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feat: 添加 Windows 交叉编译支持与 ONNX Runtime MinGW 兼容方案

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- 新增 C API shim (ort_api_shim.h) 解决 MinGW 与 ONNX Runtime 的 SAL 注解/_stdcall 兼容性问题
- 新增轻量级 C++ 包装器 (ort_minimal) 替代 onnxruntime_cxx_api.h
- cmake/dependencies.cmake 支持 Windows/ Linux 平台自动识别依赖路径
- 修复音频采集 paNonInterleaved bug（指针被误解析为 float 导致 RMS=inf）
- 修复 Windows 热键和 UI 相关代码
- 添加 MinGW 交叉编译工具链配置

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
Alvin Young 2026-06-11 11:50:16 +08:00
parent 01a39ddc8c
commit 8c2e787a25
14 changed files with 888 additions and 129 deletions
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9
.gitignore vendored
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@ -64,3 +64,12 @@ configs/config.json
# 日志
*.log
# 构建目录（所有平台）
build-win/
build_linux/
build_win/
dist/
# Windows 第三方依赖（ONNX Runtime Win x64 预编译二进制）
third_party/onnxruntime-win-x64/

31
CMakeLists.txt
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@ -55,6 +55,7 @@ set(SOURCES
# Core (平台无关)
src/core/stt_engine.cpp
src/core/sense_voice_engine.cpp
src/core/ort_minimal.cpp
src/core/sense_voice_features.cpp
src/core/sense_voice_tokenizer.cpp
src/core/mel_spectrogram.cpp
@ -166,6 +167,36 @@ target_compile_options(${PROJECT_NAME} PRIVATE
$<$<CXX_COMPILER_ID:MSVC>:/W4>
)
# ============================================================================
# Windows DLL 复制（交叉编译时自动拷贝到输出目录）
# ============================================================================
if(WIN32)
if(ONNXRUNTIME_DLL)
add_custom_command(TARGET ${PROJECT_NAME} POST_BUILD
COMMAND ${CMAKE_COMMAND} -E copy_if_different
"${ONNXRUNTIME_DLL}"
$<TARGET_FILE_DIR:${PROJECT_NAME}>
COMMENT "拷贝 onnxruntime.dll 到输出目录"
)
endif()
if(ONNXRUNTIME_PROVIDERS_DLL)
add_custom_command(TARGET ${PROJECT_NAME} POST_BUILD
COMMAND ${CMAKE_COMMAND} -E copy_if_different
"${ONNXRUNTIME_PROVIDERS_DLL}"
$<TARGET_FILE_DIR:${PROJECT_NAME}>
COMMENT "拷贝 onnxruntime_providers_shared.dll 到输出目录"
)
endif()
if(PORTAUDIO_DLL)
add_custom_command(TARGET ${PROJECT_NAME} POST_BUILD
COMMAND ${CMAKE_COMMAND} -E copy_if_different
"${PORTAUDIO_DLL}"
$<TARGET_FILE_DIR:${PROJECT_NAME}>
COMMENT "拷贝 libportaudio.dll 到输出目录"
)
endif()
endif()
# ============================================================================
# 资源文件
# ============================================================================

102
cmake/dependencies.cmake
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@ -2,21 +2,39 @@ include(FetchContent)
set(THIRD_PARTY_DIR "${CMAKE_CURRENT_SOURCE_DIR}/third_party")
# ----------------------------------------------------------------------------
# ============================================================================
# ONNX Runtime
# ----------------------------------------------------------------------------
set(ONNXRUNTIME_ROOT "${THIRD_PARTY_DIR}/onnxruntime")
find_library(ONNXRUNTIME_LIB
NAMES onnxruntime
PATHS "${ONNXRUNTIME_ROOT}/lib"
NO_DEFAULT_PATH
)
find_path(ONNXRUNTIME_INCLUDE_DIR
NAMES onnxruntime_cxx_api.h
PATHS "${ONNXRUNTIME_ROOT}/include"
NO_DEFAULT_PATH
)
# ============================================================================
if(WIN32)
# Windows 版本：onnxruntime.dll
set(ONNXRUNTIME_ROOT "${THIRD_PARTY_DIR}/onnxruntime-win-x64")
if(NOT EXISTS "${ONNXRUNTIME_ROOT}/lib/onnxruntime.dll")
# 回退到旧目录名
set(ONNXRUNTIME_ROOT "${THIRD_PARTY_DIR}/onnxruntime")
endif()
# 直接用 DLL 路径（MinGW 可直接链接 DLL）
if(EXISTS "${ONNXRUNTIME_ROOT}/lib/onnxruntime.dll")
set(ONNXRUNTIME_LIB "${ONNXRUNTIME_ROOT}/lib/onnxruntime.dll")
set(ONNXRUNTIME_DLL "${ONNXRUNTIME_ROOT}/lib/onnxruntime.dll")
set(ONNXRUNTIME_INCLUDE_DIR "${ONNXRUNTIME_ROOT}/include")
endif()
if(NOT ONNXRUNTIME_INCLUDE_DIR)
set(ONNXRUNTIME_INCLUDE_DIR "${ONNXRUNTIME_ROOT}/include")
endif()
else()
# Linux 版本：libonnxruntime.so
set(ONNXRUNTIME_ROOT "${THIRD_PARTY_DIR}/onnxruntime")
find_library(ONNXRUNTIME_LIB
NAMES onnxruntime
PATHS "${ONNXRUNTIME_ROOT}/lib"
NO_DEFAULT_PATH
)
find_path(ONNXRUNTIME_INCLUDE_DIR
NAMES onnxruntime_cxx_api.h
PATHS "${ONNXRUNTIME_ROOT}/include"
NO_DEFAULT_PATH
)
endif()
if(ONNXRUNTIME_LIB AND ONNXRUNTIME_INCLUDE_DIR)
set(ONNXRUNTIME_LIBRARIES ${ONNXRUNTIME_LIB})
@ -27,21 +45,45 @@ else()
message(WARNING "未找到 ONNX Runtime，推理功能将使用占位实现")
endif()
# ----------------------------------------------------------------------------
# ============================================================================
# PortAudio
# ----------------------------------------------------------------------------
# ============================================================================
set(PORTAUDIO_ROOT "${THIRD_PARTY_DIR}/portaudio")
find_library(PORTAUDIO_LIB
NAMES portaudio libportaudio
PATHS "${PORTAUDIO_ROOT}/lib"
NO_DEFAULT_PATH
)
find_path(PORTAUDIO_INCLUDE_DIR
NAMES portaudio.h
PATHS "${PORTAUDIO_ROOT}/include"
NO_DEFAULT_PATH
)
if(WIN32)
# Windows 版本：libportaudio.dll 在 bin/ 目录
if(EXISTS "${PORTAUDIO_ROOT}/bin/libportaudio.dll")
set(PORTAUDIO_LIB "${PORTAUDIO_ROOT}/bin/libportaudio.dll")
set(PORTAUDIO_DLL "${PORTAUDIO_ROOT}/bin/libportaudio.dll")
endif()
if(EXISTS "${PORTAUDIO_ROOT}/include/portaudio.h")
set(PORTAUDIO_INCLUDE_DIR "${PORTAUDIO_ROOT}/include")
endif()
else()
# Linux 版本：优先使用构建好的本地库
find_library(PORTAUDIO_LIB
NAMES portaudio libportaudio
PATHS "${PORTAUDIO_ROOT}/lib" /usr/lib64 /usr/lib /usr/local/lib
NO_DEFAULT_PATH
)
find_path(PORTAUDIO_INCLUDE_DIR
NAMES portaudio.h
PATHS "${PORTAUDIO_ROOT}/include" /usr/include /usr/include/portaudio /usr/local/include
NO_DEFAULT_PATH
)
# 回退：通过 pkg-config 查找
if(NOT PORTAUDIO_LIB OR NOT PORTAUDIO_INCLUDE_DIR)
find_package(PkgConfig QUIET)
if(PKG_CONFIG_FOUND)
pkg_check_modules(PORTAUDIO_PC portaudio-2.0 QUIET)
if(PORTAUDIO_PC_FOUND)
set(PORTAUDIO_LIBRARIES ${PORTAUDIO_PC_LIBRARIES})
set(PORTAUDIO_INCLUDE_DIRS ${PORTAUDIO_PC_INCLUDE_DIRS})
endif()
endif()
endif()
endif()
if(PORTAUDIO_LIB AND PORTAUDIO_INCLUDE_DIR)
set(PORTAUDIO_LIBRARIES ${PORTAUDIO_LIB})
@ -52,9 +94,9 @@ else()
message(WARNING "未找到 PortAudio，音频采集功能将使用占位实现")
endif()
# ----------------------------------------------------------------------------
# ============================================================================
# dr_libs (header-only)
# ----------------------------------------------------------------------------
# ============================================================================
set(DR_LIBS_INCLUDE_DIR "${THIRD_PARTY_DIR}/dr_libs")
if(EXISTS "${DR_LIBS_INCLUDE_DIR}/dr_wav.h")
message(STATUS "找到 dr_libs: ${DR_LIBS_INCLUDE_DIR}")
@ -63,7 +105,7 @@ else()
message(WARNING "未找到 dr_libs 头文件")
endif()
# ----------------------------------------------------------------------------
# ============================================================================
# nlohmann/json (header-only)
# ----------------------------------------------------------------------------
# ============================================================================
set(NLOHMANN_JSON_INCLUDE_DIR "${THIRD_PARTY_DIR}/nlohmann_json")

