolov5) | Classification
Object Detection
Instance Segmentation | [demo](examples/yolov5) | ✅ | ✅ | ✅ | ✅ | +| [YOLOv8](https://github.com/ultralytics/ultralytics) | Object Detection
Instance Segmentation
Classification
Oriented Object Detection
Keypoint Detection | [demo](examples/yolov8) | ✅ | ✅ | ✅ | ✅ | | [YOLOv9](https://github.com/WongKinYiu/yolov9) | Object Detection | [demo](examples/yolov9) | ✅ | ✅ | ✅ | ✅ | | [YOLOv10](https://github.com/THU-MIG/yolov10) | Object Detection | [demo](examples/yolov10) | ✅ | ✅ | ✅ | ✅ | -| [RT-DETR](https://arxiv.org/abs/2304.08069) | Object Detection | [demo](examples/rtdetr) | ✅ | ✅ | ✅ | ✅ | +| [RTDETR](https://arxiv.org/abs/2304.08069) | Object Detection | [demo](examples/rtdetr) | ✅ | ✅ | ✅ | ✅ | | [FastSAM](https://github.com/CASIA-IVA-Lab/FastSAM) | Instance Segmentation | [demo](examples/fastsam) | ✅ | ✅ | ✅ | ✅ | | [YOLO-World](https://github.com/AILab-CVC/YOLO-World) | Object Detection | [demo](examples/yolo-world) | ✅ | ✅ | ✅ | ✅ | | [DINOv2](https://github.com/facebookresearch/dinov2) | Vision-Self-Supervised | [demo](examples/dinov2) | ✅ | ✅ | ✅ | ✅ | @@ -50,57 +46,50 @@ A Rust library integrated with **ONNXRuntime**, providing a collection of **Comp | [Depth-Anything](https://github.com/LiheYoung/Depth-Anything) | Monocular Depth Estimation | [demo](examples/depth-anything) | ✅ | ✅ | ❌ | ❌ | | [MODNet](https://github.com/ZHKKKe/MODNet) | Image Matting | [demo](examples/modnet) | ✅ | ✅ | ✅ | ✅ | -## Solution Models -
-Additionally, this repo also provides some solution models. - -| Model | Example | Result | -| :---------------------------------------------------------------------------------------------------------: | :------------------------------: | :-----------------------------------------------------------------------------: | -| Lane Line Segmentation
Drivable Area Segmentation
Car Detection
车道线-可行驶区域-车辆检测 | [demo](examples/yolov8-plastic-bag) | | -| Face Parsing
人脸解析 | [demo](examples/face-parsing) | | -| Text Detection
(PPOCR-det v3, v4)
通用文本检测 | [demo](examples/db) | | -| Text Recognition
(PPOCR-rec v3, v4)
中英文-文本识别 | [demo](examples/svtr) | | -| Face-Landmark Detection
人脸 & 关键点检测 | [demo](examples/yolov8-face) | | -| Head Detection
人头检测 | [demo](examples/yolov8-head) | | -| Fall Detection
摔倒检测 | [demo](examples/yolov8-falldown) | | -| Trash Detection
垃圾检测 | [demo](examples/yolov8-plastic-bag) | | - -
- -## Demo - -``` -cargo run -r --example yolov8 # yolov9, blip, clip, dinov2, svtr, db, yolo-world... -``` - ## Installation -check **[ort guide](https://ort.pyke.io/setup/linking)** +Refer to **[ort guide](https://ort.pyke.io/setup/linking)**
For Linux or MacOS users - Firstly, download from latest release from [ONNXRuntime Releases](https://github.com/microsoft/onnxruntime/releases) - Then linking - ```shell + ```Shell export ORT_DYLIB_PATH=/Users/qweasd/Desktop/onnxruntime-osx-arm64-1.17.1/lib/libonnxruntime.1.17.1.dylib ```
