feat: ddddocr-rs 完成 core/ort/tract2 规范整改与发布

准备

  - core：内置官方字符集（OLD/BETA）与 ModelMetadata::from_builtin_*
  构造器
  - ort：导出 Session、实现 Info、修正 cuda feature 接线、共享推理工具
  - tract2：包名更名（原 ddddocr-tract 已被占用）并完成规范整改
  - 集成测试按领域拆分（ocr / det / slide / common / api_surface）
  - 发布准备：Cargo.toml 元数据、workspace 版本 0.2.4、LICENSE/
  NOTICE、README 模型下载说明

ddddocr-tract2/tests/api_surface.rs

@@ -0,0 +1,74 @@
+//! 外部视角 API 测试：验证 `ddddocr-tract2` 的公开类型与方法在外部 crate 中可正常使用。
+
+use ddddocr_core::Resize;
+use ddddocr_core::traits::{Info, Loader};
+use ddddocr_core::types::AxisDim;
+use ddddocr_tract2::loader::ModelLoader;
+use ddddocr_tract2::{
+    DetRuntime, ModelMetadata, Normalization, OcrBuilder, OcrRuntime, Session, SlideResult, Slider,
+};
+use std::path::{Path, PathBuf};
+
+fn model_path(name: &str) -> PathBuf {
+    Path::new(env!("CARGO_MANIFEST_DIR"))
+        .join("..")
+        .join("models")
+        .join(name)
+}
+
+/// 验证对外导出的类型（含 `Session` 与 core 便捷重导出）均可直接命名。
+#[test]
+fn public_types_are_nameable() {
+    let _: Option<Session> = None;
+    let _: Option<OcrBuilder> = None;
+    let _: Option<SlideResult> = None;
+    let _slider = Slider::new();
+}
+
+/// 验证构建器链式 API 可组合使用，且返回的会话类型可显式标注。
+#[test]
+fn loader_chain_builds_session() -> anyhow::Result<()> {
+    let path = model_path("common_sml2h3_f32.onnx");
+    assert!(path.exists(), "缺少测试模型: {}", path.display());
+    let _session: Session = ModelLoader::default().num_threads(4).build_for_path(path)?;
+    Ok(())
+}
+
+/// 验证 `Info` trait 能从真实会话中解析输入/输出信息。
+#[test]
+fn info_trait_returns_model_metadata() -> anyhow::Result<()> {
+    let path = model_path("common_sml2h3_f32.onnx");
+    assert!(path.exists(), "缺少测试模型: {}", path.display());
+    let session: Session = ModelLoader::default().build_for_path(path)?;
+    let metadata = ModelMetadata::from_static_slice(
+        &["a", "b"],
+        false,
+        Resize::DynamicWidth(64),
+        1,
+        Normalization::MinusOneToOne,
+    );
+    let ocr = OcrRuntime::new(session, metadata);
+
+    let inputs = ocr.input_info()?;
+    let outputs = ocr.output_info()?;
+    assert!(!inputs.is_empty());
+    assert!(!outputs.is_empty());
+    assert!(matches!(inputs[0].shape[0], AxisDim::Static(1)));
+    assert!(matches!(inputs[0].shape[2], AxisDim::Static(64)));
+
+    let model_info = ocr.model_info()?;
+    assert_eq!(model_info.inputs.len(), inputs.len());
+    assert_eq!(model_info.outputs.len(), outputs.len());
+    assert!(model_info.providers.is_none());
+    Ok(())
+}
+
+/// 验证检测运行时可以从构建的会话创建。
+#[test]
+fn det_runtime_builds_from_session() -> anyhow::Result<()> {
+    let path = model_path("common_det.onnx");
+    assert!(path.exists(), "缺少测试模型: {}", path.display());
+    let session: Session = ModelLoader::default().build_for_path(path)?;
+    let _det = DetRuntime::new(session);
+    Ok(())
+}

ddddocr-tract2/tests/common/mod.rs

@@ -0,0 +1,25 @@
+//! 集成测试共享工具。
+
+use std::path::{Path, PathBuf};
+
+/// 仓库根目录 `models/` 下模型文件的路径。
+pub fn model_path(name: &str) -> PathBuf {
+    Path::new(env!("CARGO_MANIFEST_DIR"))
+        .join("..")
+        .join("models")
+        .join(name)
+}
+
+/// 仓库根目录 `samples/` 下样例图片的路径。
+pub fn sample_path(name: &str) -> PathBuf {
+    Path::new(env!("CARGO_MANIFEST_DIR"))
+        .join("..")
+        .join("samples")
+        .join(name)
+}
+
+/// 加载图片，失败时附带路径上下文。
+pub fn load_image<P: AsRef<Path>>(path: P) -> anyhow::Result<image::DynamicImage> {
+    let path_ref = path.as_ref();
+    image::open(path_ref).map_err(|e| anyhow::anyhow!("无法加载图片 {:?}: {}", path_ref, e))
+}