15
cmake/mingw-toolchain.cmake Normal file
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@ -0,0 +1,15 @@
# MinGW Windows 交叉编译工具链
set(CMAKE_SYSTEM_NAME Windows)
set(CMAKE_SYSTEM_PROCESSOR x86_64)
set(CMAKE_C_COMPILER x86_64-w64-mingw32-gcc)
set(CMAKE_CXX_COMPILER x86_64-w64-mingw32-g++)
set(CMAKE_RC_COMPILER x86_64-w64-mingw32-windres)
set(CMAKE_FIND_ROOT_PATH /usr/x86_64-w64-mingw32/sys-root/mingw)
# 搜索策略：允许在 sysroot 和宿主路径之外查找
set(CMAKE_FIND_ROOT_PATH_MODE_PROGRAM NEVER)
set(CMAKE_FIND_ROOT_PATH_MODE_LIBRARY BOTH)
set(CMAKE_FIND_ROOT_PATH_MODE_INCLUDE BOTH)
set(CMAKE_FIND_ROOT_PATH_MODE_PACKAGE BOTH)

26
run.sh
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@ -1,11 +1,31 @@
#!/bin/bash
# Impress Voice Input 启动脚本
# 设置 ONNX Runtime / PortAudio 库路径并启动应用
set -e
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
BUILD_DIR="${SCRIPT_DIR}/build"
ONNXRUNTIME_LIB_DIR="${SCRIPT_DIR}/third_party/onnxruntime/lib"
PORTAUDIO_LIB_DIR="${SCRIPT_DIR}/third_party/portaudio/lib"
# 设置库路径
export LD_LIBRARY_PATH="${SCRIPT_DIR}/third_party/onnxruntime/lib:${SCRIPT_DIR}/third_party/portaudio/lib:${LD_LIBRARY_PATH}"
# 检查可执行文件
if [ ! -f "${BUILD_DIR}/impress_voice_input" ]; then
echo "错误：未找到可执行文件，请先编译："
echo " mkdir -p build && cd build"
echo " cmake .. -DCMAKE_BUILD_TYPE=RelWithDebInfo"
echo " cmake --build . -j\$(nproc)"
exit 1
fi
# 运行
# 检查 ONNX Runtime
if [ ! -f "${ONNXRUNTIME_LIB_DIR}/libonnxruntime.so" ]; then
echo "警告：ONNX Runtime 未部署，推理功能将不可用"
echo " 请按照 third_party/README.md 部署 ONNX Runtime"
fi
# 设置库路径（ONNX Runtime 优先，PortAudio 回退到系统）
export LD_LIBRARY_PATH="${ONNXRUNTIME_LIB_DIR}:${PORTAUDIO_LIB_DIR}:${LD_LIBRARY_PATH}"
# 启动应用
exec "${BUILD_DIR}/impress_voice_input" "$@"

30
src/audio/audio_capture.cpp
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@ -13,6 +13,7 @@ namespace impress {
// 预分配缓冲区，避免在实时回调中分配内存
static constexpr int kMaxBufferSize = 8192;
#ifdef HAVE_PORTAUDIO
// 全局 PortAudio 初始化状态
static bool gPaInitialized = false;
@ -33,6 +34,7 @@ static void safePaTerminate() {
gPaInitialized = false;
}
}
#endif
// 回调上下文：独立于 Impl 的 POD 结构，供静态回调使用
struct CallbackContext {
@ -52,13 +54,13 @@ struct AudioCapture::Impl {
CallbackContext ctx;
};
#ifdef HAVE_PORTAUDIO
static int paCallback(const void* input, void* /*output*/,
unsigned long frameCount,
const PaStreamCallbackTimeInfo* /*timeInfo*/,
PaStreamCallbackFlags /*statusFlags*/,
void* userData)
{
#ifdef HAVE_PORTAUDIO
auto* ctx = static_cast<CallbackContext*>(userData);
const float* samples = static_cast<const float*>(input);
@ -88,11 +90,15 @@ static int paCallback(const void* input, void* /*output*/,
emit ctx->owner->audioDataReady(data, ctx->sampleRate);
return paContinue;
#else
(void)input; (void)frameCount; (void)userData;
return 0;
#endif
}
#else
// 占位回调（无 PortAudio 时不使用）
static int paCallbackStub(const void*, void*, unsigned long,
const int*, int, void*)
{
return 0;
}
#endif
AudioCapture::AudioCapture(QObject* parent)
: QObject(parent)
@ -107,8 +113,8 @@ AudioCapture::~AudioCapture() {
QStringList AudioCapture::getDeviceList() {
QStringList devices;
devices << "默认设备";
#ifdef HAVE_PORTAUDIO
devices << "默认设备";
if (!ensurePaInitialized()) {
LOG_ERROR(kTag, "PortAudio 初始化失败");
return devices;
@ -124,6 +130,9 @@ QStringList AudioCapture::getDeviceList() {
.arg(info->defaultSampleRate).arg(hostApiName);
}
}
#else
devices << "PortAudio 未启用（占位设备）";
LOG_WARNING(kTag, "PortAudio 未编译启用，设备列表为占位");
#endif
return devices;
}
@ -195,7 +204,9 @@ bool AudioCapture::start(int deviceIndex, int sampleRate, int bufferSizeMs) {
PaStreamParameters inputParams{};
inputParams.device = devIdx;
inputParams.channelCount = 1;
inputParams.sampleFormat = paFloat32 | paNonInterleaved;
inputParams.sampleFormat = paFloat32;
// 不使用 paNonInterleaved：input 指针直接是 float* 数组（interleaved mono），
// 回调中可以安全地 static_cast<const float*>(input)
// 使用高延迟以避免回调过快
inputParams.suggestedLatency = devInfo->defaultHighInputLatency;
@ -232,8 +243,9 @@ bool AudioCapture::start(int deviceIndex, int sampleRate, int bufferSizeMs) {
.arg(deviceIndex).arg(sampleRate).arg(bufferSizeMs));
return true;
#else
LOG_ERROR(kTag, "PortAudio 未编译启用");
emit error("PortAudio 未编译启用");
(void)deviceIndex; (void)sampleRate; (void)bufferSizeMs;
LOG_ERROR(kTag, "PortAudio 未编译启用，无法启动采集");
emit error("PortAudio 未编译启用，请在 third_party/portaudio/ 中部署后重新编译");
return false;
#endif
}