+ +## Demo + +```Shell +cargo run -r --example yolov8 # yolov10, blip, clip, yolop, svtr, db, yolo-world, ... +``` + + + ## Integrate into your own project
Expand -#### 1. Add `usls` as a dependency to your project's `Cargo.toml` +### 1. Add `usls` as a dependency to your project's `Cargo.toml` -```shell -usls = { git = "https://github.com/jamjamjon/usls", rev = "xxx"} +```Shell +cargo add usls ``` -#### 2. Set `Options` and build model +Or you can use specific commit +```Shell +usls = { git = "https://github.com/jamjamjon/usls", rev = "???sha???"} +``` + + + +### 2. Set `Options` and build model ```Rust let options = Options::default() @@ -201,5 +190,24 @@ pub struct Y { - Other tasks results can be found at: `src/ys/y.rs` +
+ + +## Solution Models + + +
+Additionally, this repo also provides some solution models. + +| Model | Example | Result | +| :---------------------------------------------------------------------------------------------------------: | :------------------------------: | :-----------------------------------------------------------------------------: | +| Lane Line Segmentation
Drivable Area Segmentation
Car Detection
车道线-可行驶区域-车辆检测 | [demo](examples/yolov8-plastic-bag) | | +| Face Parsing
人脸解析 | [demo](examples/face-parsing) | | +| Text Detection
(PPOCR-det v3, v4)
通用文本检测 | [demo](examples/db) | | +| Text Recognition
(PPOCR-rec v3, v4)
中英文-文本识别 | [demo](examples/svtr) | | +| Face-Landmark Detection
人脸 & 关键点检测 | [demo](examples/yolov8-face) | | +| Head Detection
人头检测 | [demo](examples/yolov8-head) | | +| Fall Detection
摔倒检测 | [demo](examples/yolov8-falldown) | | +| Trash Detection
垃圾检测 | [demo](examples/yolov8-plastic-bag) | |
diff --git a/src/core/annotator.rs b/src/core/annotator.rs index de6af68..72f3ede 100644 --- a/src/core/annotator.rs +++ b/src/core/annotator.rs @@ -109,7 +109,7 @@ impl Annotator { self } - /// Plotting BBOXes or not + /// Plotting bboxes or not pub fn without_bboxes(mut self, x: bool) -> Self { self.without_bboxes = x; self @@ -195,7 +195,7 @@ impl Annotator { self } - /// Plotting MBRs or not + /// Plotting mbrs or not pub fn without_mbrs(mut self, x: bool) -> Self { self.without_mbrs = x; self diff --git a/src/core/engine.rs b/src/core/engine.rs index 796fabe..c0b18aa 100644 --- a/src/core/engine.rs +++ b/src/core/engine.rs @@ -32,7 +32,7 @@ pub struct OrtEngine { model_proto: onnx::ModelProto, params: usize, wbmems: usize, - pub ts: Ts, + ts: Ts, } impl OrtEngine { @@ -353,7 +353,7 @@ impl OrtEngine { Ok(ys) } - pub fn _set_ixx(x: isize, ixx: &Option, i: usize, ii: usize) -> Option { + fn _set_ixx(x: isize, ixx: &Option, i: usize, ii: usize) -> Option { match x { -1 => { match ixx { @@ -369,7 +369,8 @@ impl OrtEngine { } } - pub fn nbytes_from_onnx_dtype_id(x: usize) -> usize { + #[allow(dead_code)] + fn nbytes_from_onnx_dtype_id(x: usize) -> usize { match x { 7 | 11 | 13 => 