Rust运行YoloV11时出现STATUS_ENTRYPOINT_NOT_FOUND错误（OpenCV绑定相关）的排查求助

我正在尝试用Rust跑一个简单的YoloV11推理程序，但每次运行都会弹出这个错误：

error: process didn't exit successfully: target\debug\yolov11.exe (exit code: 0xc0000139, STATUS_ENTRYPOINT_NOT_FOUND)

除此之外没有任何其他错误提示。我已经在Windows系统上安装了Clang和OpenCV 4，为了定位缺失的依赖，我用Dependency Walker工具做了检查，结果显示有一批文件缺失（文件列表太长，这里就不贴出来了）。

目前推测这个问题和OpenCV的Rust绑定有关，有没有朋友遇到过类似的情况，能帮忙分析下原因或者给个解决思路吗？

下面是我的代码配置，供大家参考：

Cargo.toml #

[package]
name = "yolov11"
version = "0.1.0"
edition = "2021"

[dependencies]
ort = { version = "2.0.0-rc.8", features = ["load-dynamic"]}
ndarray = "0.16"
image = "0.25"
opencv = { version = "0.93.3", features = ["clang-runtime"] }

main.rs #

use opencv::{
    prelude::*,
    videoio,
    core,
    highgui,
    imgproc,
};
use image::{ImageBuffer, Rgb};
use ndarray::{Array, Axis, s};
use ort::{CPUExecutionProvider, Session, SessionOutputs, inputs};
use image::imageops::FilterType;
use image::GenericImageView;

#[derive(Debug, Clone, Copy)]
struct BoundingBox {
    x1: f32,
    y1: f32,
    x2: f32,
    y2: f32
}

fn intersection(box1: &BoundingBox, box2: &BoundingBox) -> f32 {
    (box1.x2.min(box2.x2) - box1.x1.max(box2.x1)) * (box1.y2.min(box2.y2) - box1.y1.max(box2.y1))
}

fn union(box1: &BoundingBox, box2: &BoundingBox) -> f32 {
    ((box1.x2 - box1.x1) * (box1.y2 - box1.y1)) + ((box2.x2 - box2.x1) * (box2.y2 - box2.y1)) - intersection(box1, box2)
}

#[rustfmt::skip]
const YOLOV8_CLASS_LABELS: [&str; 80] = [
    "person", "bicycle", "car", "motorcycle", "airplane", "bus", "train", "truck", "boat", "traffic light",
    "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant",
    "bear", "zebra", "giraffe", "backpack", "umbrella", "handbag", "tie", "suitcase", "frisbee", "skis", "snowboard",
    "sports ball", "kite", "baseball bat", "baseball glove", "skateboard", "surfboard", "tennis racket", "bottle",
    "wine glass", "cup", "fork", "knife", "spoon", "bowl", "banana", "apple", "sandwich", "orange", "broccoli",
    "carrot", "hot dog", "pizza", "donut", "cake", "chair", "couch", "potted plant", "bed", "dining table", "toilet",
    "tv", "laptop", "mouse", "remote", "keyboard", "cell phone", "microwave", "oven", "toaster", "sink", "refrigerator",
    "book", "clock", "vase", "scissors", "teddy bear", "hair drier", "toothbrush"
];

fn main() -> Result<(), Box<dyn std::error::Error>> {
    ort::init()
        .with_execution_providers([CPUExecutionProvider::default().build()])
        .commit()?;

    let model = Session::builder()?.commit_from_file("./yolo11n.onnx")?;
    let mut cap = videoio::VideoCapture::from_file("./video.mp4", videoio::CAP_ANY)?;
    
    let frame_width = cap.get(videoio::CAP_PROP_FRAME_WIDTH)? as i32;
    let frame_height = cap.get(videoio::CAP_PROP_FRAME_HEIGHT)? as i32;
    let fps = cap.get(videoio::CAP_PROP_FPS)? as f64;