62
src/core/ort_api_shim.h Normal file
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@ -0,0 +1,62 @@
#pragma once
/**
* @brief ONNX Runtime C API Shim
*
* 包装 onnxruntime_c_api.h 以解决 MinGW 交叉编译兼容性问题：
* 1. SAL 注解（specstrings.h 中的宏与 MinGW 不兼容）
* 2. _stdcall 调用约定导致函数声明语法错误
*
* 关键：必须在包含 onnxruntime_c_api.h 之前定义这些宏，
* 因为 header 内部的 #define 会使用它们。
*/
#ifdef HAVE_ONNXRUNTIME
#ifndef ORT_API_SHIM_H
#define ORT_API_SHIM_H
#ifdef _WIN32
#define ORT_DLL_IMPORT
/* 在 specstrings.h 被包含之前，抢先定义 SAL 注解为空。
onnxruntime_c_api.h 第 74 行 #include <specstrings.h>，
如果 specstrings.h 用 #ifndef 保护，我们的定义就不会被覆盖。
即使被覆盖，_stdcall 下面的定义也会生效。 */
#define _Success_(x)
#define _Check_return_
#define _Ret_maybenull_
#define _In_
#define _In_z_
#define _In_opt_
#define _In_opt_z_
#define _Out_
#define _Outptr_
#define _Out_opt_
#define _Inout_
#define _Inout_opt_
#define _Frees_ptr_opt_
#define _Ret_notnull_
#define _In_reads_(x)
#define _Inout_updates_(x)
#define _Out_writes_(x)
#define _Inout_updates_all_(x)
#define _Out_writes_bytes_all_(x)
#define _Out_writes_all_(x)
#define _Outptr_result_maybenull_(x)
#define _In_reads_opt_(x)
#define _Outptr_result_buffer_maybenull_(x)
#define _Return_type_success_(x)
#define _Out_writes_bytes_all_opt_(x)
#define _In_reads_bytes_(x)
/* 将 _stdcall 定义为空。
onnxruntime_c_api.h 第 86 行 #define ORT_API_CALL _stdcall，
所以当 ORT_API_CALL 展开为 _stdcall 后，_stdcall 再展开为空。
这样最终的函数声明没有调用约定修饰，MinGW 可以正常解析。 */
#define _stdcall
#define __stdcall
#endif /* _WIN32 */
#include <onnxruntime_c_api.h>
#endif /* ORT_API_SHIM_H */
#endif /* HAVE_ONNXRUNTIME */