8, // i64, f64, u64 1 | 6 | 12 => 4, // f32, i32, u32 @@ -380,7 +381,8 @@ impl OrtEngine { } } - pub fn nbytes_from_onnx_dtype(x: &ort::TensorElementType) -> usize { + #[allow(dead_code)] + fn nbytes_from_onnx_dtype(x: &ort::TensorElementType) -> usize { match x { ort::TensorElementType::Float64 | ort::TensorElementType::Uint64 @@ -399,6 +401,7 @@ impl OrtEngine { } } + #[allow(dead_code)] fn ort_dtype_from_onnx_dtype_id(value: i32) -> Option { match value { 0 => None, @@ -630,4 +633,8 @@ impl OrtEngine { pub fn memory_weights(&self) -> usize { self.wbmems } + + pub fn ts(&self) -> &Ts { + &self.ts + } } diff --git a/src/core/onnx.rs b/src/core/onnx.rs index e39b507..d88dc84 100644 --- a/src/core/onnx.rs +++ b/src/core/onnx.rs @@ -1,3 +1,5 @@ +//! ONNX file generated by prost-build. + // This file is @generated by prost-build. /// Attributes /// diff --git a/src/core/ops.rs b/src/core/ops.rs index e294f65..d617647 100644 --- a/src/core/ops.rs +++ b/src/core/ops.rs @@ -1,3 +1,5 @@ +//! Some processing functions to image and ndarray. + use anyhow::Result; use fast_image_resize as fir; use fast_image_resize::{ diff --git a/src/core/options.rs b/src/core/options.rs index 38cf86c..0298286 100644 --- a/src/core/options.rs +++ b/src/core/options.rs @@ -1,3 +1,5 @@ +//! Options for build models. + use anyhow::Result; use crate::{ diff --git a/src/core/x.rs b/src/core/x.rs index 4678fd2..72da861 100644 --- a/src/core/x.rs +++ b/src/core/x.rs @@ -4,6 +4,7 @@ use ndarray::{Array, Dim, IxDyn, IxDynImpl}; use crate::Ops; +/// Model input, alias for [`Array`] #[derive(Debug, Clone, Default)] pub struct X(pub Array); diff --git a/src/lib.rs b/src/lib.rs index 86881a8..c1d2855 100644 --- a/src/lib.rs +++ b/src/lib.rs @@ -1,3 +1,110 @@ +//! A Rust library integrated with ONNXRuntime, providing a collection of Computer Vison and Vision-Language models. +//! +//! [`OrtEngine`] provides ONNX model loading, metadata parsing, dry_run, inference and other functions, supporting EPs such as CUDA, TensorRT, CoreML, etc. You can use it as the ONNXRuntime engine for building models. +//! +//! +//! +//! + +//! # Supported models +//! | Model | Task / Type | Example | CUDA
f32 | CUDA
f16 | TensorRT
f32 | TensorRT
f16 | +//! | :---------------------------------------------------------------: | :-------------------------: | :----------------------: | :-----------: | :-----------: | :------------------------: | :-----------------------: | +//! | [YOLOv5](https://github.com/ultralytics/yolov5) | Object Detection
Instance Segmentation
Classification | [demo](examples/yolov5) | ✅ | ✅ | ✅ | ✅ | +//! | [YOLOv8-obb](https://github.com/ultralytics/ultralytics) | Object Detection
Instance Segmentation
Classification
Oriented Object Detection