    let fourcc = videoio::VideoWriter::fourcc('m', 'p', '4', 'v')?;
    let mut writer = videoio::VideoWriter::new(
        "output.mp4",
        fourcc,
        fps,
        (frame_width, frame_height).into(),
        true,
    )?;

    let mut frame = core::Mat::default();

    while cap.read(&mut frame)? {
        let mut img_buffer = ImageBuffer::new(frame_width as u32, frame_height as u32);
        for y in 0..frame_height {
            for x in 0..frame_width {
                let pixel = frame.at_2d::<core::Vec3b>(y, x)?;
                img_buffer.put_pixel(x as u32, y as u32, Rgb([pixel[2], pixel[1], pixel[0]]));
            }
        }

        let img = image::DynamicImage::ImageRgb8(img_buffer)
            .resize_exact(640, 640, FilterType::CatmullRom);

        let mut input = Array::zeros((1, 3, 640, 640));
        for pixel in img.pixels() {
            let x = pixel.0 as usize;
            let y = pixel.1 as usize;
            let [r, g, b] = [pixel.2[0], pixel.2[1], pixel.2[2]];
            input[[0, 0, y, x]] = (r as f32) / 255.;
            input[[0, 1, y, x]] = (g as f32) / 255.;
            input[[0, 2, y, x]] = (b as f32) / 255.;
        }

        let outputs: SessionOutputs = model.run(inputs!["images" => input.view()]?)?;
        let output = outputs["output0"].try_extract_tensor::<f32>()?.t().into_owned();

        let mut boxes = Vec::new();
        let output = output.slice(s![.., .., 0]);
        for row in output.axis_iter(Axis(0)) {
            let row: Vec<_> = row.iter().copied().collect();
            let (class_id, prob) = row
                .iter()
                .skip(4)
                .enumerate()
                .map(|(index, value)| (index, *value))
                .reduce(|accum, row| if row.1 > accum.1 { row } else { accum })
                .unwrap();
            
            if prob < 0.5 {
                continue;
            }

            let label = YOLOV8_CLASS_LABELS[class_id];
            let xc = row[0] / 640. * (frame_width as f32);
            let yc = row[1] / 640. * (frame_height as f32);
            let w = row[2] / 640. * (frame_width as f32);
            let h = row[3] / 640. * (frame_height as f32);
            
            boxes.push((
                BoundingBox {
                    x1: xc - w / 2.,
                    y1: yc - h / 2.,
                    x2: xc + w / 2.,
                    y2: yc + h / 2.
                },
                label,
                prob
            ));
        }

        boxes.sort_by(|box1, box2| box2.2.total_cmp(&box1.2));
        let mut result = Vec::new();

        while !boxes.is_empty() {
            result.push(boxes[0]);
            boxes = boxes
                .iter()
                .filter(|box1| intersection(&boxes[0].0, &box1.0) / union(&boxes[0].0, &box1.0) < 0.7)
                .copied()
                .collect();
        }

        for (bbox, label, _confidence) in &result {

            let rect = core::Rect::new(
                bbox.x1 as i32,
                bbox.y1 as i32,
                (bbox.x2 - bbox.x1) as i32,
                (bbox.y2 - bbox.y1) as i32
            );
            
            imgproc::rectangle(
                &mut frame,
                rect,
                core::Scalar::new(0.0, 255.0, 0.0, 0.0), // Green color
                2,
                imgproc::LINE_8,
                0,
            )?;

            imgproc::put_text(
                &mut frame,
                label,
                core::Point::new(rect.x, rect.y - 5),
                imgproc::FONT_HERSHEY_SIMPLEX,
                0.5,
                core::Scalar::new(0.0, 255.0, 0.0, 0.0),
                1,
                imgproc::LINE_8,
                false,
            )?;
        }

        writer.write(&frame)?;

        highgui::imshow("YOLOv8 Detection", &frame)?;
        if highgui::wait_key(1)? == 27 { // ESC key
            break;
        }
    }

    Ok(())
}

备注：内容来源于stack exchange，提问作者Fuji