365
src/core/ort_minimal.cpp Normal file
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@ -0,0 +1,365 @@
/**
* @brief ONNX Runtime 轻量级 C API 包装器 - 实现
*
* 直接使用 C API，避免 onnxruntime_cxx_api.h 的 MinGW 兼容性问题。
*/
#ifdef HAVE_ONNXRUNTIME
#include "ort_minimal.h"
#include <cstring>
#include <sstream>
#include <vector>
#ifdef _WIN32
#include <windows.h>
#endif
namespace ort {
/**
* 获取 OrtApi 指针
*
* 调用路径: OrtGetApiBase() -> OrtApiBase -> GetApi(version) -> OrtApi
*/
const OrtApi* getApi() {
static const OrtApi* api = nullptr;
if (!api) {
const OrtApiBase* apiBase = OrtGetApiBase();
api = apiBase->GetApi(ORT_API_VERSION);
}
return api;
}
// ============================================================================
// Env
// ============================================================================
Env::Env(OrtLoggingLevel logLevel, const char* logId) {
const OrtApi* api = getApi();
OrtStatus* status = api->CreateEnv(logLevel, logId, &env_);
if (status) {
const char* msg = api->GetErrorMessage(status);
throw Exception(msg ? msg : "CreateEnv failed");
}
}
Env::~Env() {
if (env_) {
const OrtApi* api = getApi();
api->ReleaseEnv(env_);
}
}
// ============================================================================
// SessionOptions
// ============================================================================
SessionOptions::SessionOptions() {
const OrtApi* api = getApi();
OrtStatus* status = api->CreateSessionOptions(&opts_);
if (status) {
const char* msg = api->GetErrorMessage(status);
throw Exception(msg ? msg : "CreateSessionOptions failed");
}
}
SessionOptions::~SessionOptions() {
if (opts_) {
const OrtApi* api = getApi();
api->ReleaseSessionOptions(opts_);
}
}
void SessionOptions::setIntraOpNumThreads(int n) {
const OrtApi* api = getApi();
OrtStatus* status = api->SetIntraOpNumThreads(opts_, n);
if (status) {
const char* msg = api->GetErrorMessage(status);
throw Exception(msg ? msg : "SetIntraOpNumThreads failed");
}
}
void SessionOptions::setGraphOptimizationLevel(GraphOptimizationLevel level) {
const OrtApi* api = getApi();
OrtStatus* status = api->SetSessionGraphOptimizationLevel(opts_, level);
if (status) {
const char* msg = api->GetErrorMessage(status);
throw Exception(msg ? msg : "SetSessionGraphOptimizationLevel failed");
}
}
// ============================================================================
// Session
// ============================================================================
Session::Session(const Env& env, const char* modelPath, const SessionOptions& opts) {
const OrtApi* api = getApi();
#ifdef _WIN32
// Windows: ORTCHAR_T = wchar_t, 需要将 UTF-8 转换为 UTF-16
int len = MultiByteToWideChar(CP_UTF8, 0, modelPath, -1, nullptr, 0);
std::vector<wchar_t> widePath(len);
MultiByteToWideChar(CP_UTF8, 0, modelPath, -1, widePath.data(), len);
OrtStatus* status = api->CreateSession(env.ptr(), widePath.data(), opts.ptr(), &session_);
#else
OrtStatus* status = api->CreateSession(env.ptr(), modelPath, opts.ptr(), &session_);
#endif
if (status) {
const char* msg = api->GetErrorMessage(status);
throw Exception(msg ? msg : "CreateSession failed");
}
}
#ifdef _WIN32
Session::Session(const Env& env, const wchar_t* modelPath, const SessionOptions& opts) {
const OrtApi* api = getApi();
OrtStatus* status = api->CreateSession(env.ptr(), modelPath, opts.ptr(), &session_);
if (status) {
const char* msg = api->GetErrorMessage(status);
throw Exception(msg ? msg : "CreateSession failed");
}
}
#endif
Session::~Session() {
if (session_) {
const OrtApi* api = getApi();
api->ReleaseSession(session_);
}
}
size_t Session::getInputCount() const {
const OrtApi* api = getApi();
size_t count = 0;
OrtStatus* status = api->SessionGetInputCount(session_, &count);
if (status) {
const char* msg = api->GetErrorMessage(status);
throw Exception(msg ? msg : "SessionGetInputCount failed");
}
return count;
}
size_t Session::getOutputCount() const {
const OrtApi* api = getApi();
size_t count = 0;
OrtStatus* status = api->SessionGetOutputCount(session_, &count);
if (status) {
const char* msg = api->GetErrorMessage(status);
throw Exception(msg ? msg : "SessionGetOutputCount failed");
}
return count;
}
std::string Session::getInputName(size_t index) const {
const OrtApi* api = getApi();
char* name = nullptr;
OrtAllocator* allocator = nullptr;
OrtStatus* status = api->GetAllocatorWithDefaultOptions(&allocator);
if (status) {
const char* msg = api->GetErrorMessage(status);
throw Exception(msg ? msg : "GetAllocatorWithDefaultOptions failed");
}
status = api->SessionGetInputName(session_, index, allocator, &name);
if (status) {
const char* msg = api->GetErrorMessage(status);
throw Exception(msg ? msg : "SessionGetInputName failed");
}
std::string result(name);
// 不要释放 name - allocator 分配的内存由 allocator 管理
return result;
}
std::string Session::getOutputName(size_t index) const {
const OrtApi* api = getApi();
char* name = nullptr;
OrtAllocator* allocator = nullptr;
OrtStatus* status = api->GetAllocatorWithDefaultOptions(&allocator);
if (status) {
const char* msg = api->GetErrorMessage(status);
throw Exception(msg ? msg : "GetAllocatorWithDefaultOptions failed");
}
status = api->SessionGetOutputName(session_, index, allocator, &name);
if (status) {
const char* msg = api->GetErrorMessage(status);
throw Exception(msg ? msg : "SessionGetOutputName failed");
}
std::string result(name);
return result;
}
// ============================================================================
// MemoryInfo
// ============================================================================
MemoryInfo::MemoryInfo(OrtMemoryInfo* info) : info_(info) {}
MemoryInfo MemoryInfo::createCpu(OrtAllocatorType type, OrtMemType memType) {
const OrtApi* api = getApi();
OrtMemoryInfo* info = nullptr;
OrtStatus* status = api->CreateCpuMemoryInfo(type, memType, &info);
if (status) {
const char* msg = api->GetErrorMessage(status);
throw Exception(msg ? msg : "CreateCpuMemoryInfo failed");
}
return MemoryInfo(info);
}
MemoryInfo::~MemoryInfo() {
if (info_) {
const OrtApi* api = getApi();
api->ReleaseMemoryInfo(info_);
}
}
// ============================================================================
// Value
// ============================================================================
Value::Value(OrtValue* value) : value_(value) {}
Value Value::fromRaw(OrtValue* value) {
return Value(value);
}
Value Value::createTensor(const MemoryInfo& info, float* data, size_t elemCount,
const int64_t* shape, size_t shapeLen) {
const OrtApi* api = getApi();
OrtValue* value = nullptr;
OrtStatus* status = api->CreateTensorWithDataAsOrtValue(
info.ptr(), data, elemCount * sizeof(float),
shape, shapeLen, ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT, &value);
if (status) {
const char* msg = api->GetErrorMessage(status);
throw Exception(msg ? msg : "CreateTensorWithDataAsOrtValue failed");
}
return Value(value);
}
Value Value::createTensor(const MemoryInfo& info, int32_t* data, size_t elemCount,
const int64_t* shape, size_t shapeLen) {
const OrtApi* api = getApi();
OrtValue* value = nullptr;
OrtStatus* status = api->CreateTensorWithDataAsOrtValue(
info.ptr(), data, elemCount * sizeof(int32_t),
shape, shapeLen, ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32, &value);
if (status) {
const char* msg = api->GetErrorMessage(status);
throw Exception(msg ? msg : "CreateTensorWithDataAsOrtValue failed");
}
return Value(value);
}
Value::~Value() {
if (value_) {
const OrtApi* api = getApi();
api->ReleaseValue(value_);
}
}
std::vector<int64_t> Value::getShape() const {
const OrtApi* api = getApi();
OrtTensorTypeAndShapeInfo* info = nullptr;
OrtStatus* status = api->GetTensorTypeAndShape(value_, &info);
if (status) {
const char* msg = api->GetErrorMessage(status);
throw Exception(msg ? msg : "GetTensorTypeAndShape failed");
}
size_t dimCount = 0;
status = api->GetDimensionsCount(info, &dimCount);
std::vector<int64_t> shape(dimCount);
if (dimCount > 0) {
status = api->GetDimensions(info, shape.data(), dimCount);
}
api->ReleaseTensorTypeAndShapeInfo(info);
if (status) {
const char* msg = api->GetErrorMessage(status);
throw Exception(msg ? msg : "GetDimensions failed");
}
return shape;
}
const float* Value::getTensorData() const {
const OrtApi* api = getApi();
void* data = nullptr;
OrtStatus* status = api->GetTensorMutableData(value_, &data);
if (status) {
const char* msg = api->GetErrorMessage(status);
throw Exception(msg ? msg : "GetTensorMutableData failed");
}
return static_cast<const float*>(data);
}
Value::Value(Value&& other) noexcept : value_(other.value_) {
other.value_ = nullptr;
}
Value& Value::operator=(Value&& other) noexcept {
if (this != &other) {
if (value_) {
const OrtApi* api = getApi();
api->ReleaseValue(value_);
}
value_ = other.value_;
other.value_ = nullptr;
}
return *this;
}
// ============================================================================
// RunOptions
// ============================================================================
RunOptions::RunOptions() {
const OrtApi* api = getApi();
OrtStatus* status = api->CreateRunOptions(&opts_);
if (status) {
const char* msg = api->GetErrorMessage(status);
throw Exception(msg ? msg : "CreateRunOptions failed");
}
}
RunOptions::~RunOptions() {
if (opts_) {
const OrtApi* api = getApi();
api->ReleaseRunOptions(opts_);
}
}
// ============================================================================
// run
// ============================================================================
std::vector<Value> run(Session& session,
const RunOptions& runOptions,
const char* const* inputNames,
Value* inputValues,
size_t inputCount,
const char* const* outputNames,
size_t outputCount)
{
const OrtApi* api = getApi();
// 准备输入输出 OrtValue 指针数组
std::vector<OrtValue*> inputPtrs(inputCount);
for (size_t i = 0; i < inputCount; i++) {
inputPtrs[i] = inputValues[i].ptr();
}
std::vector<OrtValue*> outputPtrs(outputCount, nullptr);
OrtStatus* status = api->Run(
session.ptr(),
runOptions.ptr(),
inputNames, inputPtrs.data(), static_cast<int>(inputCount),
outputNames, static_cast<int>(outputCount),
outputPtrs.data());
if (status) {
const char* msg = api->GetErrorMessage(status);
throw Exception(msg ? msg : "Run failed");
}
std::vector<Value> results;
results.reserve(outputCount);
for (size_t i = 0; i < outputCount; i++) {
results.emplace_back(Value::fromRaw(outputPtrs[i]));
}
return results;
}
} // namespace ort
#endif // HAVE_ONNXRUNTIME