ddddocr-tract2/tests/det.rs

@@ -0,0 +1,33 @@
+//! 目标检测集成测试。
+
+mod common;
+
+use common::{model_path, sample_path};
+use ddddocr_core::Detector;
+use ddddocr_core::traits::Loader;
+use ddddocr_tract2::DetRuntime;
+use ddddocr_tract2::loader::ModelLoader;
+use image::GenericImageView;
+
+/// 检测模型应能从样例图片中找到至少一个目标，且坐标在图片范围内。
+#[test]
+fn det_model_detects_targets_in_image() -> anyhow::Result<()> {
+    let session = ModelLoader::default()
+        .build_for_path(model_path("common_det.onnx"))
+        .expect("模型加载失败");
+    let det = DetRuntime::new(session);
+    let img = image::open(sample_path("det1.png")).expect("测试图片不存在");
+
+    let bboxes = Detector::new(&det).predict(&img)?;
+    assert!(!bboxes.is_empty(), "应检测到至少一个目标");
+
+    let (width, height) = img.dimensions();
+    for bbox in &bboxes {
+        assert!(bbox.x1 >= 0 && bbox.y1 >= 0, "检测框左上角不应为负");
+        assert!(
+            bbox.x2 <= width as i32 && bbox.y2 <= height as i32,
+            "检测框右下角不应超出图片范围"
+        );
+    }
+    Ok(())
+}

ddddocr-tract2/tests/ocr.rs

@@ -0,0 +1,55 @@
+//! OCR 识别与模型信息集成测试。
+
+mod common;
+
+use common::{model_path, sample_path};
+use ddddocr_core::traits::{Info, Loader};
+use ddddocr_core::{ModelMetadata, Normalization, Ocr, Resize};
+use ddddocr_tract2::OcrRuntime;
+use ddddocr_tract2::loader::ModelLoader;
+
+/// 用官方 sml2h3 f32 模型识别验证码图片，结果不应为空。
+#[test]
+fn ocr_classification_recognizes_code_image() {
+    let session = ModelLoader::default()
+        .build_for_path(model_path("common_sml2h3_f32.onnx"))
+        .expect("模型加载失败");
+    let metadata = ModelMetadata::from_builtin_beta(
+        false,
+        Resize::DynamicWidth(64),
+        1,
+        Normalization::MinusOneToOne,
+    );
+    let ocr = OcrRuntime::new(session, metadata);
+
+    let img = image::open(sample_path("code2.png")).expect("测试图片不存在");
+    let text = Ocr::builder()
+        .build_with(&ocr)
+        .predict(&img)
+        .expect("识别过程出错")
+        .into_text();
+
+    println!("识别结果: {text}");
+    assert!(!text.is_empty(), "识别结果不应为空");
+}
+
+/// 真实模型应能通过 `Info` trait 返回输入/输出张量信息。
+#[test]
+fn model_info_lists_inputs_and_outputs() -> anyhow::Result<()> {
+    let session = ModelLoader::default()
+        .build_for_path(model_path("common_huashi666_i64.onnx"))
+        .expect("建立测试模型图失败");
+    let metadata = ModelMetadata::from_builtin_beta(
+        false,
+        Resize::DynamicWidth(64),
+        1,
+        Normalization::MinusOneToOne,
+    );
+    let ocr = OcrRuntime::new(session, metadata);
+
+    let inputs = ocr.input_info()?;
+    let outputs = ocr.output_info()?;
+    assert!(!inputs.is_empty(), "模型应有输入张量信息");
+    assert!(!outputs.is_empty(), "模型应有输出张量信息");
+    Ok(())
+}

ddddocr-tract2/tests/slide.rs

@@ -0,0 +1,52 @@
+//! 滑块匹配集成测试。
+
+mod common;
+
+use common::{load_image, sample_path};
+use ddddocr_core::Slider;
+
+/// 边缘模式匹配应定位到预期坐标。
+#[test]
+fn slide_match_locates_target_position() {
+    let engine = Slider::new();
+    let target = load_image(sample_path("target1.png")).expect("请确保 samples/target1.png 存在");
+    let background = load_image(sample_path("background1.png")).expect("请确保 samples/background1.png 存在");
+
+    let start = std::time::Instant::now();
+    let result = engine
+        .slide_match(&target, &background, false)
+        .expect("Slide match 执行失败");
+    let elapsed = start.elapsed();
+
+    println!("边缘模式匹配: {result}");
+    println!("耗时: {elapsed:?}");
+
+    assert_eq!(result.target_x, 237);
+    assert_eq!(result.target_y, 77);
+    assert!(result.confidence > 0.0);
+}
+
+/// 灰度对比匹配应定位到预期坐标。
+#[test]
+fn slide_comparison_locates_target_position() {
+    let engine = Slider::new();
+    let target = load_image(sample_path("target2.jpg")).expect("请确保 samples/target2.jpg 存在");
+    let background =
+        load_image(sample_path("background2.jpg")).expect("请确保 samples/background2.jpg 存在");
+
+    let start = std::time::Instant::now();
+    let result = engine
+        .slide_comparison(&target, &background)
+        .expect("Slide comparison 执行失败");
+    let elapsed = start.elapsed();
+
+    println!(
+        "灰度对比匹配: 坐标 [x: {}, y: {}], 置信度 {:.4}",
+        result.target_x, result.target_y, result.confidence
+    );
+    println!("耗时: {elapsed:?}");
+
+    assert_eq!(result.target_x, 171);
+    assert_eq!(result.target_y, 90);
+    assert!(result.confidence > 0.0);
+}