Add QuickJS Feasibility Survey #10
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添加 MNN 的 JavaScript/Node.js 绑定，支持在 Node.js 应用中进行高性能深度学习推理。 主要特性： - 基于 N-API 的原生 C++ 扩展，提供接近原生的性能 - 支持 CPU、Metal、OpenCL 等多种后端 - 包含完整的 TypeScript 类型定义 - 提供简洁直观的 API 接口 - 包含多个示例：图像分类、目标检测、语义分割等 - 支持 LLM 推理功能 包含内容： - Node.js 原生绑定实现 - TypeScript 类型定义 - 构建配置 - 示例代码和测试用例 - 预训练模型示例
添加 MNN 的 Rust 语言绑定，支持在 Rust 应用中使用 MNN 进行深度学习推理，特别是 LLM 推理。 主要特性： - 使用 FFI 绑定到 MNN C++ API - 提供 Rust 风格的 API 接口 - 支持 LLM 推理功能 - 包含完整的错误处理机制 - 提供模型下载脚本 包含内容： - Rust FFI 绑定实现 - LLM API 封装 - 示例代码：llm_example、qwen_demo、qwen_inference - 构建配置 - 模型下载脚本 - 进度文档 使用方式： - 需要先构建 MNN 核心库 - 设置动态库路径后即可使用 - 支持 Qwen3-0.6B 等模型
- Add `js/test_style_transfer.js` to verify style transfer inference with MNN Node.js bindings. - Add `jimp` dependency for image processing in tests. - Fix `InterpreterWrap::CreateSession` in `js/src/interpreter.cc` to correctly return a `Session` instance. - Include test assets: `candy-9.onnx`, `input.png`, and converted `style_transfer.mnn`. - Generate `output.png` during test execution.
- Add `js/test_style_transfer.js` to verify style transfer inference with MNN Node.js bindings. - Add `jimp` dependency for image processing in tests. - Fix `InterpreterWrap::CreateSession` in `js/src/interpreter.cc` to correctly return a `Session` instance. - Include test assets: `candy-9.onnx`, `input.png`, and converted `style_transfer.mnn`. - Generate `output.png` during test execution.
…6683169831 Verify MNN JS bindings with style transfer model
…example Extends the MNN Rust bindings to include: - `Interpreter` and `Session` APIs for general model inference. - `Tensor` API for data manipulation. - `ImageProcess` API (MNN CV) for efficient image preprocessing. - New `style_transfer` example demonstrating the usage of these APIs. - Helper script `download_style_transfer_model.sh` to fetch assets and run the example. - Updated `mnn_c` C++ FFI layer to expose the necessary MNN functionalities. - Added `image` crate dependency for the example.
…example Extends the MNN Rust bindings to include: - `Interpreter` and `Session` APIs for general model inference. - `Tensor` API for data manipulation. - `ImageProcess` API (MNN CV) for efficient image preprocessing. - New `style_transfer` example demonstrating the usage of these APIs. - Helper script `download_style_transfer_model.sh` to fetch assets and run the example. - Updated `mnn_c` C++ FFI layer to expose the necessary MNN functionalities. - Added `image` crate dependency for the example.
…4747934455917 Extend Rust bindings with Interpreter, Tensor, ImageProcess and Style Transfer example
Investigated the possibility of reusing the existing N-API bindings in QuickJS. Concluded that it is infeasible due to lack of N-API support in QuickJS. Proposed an alternative solution using QuickJS FFI with the existing C API wrapper.
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QUICKJS_SURVEY.mdwhich details the investigation into running the existing MNN Node.js bindings on QuickJS. The survey concludes that direct reuse is not possible because QuickJS does not implement the N-API ABI required bynode-addon-api. It suggests using the C API wrapper (rust/csrc/mnn_c.h) via FFI as a viable alternative.PR created automatically by Jules for task 9769435063889005762 started by @Juude