134
src/core/ort_minimal.h Normal file
View File

@ -0,0 +1,134 @@
#pragma once
/**
* @brief ONNX Runtime 轻量级 C API 包装器
*
* 替代 onnxruntime_cxx_api.h（该文件与 MinGW 存在 ABI 兼容性问题）。
* 直接使用 C API（onnxruntime_c_api.h），用异常替代 C 风格返回值。
*/
#ifdef HAVE_ONNXRUNTIME
#ifndef ORT_MINIMAL_H
#define ORT_MINIMAL_H
/* 使用 shim 头文件处理 MinGW 兼容性问题 */
#include "ort_api_shim.h"
#include <string>
#include <vector>
#include <memory>
#include <stdexcept>
namespace ort {
/** 异常类型 */
class Exception : public std::runtime_error {
public:
explicit Exception(const char* msg) : std::runtime_error(msg) {}
explicit Exception(const std::string& msg) : std::runtime_error(msg) {}
};
/** 获取 API 基础指针（内部使用） */
const OrtApi* getApi();
/** Env: ONNX Runtime 环境 */
class Env {
public:
explicit Env(OrtLoggingLevel logLevel = ORT_LOGGING_LEVEL_WARNING,
const char* logId = "ort");
~Env();
OrtEnv* ptr() const { return env_; }
Env(const Env&) = delete;
Env& operator=(const Env&) = delete;
private:
OrtEnv* env_ = nullptr;
};
/** SessionOptions: 会话配置选项 */
class SessionOptions {
public:
SessionOptions();
~SessionOptions();
OrtSessionOptions* ptr() const { return opts_; }
void setIntraOpNumThreads(int n);
void setGraphOptimizationLevel(GraphOptimizationLevel level);
SessionOptions(const SessionOptions&) = delete;
SessionOptions& operator=(const SessionOptions&) = delete;
private:
OrtSessionOptions* opts_ = nullptr;
};
/** Session: 推理会话 */
class Session {
public:
Session(const Env& env, const char* modelPath, const SessionOptions& opts);
Session(const Env& env, const wchar_t* modelPath, const SessionOptions& opts);
~Session();
OrtSession* ptr() const { return session_; }
size_t getInputCount() const;
size_t getOutputCount() const;
std::string getInputName(size_t index) const;
std::string getOutputName(size_t index) const;
Session(const Session&) = delete;
Session& operator=(const Session&) = delete;
private:
OrtSession* session_ = nullptr;
};
/** MemoryInfo: 内存信息 */
class MemoryInfo {
public:
static MemoryInfo createCpu(OrtAllocatorType type = OrtDeviceAllocator,
OrtMemType memType = OrtMemTypeCPU);
~MemoryInfo();
const OrtMemoryInfo* ptr() const { return info_; }
private:
explicit MemoryInfo(OrtMemoryInfo* info);
OrtMemoryInfo* info_ = nullptr;
};
/** Value: 张量值 */
class Value {
public:
static Value createTensor(const MemoryInfo& info, float* data, size_t elemCount,
const int64_t* shape, size_t shapeLen);
static Value createTensor(const MemoryInfo& info, int32_t* data, size_t elemCount,
const int64_t* shape, size_t shapeLen);
~Value();
OrtValue* ptr() const { return value_; }
std::vector<int64_t> getShape() const;
const float* getTensorData() const;
Value(Value&& other) noexcept;
Value& operator=(Value&& other) noexcept;
Value(const Value&) = delete;
Value& operator=(const Value&) = delete;
private:
explicit Value(OrtValue* value);
OrtValue* value_ = nullptr;
public:
/** @brief 从原始指针构造（用于接收 C API 返回的值） */
static Value fromRaw(OrtValue* value);
};
/** RunOptions: 推理选项 */
class RunOptions {
public:
RunOptions();
~RunOptions();
OrtRunOptions* ptr() const { return opts_; }
private:
OrtRunOptions* opts_ = nullptr;
};
/** 推理执行 */
std::vector<Value> run(Session& session,
const RunOptions& runOptions,
const char* const* inputNames,
Value* inputValues,
size_t inputCount,
const char* const* outputNames,
size_t outputCount);
} // namespace ort
#endif // ORT_MINIMAL_H
#endif // HAVE_ONNXRUNTIME

