FunASR/runtime/onnxruntime/bin/funasr-onnx-online-asr.cpp

177 lines
6.0 KiB
C++

/**
* Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
* MIT License (https://opensource.org/licenses/MIT)
*/
#ifndef _WIN32
#include <sys/time.h>
#else
#include <win_func.h>
#endif
#include <iostream>
#include <fstream>
#include <sstream>
#include <map>
#include <vector>
#include <glog/logging.h>
#include "funasrruntime.h"
#include "tclap/CmdLine.h"
#include "com-define.h"
#include "audio.h"
using namespace std;
bool is_target_file(const std::string& filename, const std::string target) {
std::size_t pos = filename.find_last_of(".");
if (pos == std::string::npos) {
return false;
}
std::string extension = filename.substr(pos + 1);
return (extension == target);
}
void GetValue(TCLAP::ValueArg<std::string>& value_arg, string key, std::map<std::string, std::string>& model_path)
{
if (value_arg.isSet()){
model_path.insert({key, value_arg.getValue()});
LOG(INFO)<< key << " : " << value_arg.getValue();
}
}
int main(int argc, char *argv[])
{
google::InitGoogleLogging(argv[0]);
FLAGS_logtostderr = true;
TCLAP::CmdLine cmd("funasr-onnx-offline-vad", ' ', "1.0");
TCLAP::ValueArg<std::string> model_dir("", MODEL_DIR, "the asr online model path, which contains model.onnx, decoder.onnx, config.yaml, am.mvn", true, "", "string");
TCLAP::ValueArg<std::string> quantize("", QUANTIZE, "true (Default), load the model of model.onnx in model_dir. If set true, load the model of model_quant.onnx in model_dir", false, "true", "string");
TCLAP::ValueArg<std::string> wav_path("", WAV_PATH, "the input could be: wav_path, e.g.: asr_example.wav; pcm_path, e.g.: asr_example.pcm; wav.scp, kaldi style wav list (wav_id \t wav_path)", true, "", "string");
TCLAP::ValueArg<std::int32_t> audio_fs("", AUDIO_FS, "the sample rate of audio", false, 16000, "int32_t");
cmd.add(model_dir);
cmd.add(quantize);
cmd.add(wav_path);
cmd.add(audio_fs);
cmd.parse(argc, argv);
std::map<std::string, std::string> model_path;
GetValue(model_dir, MODEL_DIR, model_path);
GetValue(quantize, QUANTIZE, model_path);
GetValue(wav_path, WAV_PATH, model_path);
struct timeval start, end;
gettimeofday(&start, nullptr);
int thread_num = 1;
FUNASR_HANDLE asr_handle=FunASRInit(model_path, thread_num, ASR_ONLINE);
if (!asr_handle)
{
LOG(ERROR) << "FunVad init failed";
exit(-1);
}
gettimeofday(&end, nullptr);
long seconds = (end.tv_sec - start.tv_sec);
long modle_init_micros = ((seconds * 1000000) + end.tv_usec) - (start.tv_usec);
LOG(INFO) << "Model initialization takes " << (double)modle_init_micros / 1000000 << " s";
// read wav_path
vector<string> wav_list;
vector<string> wav_ids;
string default_id = "wav_default_id";
string wav_path_ = model_path.at(WAV_PATH);
if(is_target_file(wav_path_, "scp")){
ifstream in(wav_path_);
if (!in.is_open()) {
LOG(ERROR) << "Failed to open file: " << model_path.at(WAV_SCP) ;
return 0;
}
string line;
while(getline(in, line))
{
istringstream iss(line);
string column1, column2;
iss >> column1 >> column2;
wav_list.emplace_back(column2);
wav_ids.emplace_back(column1);
}
in.close();
}else{
wav_list.emplace_back(wav_path_);
wav_ids.emplace_back(default_id);
}
// init online features
FUNASR_HANDLE online_handle=FunASROnlineInit(asr_handle);
float snippet_time = 0.0f;
long taking_micros = 0;
for (int i = 0; i < wav_list.size(); i++) {
auto& wav_file = wav_list[i];
auto& wav_id = wav_ids[i];
int32_t sampling_rate_ = audio_fs.getValue();
funasr::Audio audio(1);
if(is_target_file(wav_file.c_str(), "wav")){
if(!audio.LoadWav2Char(wav_file.c_str(), &sampling_rate_)){
LOG(ERROR)<<"Failed to load "<< wav_file;
exit(-1);
}
}else if(is_target_file(wav_file.c_str(), "pcm")){
if (!audio.LoadPcmwav2Char(wav_file.c_str(), &sampling_rate_)){
LOG(ERROR)<<"Failed to load "<< wav_file;
exit(-1);
}
}else{
if (!audio.FfmpegLoad(wav_file.c_str(), true)){
LOG(ERROR)<<"Failed to load "<< wav_file;
exit(-1);
}
}
char* speech_buff = audio.GetSpeechChar();
int buff_len = audio.GetSpeechLen()*2;
int step = 9600*2;
bool is_final = false;
string final_res="";
for (int sample_offset = 0; sample_offset < buff_len; sample_offset += std::min(step, buff_len - sample_offset)) {
if (sample_offset + step >= buff_len - 1) {
step = buff_len - sample_offset;
is_final = true;
} else {
is_final = false;
}
gettimeofday(&start, nullptr);
FUNASR_RESULT result = FunASRInferBuffer(online_handle, speech_buff+sample_offset, step, RASR_NONE, nullptr, is_final, sampling_rate_);
gettimeofday(&end, nullptr);
seconds = (end.tv_sec - start.tv_sec);
taking_micros += ((seconds * 1000000) + end.tv_usec) - (start.tv_usec);
if (result)
{
string msg = FunASRGetResult(result, 0);
final_res += msg;
LOG(INFO)<< wav_id <<" : "<<msg;
snippet_time += FunASRGetRetSnippetTime(result);
FunASRFreeResult(result);
}
else
{
LOG(ERROR) << ("No return data!\n");
}
}
LOG(INFO)<<"Final results " << wav_id <<" : "<<final_res;
}
LOG(INFO) << "Audio length: " << (double)snippet_time << " s";
LOG(INFO) << "Model inference takes: " << (double)taking_micros / 1000000 <<" s";
LOG(INFO) << "Model inference RTF: " << (double)taking_micros/ (snippet_time*1000000);
FunASRUninit(asr_handle);
FunASRUninit(online_handle);
return 0;
}