wekws/runtime/core/bin/kws_main.cc
Binbin Zhang 53d7b8f807
[runtime/onnxruntime] add onnxruntime support (#79)
* [runtime/onnxruntime] add onnxruntime support

* add cpplint and clang-format

* fix lint
2022-08-28 13:35:21 +08:00

65 lines
2.1 KiB
C++

// Copyright (c) 2022 Binbin Zhang (binbzha@qq.com)
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include <iostream>
#include <string>
#include "frontend/feature_pipeline.h"
#include "frontend/wav.h"
#include "kws/keyword_spotting.h"
#include "utils/log.h"
int main(int argc, char* argv[]) {
if (argc != 5) {
LOG(FATAL) << "Usage: kws_main fbank_dim(int) batch_size(int) "
<< "kws_model_path test_wav_path";
}
const int num_bins = std::stoi(argv[1]); // Fbank feature dim
const int batch_size = std::stoi(argv[2]);
const std::string model_path = argv[3];
const std::string wav_path = argv[4];
wenet::WavReader wav_reader(wav_path);
int num_samples = wav_reader.num_samples();
wenet::FeaturePipelineConfig feature_config(num_bins, 16000);
wenet::FeaturePipeline feature_pipeline(feature_config);
std::vector<float> wav(wav_reader.data(), wav_reader.data() + num_samples);
feature_pipeline.AcceptWaveform(wav);
feature_pipeline.set_input_finished();
wekws::KeywordSpotting spotter(model_path);
// Simulate streaming, detect batch by batch
int offset = 0;
while (true) {
std::vector<std::vector<float>> feats;
bool ok = feature_pipeline.Read(batch_size, &feats);
std::vector<std::vector<float>> prob;
spotter.Forward(feats, &prob);
for (int i = 0; i < prob.size(); i++) {
std::cout << "frame " << offset + i << " prob";
for (int j = 0; j < prob[i].size(); j++) {
std::cout << " " << prob[i][0];
}
std::cout << std::endl;
}
// Reach the end of feature pipeline
if (!ok) break;
offset += prob.size();
}
return 0;
}