Keypoint Detection | [demo](examples/yolov8) | ✅ | ✅ | ✅ | ✅ | +//! | [YOLOv9](https://github.com/WongKinYiu/yolov9) | Object Detection | [demo](examples/yolov9) | ✅ | ✅ | ✅ | ✅ | +//! | [YOLOv10](https://github.com/THU-MIG/yolov10) | Object Detection | [demo](examples/yolov10) | ✅ | ✅ | ✅ | ✅ | +//! | [RT-DETR](https://arxiv.org/abs/2304.08069) | Object Detection | [demo](examples/rtdetr) | ✅ | ✅ | ✅ | ✅ | +//! | [FastSAM](https://github.com/CASIA-IVA-Lab/FastSAM) | Instance Segmentation | [demo](examples/fastsam) | ✅ | ✅ | ✅ | ✅ | +//! | [YOLO-World](https://github.com/AILab-CVC/YOLO-World) | Object Detection | [demo](examples/yolo-world) | ✅ | ✅ | ✅ | ✅ | +//! | [DINOv2](https://github.com/facebookresearch/dinov2) | Vision-Self-Supervised | [demo](examples/dinov2) | ✅ | ✅ | ✅ | ✅ | +//! | [CLIP](https://github.com/openai/CLIP) | Vision-Language | [demo](examples/clip) | ✅ | ✅ | ✅ visual
❌ textual | ✅ visual
❌ textual | +//! | [BLIP](https://github.com/salesforce/BLIP) | Vision-Language | [demo](examples/blip) | ✅ | ✅ | ✅ visual
❌ textual | ✅ visual
❌ textual | +//! | [DB](https://arxiv.org/abs/1911.08947) | Text Detection | [demo](examples/db) | ✅ | ✅ | ✅ | ✅ | +//! | [SVTR](https://arxiv.org/abs/2205.00159) | Text Recognition | [demo](examples/svtr) | ✅ | ✅ | ✅ | ✅ | +//! | [RTMO](https://github.com/open-mmlab/mmpose/tree/main/projects/rtmo) | Keypoint Detection | [demo](examples/rtmo) | ✅ | ✅ | ❌ | ❌ | +//! | [YOLOPv2](https://arxiv.org/abs/2208.11434) | Panoptic Driving Perception | [demo](examples/yolop) | ✅ | ✅ | ✅ | ✅ | +//! | [Depth-Anything](https://github.com/LiheYoung/Depth-Anything) | Monocular Depth Estimation | [demo](examples/depth-anything) | ✅ | ✅ | ❌ | ❌ | +//! | [MODNet](https://github.com/ZHKKKe/MODNet) | Image Matting | [demo](examples/modnet) | ✅ | ✅ | ✅ | ✅ | + +//! # Use provided models for inference + +//! #### 1. Using provided [`models`] with [`Option`] + +//! ```Rust, no_run +//! use usls::{coco, models::YOLO, Annotator, DataLoader, Options, Vision}; +//! +//! let options = Options::default() +//! .with_model("yolov8m-seg-dyn.onnx")? +//! .with_trt(0) +//! .with_fp16(true) +//! .with_i00((1, 1, 4).into()) +//! .with_i02((224, 640, 800).into()) +//! .with_i03((224, 640, 800).into()) +//! .with_confs(&[0.4, 0.15]) // class_0: 0.4, others: 0.15 +//! .with_profile(false); +//! let mut model = YOLO::new(options)?; +//! ``` + +//! #### 2. Load images using [`DataLoader`] or [`image::io::Reader`] +//! +//! ```Rust, no_run +//! // Load one image +//! let x = vec![DataLoader::try_read("./assets/bus.jpg")?]; +//! +//! // Load images with batch_size = 4 +//! let dl = DataLoader::default() +//! .with_batch(4) +//! .load("./assets")?; +//! // Load one image with `image::io::Reader` +//! let x = image::io::Reader::open("myimage.png")?.decode()? +//! ``` +//! +//! #### 3. Build annotator using [`Annotator`] +//! +//! ```Rust, no_run +//! let annotator = Annotator::default() +//! .with_bboxes_thickness(7) +//! .with_saveout("YOLOv8"); +//! ``` +//! +//! #### 4. Run and annotate +//! +//! ```Rust, no_run +//! for (xs, _paths) in dl { +//! let ys = model.run(&xs)?; +//! annotator.annotate(&xs, &ys); +//! } +//! ``` +//! +//! #### 5. Parse inference results from [`Vec`] +//! For example, uou can get detection bboxes with `y.bboxes()`: +//! ```Rust, no_run +//! let ys = model.run(&xs)?; +//! for y in ys { +//! // bboxes +//! if let Some(bboxes) = y.bboxes() { +//! for bbox in bboxes { +//! println!