84
src/core/sense_voice_engine.cpp
View File

@ -3,6 +3,7 @@
#include "sense_voice_tokenizer.h"
#include "sense_voice_cmvn.h"
#include "audio_processor.h"
#include "ort_minimal.h"
#include "utils/logger.h"
#include "utils/timer.h"
@ -19,11 +20,6 @@
#include <algorithm>
#include <cmath>
// ONNX Runtime headers
#ifdef HAVE_ONNXRUNTIME
#include <onnxruntime_cxx_api.h>
#endif
static const char* const kTag = "SenseVoiceEngine";
/**
@ -93,9 +89,9 @@ static int languageToInt(const QString& lang) {
*/
struct SenseVoiceEngine::Impl {
#ifdef HAVE_ONNXRUNTIME
std::unique_ptr<Ort::Env> env;
std::unique_ptr<Ort::SessionOptions> sessionOptions;
std::unique_ptr<Ort::Session> session;
std::unique_ptr<ort::Env> env;
std::unique_ptr<ort::SessionOptions> sessionOptions;
std::unique_ptr<ort::Session> session;
std::vector<std::string> inputNames;
std::vector<std::string> outputNames;
@ -111,11 +107,11 @@ struct SenseVoiceEngine::Impl {
{
QMutexLocker locker(&mutex);
try {
auto envPtr = std::make_unique<Ort::Env>(
auto envPtr = std::make_unique<ort::Env>(
ORT_LOGGING_LEVEL_WARNING, "impress_sensevoice");
auto optionsPtr = std::make_unique<Ort::SessionOptions>();
optionsPtr->SetIntraOpNumThreads(numThreads);
optionsPtr->SetGraphOptimizationLevel(
auto optionsPtr = std::make_unique<ort::SessionOptions>();
optionsPtr->setIntraOpNumThreads(numThreads);
optionsPtr->setGraphOptimizationLevel(
GraphOptimizationLevel::ORT_ENABLE_ALL);
if (device == "gpu") {
@ -125,14 +121,17 @@ struct SenseVoiceEngine::Impl {
LOG_INFO(kTag, QString("正在加载 SenseVoice 模型: %1 (线程: %2)")
.arg(modelPath).arg(numThreads));
auto sessionPtr = std::make_unique<Ort::Session>(
auto sessionPtr = std::make_unique<ort::Session>(
*envPtr,
#ifdef _WIN32
modelPath.toStdWString().c_str(),
#else
modelPath.toUtf8().constData(),
#endif
*optionsPtr);
Ort::AllocatorWithDefaultOptions allocator;
size_t inputCount = sessionPtr->GetInputCount();
size_t outputCount = sessionPtr->GetOutputCount();
size_t inputCount = sessionPtr->getInputCount();
size_t outputCount = sessionPtr->getOutputCount();
LOG_INFO(kTag, QString("模型有 %1 个输入, %2 个输出")
.arg(inputCount).arg(outputCount));
@ -141,15 +140,13 @@ struct SenseVoiceEngine::Impl {
outputNames.clear();
for (size_t i = 0; i < inputCount; i++) {
auto namePtr = sessionPtr->GetInputNameAllocated(i, allocator);
inputNames.emplace_back(namePtr.get());
LOG_DEBUG(kTag, QString("输入 #%1: %2").arg(i).arg(namePtr.get()));
inputNames.emplace_back(sessionPtr->getInputName(i));
LOG_DEBUG(kTag, QString("输入 #%1: %2").arg(i).arg(QString::fromStdString(inputNames.back())));
}
for (size_t i = 0; i < outputCount; i++) {
auto namePtr = sessionPtr->GetOutputNameAllocated(i, allocator);
outputNames.emplace_back(namePtr.get());
LOG_DEBUG(kTag, QString("输出 #%1: %2").arg(i).arg(namePtr.get()));
outputNames.emplace_back(sessionPtr->getOutputName(i));
LOG_DEBUG(kTag, QString("输出 #%1: %2").arg(i).arg(QString::fromStdString(outputNames.back())));
}
env = std::move(envPtr);
@ -174,7 +171,7 @@ struct SenseVoiceEngine::Impl {
LOG_INFO(kTag, QString("SenseVoice 模型加载成功: %1").arg(modelPath));
return true;
} catch (const Ort::Exception& e) {
} catch (const ort::Exception& e) {
errorMsg = QString("ONNX 异常: %1").arg(e.what());
LOG_ERROR(kTag, errorMsg);
return false;
@ -185,6 +182,21 @@ struct SenseVoiceEngine::Impl {
}
}
QMutex mutex;
#else
// 占位实现：无 ONNX Runtime 时仅提供基本结构
bool loadInWorker(const QString& /*modelPath*/,
const QString& /*tokensPath*/,
const QString& /*device*/,
int /*numThreads*/,
QString& errorMsg)
{
errorMsg = "ONNX Runtime 未安装，推理功能不可用。"
"请在 third_party/onnxruntime/ 中部署 ONNX Runtime 后重新编译。";
LOG_ERROR(kTag, errorMsg);
return false;
}
QMutex mutex;
#endif
};
@ -206,11 +218,13 @@ bool SenseVoiceEngine::loadModelSync(const QString& modelPath,
if (loaded_) {
LOG_WARNING(kTag, "模型已加载，先卸载再加载");
// 内联清理，避免调用 unloadModel() 导致 mutex 递归死锁
#ifdef HAVE_ONNXRUNTIME
impl_->session.reset();
impl_->sessionOptions.reset();
impl_->env.reset();
impl_->features.reset();
impl_->tokenizer = SenseVoiceTokenizer();
#endif
loaded_ = false;
}
@ -235,11 +249,13 @@ void SenseVoiceEngine::loadModelAsync(const QString& modelPath,
if (loaded_) {
LOG_WARNING(kTag, "模型已加载，先卸载再加载");
// 内联清理，避免调用 unloadModel() 导致 mutex 递归死锁
#ifdef HAVE_ONNXRUNTIME
impl_->session.reset();
impl_->sessionOptions.reset();
impl_->env.reset();
impl_->features.reset();
impl_->tokenizer = SenseVoiceTokenizer();
#endif
loaded_ = false;
}
@ -417,7 +433,7 @@ RecognitionResult SenseVoiceEngine::infer(const std::vector<float>& samples,
// 输入: x, x_length, language, text_norm
int64_t xShape[] = {1, numFrames, kLFROutputDim};
auto memInfo = Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeCPU);
auto memInfo = ort::MemoryInfo::createCpu(OrtDeviceAllocator, OrtMemTypeCPU);
int32_t xLengthVal = numFrames;
int64_t xLengthShape[] = {1};
@ -429,14 +445,14 @@ RecognitionResult SenseVoiceEngine::infer(const std::vector<float>& samples,
int32_t textNormVal = kTextNormWithITN;
int64_t textNormShape[] = {1};
std::vector<Ort::Value> inputTensors;
inputTensors.push_back(Ort::Value::CreateTensor<float>(
std::vector<ort::Value> inputTensors;
inputTensors.push_back(ort::Value::createTensor(
memInfo, lfrFeatures.data(), lfrFeatures.size(), xShape, 3));
inputTensors.push_back(Ort::Value::CreateTensor<int32_t>(
inputTensors.push_back(ort::Value::createTensor(
memInfo, &xLengthVal, 1, xLengthShape, 1));
inputTensors.push_back(Ort::Value::CreateTensor<int32_t>(
inputTensors.push_back(ort::Value::createTensor(
memInfo, &langVal, 1, langShape, 1));
inputTensors.push_back(Ort::Value::CreateTensor<int32_t>(
inputTensors.push_back(ort::Value::createTensor(
memInfo, &textNormVal, 1, textNormShape, 1));
// 4. 运行推理
@ -446,8 +462,10 @@ RecognitionResult SenseVoiceEngine::infer(const std::vector<float>& samples,
std::vector<const char*> outputNamePtrs;
for (auto& name : impl_->outputNames) outputNamePtrs.push_back(name.c_str());
auto outputTensors = impl_->session->Run(
Ort::RunOptions{nullptr},
ort::RunOptions runOptions;
auto outputTensors = ort::run(
*impl_->session,
runOptions,
inputNamePtrs.data(), inputTensors.data(), inputTensors.size(),
outputNamePtrs.data(), outputNamePtrs.size());
@ -455,8 +473,8 @@ RecognitionResult SenseVoiceEngine::infer(const std::vector<float>& samples,
// 5. 解析输出 logits [1, seq_len, 25055]
auto& outputTensor = outputTensors[0];
auto shape = outputTensor.GetTensorTypeAndShapeInfo().GetShape();
const float* logitsData = outputTensor.GetTensorData<float>();
auto shape = outputTensor.getShape();
const float* logitsData = outputTensor.getTensorData();
LOG_DEBUG(kTag, QString("输出维度: [%1, %2, %3]")
.arg(shape[0]).arg(shape[1]).arg(shape[2]));

