34 lines
1.2 KiB
C++
34 lines
1.2 KiB
C++
// sherpa-onnx/python/csrc/vad-model.cc
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//
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// Copyright (c) 2023 Xiaomi Corporation
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#include "sherpa-onnx/python/csrc/vad-model.h"
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#include <vector>
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#include "sherpa-onnx/csrc/vad-model.h"
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namespace sherpa_onnx {
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void PybindVadModel(py::module *m) {
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using PyClass = VadModel;
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py::class_<PyClass>(*m, "VadModel")
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.def_static("create", &PyClass::Create, py::arg("config"),
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py::call_guard<py::gil_scoped_release>())
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.def("reset", &PyClass::Reset, py::call_guard<py::gil_scoped_release>())
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.def(
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"is_speech",
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[](PyClass &self, const std::vector<float> &samples) -> bool {
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return self.IsSpeech(samples.data(), samples.size());
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},
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py::arg("samples"), py::call_guard<py::gil_scoped_release>())
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.def("window_size", &PyClass::WindowSize,
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py::call_guard<py::gil_scoped_release>())
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.def("min_silence_duration_samples", &PyClass::MinSilenceDurationSamples,
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py::call_guard<py::gil_scoped_release>())
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.def("min_speech_duration_samples", &PyClass::MinSpeechDurationSamples,
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py::call_guard<py::gil_scoped_release>());
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}
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} // namespace sherpa_onnx
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