( +//! "Bbox: {}, {}, {}, {}, {}, {}", +//! bbox.xmin(), +//! bbox.ymin(), +//! bbox.xmax(), +//! bbox.ymax(), +//! bbox.confidence(), +//! bbox.id(), +//! ) +//! } +//! } +//! } +//! ``` +//! +//! +//! # Build your own model with [`OrtEngine`] +//! +//! Refer to [Demo: Depth-Anything](https://github.com/jamjamjon/usls/blob/main/src/models/depth_anything.rs) +//! +//! + mod core; pub mod models; mod utils; diff --git a/src/models/mod.rs b/src/models/mod.rs index 2815614..d0ccfee 100644 --- a/src/models/mod.rs +++ b/src/models/mod.rs @@ -1,3 +1,5 @@ +//! Models provided: [`Blip`], [`Clip`], [`YOLO`], [`DepthAnything`], ... + mod blip; mod clip; mod db; diff --git a/src/utils/coco.rs b/src/utils/coco.rs index a42e2b2..11344cb 100644 --- a/src/utils/coco.rs +++ b/src/utils/coco.rs @@ -1,3 +1,5 @@ +//! Some constants releated with COCO dataset: [`SKELETONS_16`], [`KEYPOINTS_NAMES_17`], [`NAMES_80`] + pub const SKELETONS_16: [(usize, usize); 16] = [ (0, 1), (0, 2), diff --git a/src/utils/colormap256.rs b/src/utils/colormap256.rs index 96b8298..c9a5c28 100644 --- a/src/utils/colormap256.rs +++ b/src/utils/colormap256.rs @@ -1,3 +1,5 @@ +//! Some colormap: [`TURBO`], [`INFERNO`], [`PLASMA`], [`VIRIDIS`], [`MAGMA`], [`BENTCOOLWARM`], [`BLACKBODY`], [`EXTENDEDKINDLMANN`], [`KINDLMANN`], [`SMOOTHCOOLWARM`]. + pub const TURBO: [[u8; 3]; 256] = [ [48, 18, 59], [50, 21, 67], diff --git a/src/utils/mod.rs b/src/utils/mod.rs index 893343a..8dd3b65 100644 --- a/src/utils/mod.rs +++ b/src/utils/mod.rs @@ -8,12 +8,13 @@ pub mod colormap256; pub use colormap256::*; -pub const GITHUB_ASSETS: &str = "https://github.com/jamjamjon/assets/releases/download/v0.0.1"; -pub const CHECK_MARK: &str = "✅"; -pub const CROSS_MARK: &str = "❌"; -pub const SAFE_CROSS_MARK: &str = "❎"; +pub(crate) const GITHUB_ASSETS: &str = + "https://github.com/jamjamjon/assets/releases/download/v0.0.1"; +pub(crate) const CHECK_MARK: &str = "✅"; +pub(crate) const CROSS_MARK: &str = "❌"; +pub(crate) const SAFE_CROSS_MARK: &str = "❎"; -pub fn auto_load>(src: P, sub: Option<&str>) -> Result { +pub(crate) fn auto_load>(src: P, sub: Option<&str>) -> Result { let src = src.as_ref(); let p = if src.is_file() { src.into() @@ -33,6 +34,7 @@ pub fn auto_load>(src: P, sub: Option<&str>) -> Result { Ok(p.to_str().unwrap().to_string()) } +/// `download` sth from src to dst pub fn download + std::fmt::Debug>( src: &str, dst: P, @@ -77,7 +79,7 @@ pub fn download + std::fmt::Debug>( Ok(()) } -pub fn string_now(delimiter: &str) -> String { +pub(crate) fn string_now(delimiter: &str) -> String { let t_now = chrono::Local::now(); let fmt = format!