74
src/core/stt_engine.cpp
View File

@ -2,6 +2,7 @@
#include "mel_spectrogram.h"
#include "whisper_tokenizer.h"
#include "audio_processor.h"
#include "ort_minimal.h"
#include "utils/logger.h"
#include "utils/timer.h"
@ -15,11 +16,6 @@
#include <cmath>
#include <cstring>
// ONNX Runtime headers
#ifdef HAVE_ONNXRUNTIME
#include <onnxruntime_cxx_api.h>
#endif
static const char* const kTag = "STTEngine";
// Whisper 常量
@ -33,9 +29,9 @@ namespace impress {
*/
struct STTEngine::Impl {
#ifdef HAVE_ONNXRUNTIME
std::unique_ptr<Ort::Env> env;
std::unique_ptr<Ort::SessionOptions> sessionOptions;
std::unique_ptr<Ort::Session> session;
std::unique_ptr<ort::Env> env;
std::unique_ptr<ort::SessionOptions> sessionOptions;
std::unique_ptr<ort::Session> session;
std::vector<std::string> inputNames;
std::vector<std::string> outputNames;
@ -50,11 +46,11 @@ struct STTEngine::Impl {
{
QMutexLocker locker(&mutex);
try {
auto envPtr = std::make_unique<Ort::Env>(
auto envPtr = std::make_unique<ort::Env>(
ORT_LOGGING_LEVEL_WARNING, "impress_voice");
auto optionsPtr = std::make_unique<Ort::SessionOptions>();
optionsPtr->SetIntraOpNumThreads(numThreads);
optionsPtr->SetGraphOptimizationLevel(
auto optionsPtr = std::make_unique<ort::SessionOptions>();
optionsPtr->setIntraOpNumThreads(numThreads);
optionsPtr->setGraphOptimizationLevel(
GraphOptimizationLevel::ORT_ENABLE_ALL);
if (device == "gpu") {
@ -63,14 +59,17 @@ struct STTEngine::Impl {
LOG_INFO(kTag, QString("正在加载模型: %1 (线程: %2)").arg(modelPath).arg(numThreads));
auto sessionPtr = std::make_unique<Ort::Session>(
auto sessionPtr = std::make_unique<ort::Session>(
*envPtr,
#ifdef _WIN32
modelPath.toStdWString().c_str(),
#else
modelPath.toUtf8().constData(),
#endif
*optionsPtr);
Ort::AllocatorWithDefaultOptions allocator;
size_t inputCount = sessionPtr->GetInputCount();
size_t outputCount = sessionPtr->GetOutputCount();
size_t inputCount = sessionPtr->getInputCount();
size_t outputCount = sessionPtr->getOutputCount();
LOG_INFO(kTag, QString("模型有 %1 个输入, %2 个输出")
.arg(inputCount).arg(outputCount));
@ -79,15 +78,13 @@ struct STTEngine::Impl {
outputNames.clear();
for (size_t i = 0; i < inputCount; i++) {
auto namePtr = sessionPtr->GetInputNameAllocated(i, allocator);
inputNames.emplace_back(namePtr.get());
LOG_DEBUG(kTag, QString("输入 #%1: %2").arg(i).arg(namePtr.get()));
inputNames.emplace_back(sessionPtr->getInputName(i));
LOG_DEBUG(kTag, QString("输入 #%1: %2").arg(i).arg(QString::fromStdString(inputNames.back())));
}
for (size_t i = 0; i < outputCount; i++) {
auto namePtr = sessionPtr->GetOutputNameAllocated(i, allocator);
outputNames.emplace_back(namePtr.get());
LOG_DEBUG(kTag, QString("输出 #%1: %2").arg(i).arg(namePtr.get()));
outputNames.emplace_back(sessionPtr->getOutputName(i));
LOG_DEBUG(kTag, QString("输出 #%1: %2").arg(i).arg(QString::fromStdString(outputNames.back())));
}
env = std::move(envPtr);
@ -106,7 +103,7 @@ struct STTEngine::Impl {
LOG_INFO(kTag, QString("模型加载成功: %1").arg(modelPath));
return true;
} catch (const Ort::Exception& e) {
} catch (const ort::Exception& e) {
errorMsg = QString("ONNX 异常: %1").arg(e.what());
LOG_ERROR(kTag, errorMsg);
return false;
@ -117,6 +114,20 @@ struct STTEngine::Impl {
}
}
QMutex mutex;
#else
// 占位实现：无 ONNX Runtime 时仅提供基本结构
bool loadInWorker(const QString& /*modelPath*/,
const QString& /*device*/,
int /*numThreads*/,
QString& errorMsg)
{
errorMsg = "ONNX Runtime 未安装，推理功能不可用。"
"请在 third_party/onnxruntime/ 中部署 ONNX Runtime 后重新编译。";
LOG_ERROR(kTag, errorMsg);
return false;
}
QMutex mutex;
#endif
};
@ -276,9 +287,10 @@ RecognitionResult STTEngine::infer(const std::vector<float>& samples,
QMutexLocker locker(&impl_->mutex);
int64_t melShape[] = {1, kMelBins, static_cast<int64_t>(nFrames)};
auto memInfo = Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeCPU);
std::vector<Ort::Value> inputTensors;
inputTensors.push_back(Ort::Value::CreateTensor<float>(
auto memInfo = ort::MemoryInfo::createCpu(OrtDeviceAllocator, OrtMemTypeCPU);
std::vector<ort::Value> inputTensors;
inputTensors.push_back(ort::Value::createTensor(
memInfo, melSpec.data(), melSpec.size(), melShape, 3));
std::vector<const char*> inputNamePtrs;
@ -286,8 +298,10 @@ RecognitionResult STTEngine::infer(const std::vector<float>& samples,
std::vector<const char*> outputNamePtrs;
for (auto& name : impl_->outputNames) outputNamePtrs.push_back(name.c_str());
auto outputTensors = impl_->session->Run(
Ort::RunOptions{nullptr},
ort::RunOptions runOptions;
auto outputTensors = ort::run(
*impl_->session,
runOptions,
inputNamePtrs.data(), inputTensors.data(), inputTensors.size(),
outputNamePtrs.data(), impl_->outputNames.size());
@ -295,8 +309,8 @@ RecognitionResult STTEngine::infer(const std::vector<float>& samples,
// 4. 解析输出
auto& outputTensor = outputTensors[0];
auto shape = outputTensor.GetTensorTypeAndShapeInfo().GetShape();
const float* outputData = outputTensor.GetTensorMutableData<float>();
auto shape = outputTensor.getShape();
const float* outputData = outputTensor.getTensorData();
LOG_DEBUG(kTag, QString("输出维度: %1").arg(shape.size()));
for (size_t i = 0; i < shape.size(); i++) {

33
src/core/win_hotkey.cpp
View File

@ -5,6 +5,8 @@
#include <windows.h>
#include <QAbstractNativeEventFilter>
#include <QGuiApplication>
#include <QThread>
#include <QWidget>
#endif
static const char* const kTag = "CapsLockVoiceHotkey";
@ -20,6 +22,7 @@ struct CapsLockVoiceHotkey::Impl {
bool longPressFired = false;
bool pollThreadRunning = false;
void* nativeEventFilter = nullptr;
QWidget* hiddenWindow = nullptr;
static constexpr int kLongPressMs = 1000;
#endif
};
@ -63,14 +66,19 @@ bool CapsLockVoiceHotkey::start() {
if (active_) return true;
#ifdef Q_OS_WIN
HWND hwnd = reinterpret_cast<HWND>(QGuiApplication::instance()->winId());
if (!hwnd) {
// Try to get the top-level widget's window handle
hwnd = GetForegroundWindow();
// 创建隐藏窗口用于接收 WM_HOTKEY 消息
if (!impl_->hiddenWindow) {
impl_->hiddenWindow = new QWidget();
impl_->hiddenWindow->setObjectName("HotkeyReceiver");
impl_->hiddenWindow->setWindowFlags(Qt::Tool | Qt::FramelessWindowHint);
impl_->hiddenWindow->resize(0, 0);
}
// 确保窗口已创建（show 会创建原生句柄）
impl_->hiddenWindow->show();
HWND hwnd = reinterpret_cast<HWND>(impl_->hiddenWindow->winId());
if (!hwnd) {
emit error("无法获取窗口句柄");
emit error("无法创建窗口句柄");
return false;
}
@ -146,11 +154,14 @@ void CapsLockVoiceHotkey::stop() {
}
// 注销快捷键
HWND hwnd = reinterpret_cast<HWND>(QGuiApplication::instance()->winId());
if (hwnd && impl_->hotkeyId) {
UnregisterHotKey(hwnd, impl_->hotkeyId);
GlobalDeleteAtom(impl_->hotkeyId);
impl_->hotkeyId = 0;
if (impl_->hiddenWindow) {
HWND hwnd = reinterpret_cast<HWND>(impl_->hiddenWindow->winId());
if (hwnd && impl_->hotkeyId) {
UnregisterHotKey(hwnd, impl_->hotkeyId);
GlobalDeleteAtom(impl_->hotkeyId);
impl_->hotkeyId = 0;
}
impl_->hiddenWindow->hide();
}
active_ = false;
@ -208,7 +219,7 @@ void CapsLockVoiceHotkey::onHotkeyEvent(int /*hotkeyId*/) {
QThread::msleep(50);
}
impl_->pollThreadRunning = false;
}).start();
})->start();
}
#endif

1
src/core/win_hotkey.h
View File

@ -49,6 +49,7 @@ signals:
void error(const QString& message);
/** @brief 处理 WM_HOTKEY 事件（由原生事件过滤器调用） */
public:
void onHotkeyEvent(int hotkeyId);
private:

51
src/ui/settings_page.cpp
View File

@ -17,6 +17,7 @@
#include <QLabel>
#include <QFileDialog>
#include <QMessageBox>
#include <QScrollArea>
static const char* const kTag = "SettingsPage";
@ -34,10 +35,24 @@ SettingsPage::~SettingsPage() = default;
void SettingsPage::setupUI() {
auto* mainLayout = new QVBoxLayout(this);
mainLayout->setContentsMargins(0, 0, 0, 0);
// ---- 可滚动内容区域 ----
auto* scrollArea = new QScrollArea(this);
scrollArea->setWidgetResizable(true);
scrollArea->setHorizontalScrollBarPolicy(Qt::ScrollBarAlwaysOff);
scrollArea->setFrameShape(QFrame::NoFrame);
auto* contentWidget = new QWidget(scrollArea);
auto* contentLayout = new QVBoxLayout(contentWidget);
contentLayout->setContentsMargins(12, 8, 12, 8);
contentLayout->setSpacing(12);
// STT 设置
auto* sttGroup = new QGroupBox("STT 推理设置", this);
auto* sttGroup = new QGroupBox("STT 推理设置", contentWidget);
auto* sttLayout = new QFormLayout(sttGroup);
sttLayout->setSpacing(8);
sttLayout->setContentsMargins(10, 12, 10, 12);
auto* modelRow = new QHBoxLayout();
modelPathEdit_ = new QLineEdit(this);
@ -109,11 +124,13 @@ void SettingsPage::setupUI() {
temperatureSpin_->setValue(0.0);
sttLayout->addRow("温度 (Temperature):", temperatureSpin_);
mainLayout->addWidget(sttGroup);
contentLayout->addWidget(sttGroup);
// 音频设置
auto* audioGroup = new QGroupBox("音频设置", this);
auto* audioGroup = new QGroupBox("音频设置", contentWidget);
auto* audioLayout = new QFormLayout(audioGroup);
audioLayout->setSpacing(8);
audioLayout->setContentsMargins(10, 12, 10, 12);
// 音频输入设备选择器
audioDeviceCombo_ = new QComboBox(this);
@ -150,11 +167,13 @@ void SettingsPage::setupUI() {
paddingSpin_->setSuffix(" ms");
audioLayout->addRow("块间重叠:", paddingSpin_);
mainLayout->addWidget(audioGroup);
contentLayout->addWidget(audioGroup);
// UI 设置
auto* uiGroup = new QGroupBox("界面设置", this);
auto* uiGroup = new QGroupBox("界面设置", contentWidget);
auto* uiLayout = new QFormLayout(uiGroup);
uiLayout->setSpacing(8);
uiLayout->setContentsMargins(10, 12, 10, 12);
themeCombo_ = new QComboBox(this);
themeCombo_->addItems({"light", "dark"});
@ -173,26 +192,32 @@ void SettingsPage::setupUI() {
showConfidenceCheck_->setChecked(true);
uiLayout->addRow("置信度显示:", showConfidenceCheck_);
mainLayout->addWidget(uiGroup);
contentLayout->addWidget(uiGroup);
contentLayout->addStretch();
// 操作按钮
auto* btnLayout = new QHBoxLayout();
auto* saveBtn = new QPushButton("保存配置", this);
scrollArea->setWidget(contentWidget);
mainLayout->addWidget(scrollArea);
// ---- 底部操作按钮（固定不滚动） ----
auto* btnBar = new QWidget(this);
auto* btnLayout = new QHBoxLayout(btnBar);
btnLayout->setContentsMargins(12, 4, 12, 8);
auto* saveBtn = new QPushButton("保存配置", btnBar);
saveBtn->setStyleSheet("QPushButton { font-weight: bold; padding: 8px 16px; }");
connect(saveBtn, &QPushButton::clicked, this, &SettingsPage::onSaveConfig);
btnLayout->addWidget(saveBtn);
auto* resetBtn = new QPushButton("恢复默认", this);
auto* resetBtn = new QPushButton("恢复默认", btnBar);
connect(resetBtn, &QPushButton::clicked, this, &SettingsPage::onResetConfig);
btnLayout->addWidget(resetBtn);
btnLayout->addStretch();
statusLabel_ = new QLabel("配置未修改", this);
statusLabel_ = new QLabel("配置未修改", btnBar);
statusLabel_->setStyleSheet("color: gray;");
btnLayout->addWidget(statusLabel_);
mainLayout->addLayout(btnLayout);
mainLayout->addStretch();
mainLayout->addWidget(btnBar);
}
void SettingsPage::loadFromConfig() {