( "%Y{}%m{}%d{}%H{}%M{}%S{}%f", @@ -86,7 +88,8 @@ pub fn string_now(delimiter: &str) -> String { t_now.format(&fmt).to_string() } -pub fn config_dir() -> PathBuf { +#[allow(dead_code)] +pub(crate) fn config_dir() -> PathBuf { match dirs::config_dir() { Some(mut d) => { d.push("usls"); @@ -99,7 +102,8 @@ pub fn config_dir() -> PathBuf { } } -pub fn home_dir(sub: Option<&str>) -> PathBuf { +#[allow(dead_code)] +pub(crate) fn home_dir(sub: Option<&str>) -> PathBuf { match dirs::home_dir() { Some(mut d) => { d.push(".usls"); diff --git a/src/ys/bbox.rs b/src/ys/bbox.rs index df5fa7c..61c460a 100644 --- a/src/ys/bbox.rs +++ b/src/ys/bbox.rs @@ -1,4 +1,4 @@ -/// Bounding Box 2D +/// Bounding Box 2D. #[derive(Clone, PartialEq, PartialOrd)] pub struct Bbox { x: f32, diff --git a/src/ys/embedding.rs b/src/ys/embedding.rs index 1145214..daaf63d 100644 --- a/src/ys/embedding.rs +++ b/src/ys/embedding.rs @@ -3,7 +3,7 @@ use ndarray::{Array, Axis, Ix2, IxDyn}; use crate::X; -/// Embedding +/// Embedding for image or text. #[derive(Clone, PartialEq, Default)] pub struct Embedding(Array); diff --git a/src/ys/keypoint.rs b/src/ys/keypoint.rs index 52e4e38..f22f6df 100644 --- a/src/ys/keypoint.rs +++ b/src/ys/keypoint.rs @@ -1,6 +1,6 @@ use std::ops::{Add, Div, Mul, Sub}; -/// Keypoint 2D +/// Keypoint 2D. #[derive(PartialEq, Clone)] pub struct Keypoint { x: f32, diff --git a/src/ys/mask.rs b/src/ys/mask.rs index 89c6476..e5896d1 100644 --- a/src/ys/mask.rs +++ b/src/ys/mask.rs @@ -1,5 +1,6 @@ use image::DynamicImage; +/// Gray-Scale Mask. #[derive(Clone, PartialEq)] pub struct Mask { mask: DynamicImage, diff --git a/src/ys/mbr.rs b/src/ys/mbr.rs index 4fab7fb..10f05e1 100644 --- a/src/ys/mbr.rs +++ b/src/ys/mbr.rs @@ -1,6 +1,6 @@ use geo::{coord, line_string, Area, BooleanOps, Coord, EuclideanDistance, LineString, Polygon}; -/// Minimum Bounding Rectangle +/// Minimum Bounding Rectangle. #[derive(Clone, PartialEq)] pub struct Mbr { ls: LineString, diff --git a/src/ys/polygon.rs b/src/ys/polygon.rs index 8580211..99539f4 100644 --- a/src/ys/polygon.rs +++ b/src/ys/polygon.rs @@ -5,6 +5,7 @@ use geo::{ use crate::{Bbox, Mbr}; +/// Polygon. #[derive(Clone, PartialEq)] pub struct Polygon { polygon: geo::Polygon, diff --git a/src/ys/prob.rs b/src/ys/prob.rs index 6a49b34..3e5ba80 100644 --- a/src/ys/prob.rs +++ b/src/ys/prob.rs @@ -1,4 +1,4 @@ -/// Probabilities for classification +/// Probabilities for classification. #[derive(Clone, PartialEq, Default)] pub struct Prob { probs: Vec, diff --git a/src/ys/y.rs b/src/ys/y.rs index 5007fb3..a1f92b0 100644 --- a/src/ys/y.rs +++ b/src/ys/y.rs @@ -1,5 +1,6 @@ use crate::{Bbox, Embedding, Keypoint, Mask, Mbr, Polygon, Prob}; +/// Inference results container for each image. #[derive(Clone, PartialEq, Default)] pub struct Y { probs: Option,