* examples : refactor common code into a library * examples : refactor common SDL code into a library * make : update Makefile to use common libs * common : fix MSVC M_PI .. * addon.node : link common lib
343 lines
12 KiB
C++
343 lines
12 KiB
C++
#include "napi.h"
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#include "common.h"
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#include "whisper.h"
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#include <string>
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#include <thread>
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#include <vector>
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#include <cmath>
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#include <cstdint>
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struct whisper_params {
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int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
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int32_t n_processors = 1;
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int32_t offset_t_ms = 0;
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int32_t offset_n = 0;
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int32_t duration_ms = 0;
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int32_t max_context = -1;
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int32_t max_len = 0;
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int32_t best_of = 5;
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int32_t beam_size = -1;
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float word_thold = 0.01f;
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float entropy_thold = 2.4f;
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float logprob_thold = -1.0f;
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bool speed_up = false;
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bool translate = false;
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bool diarize = false;
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bool output_txt = false;
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bool output_vtt = false;
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bool output_srt = false;
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bool output_wts = false;
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bool output_csv = false;
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bool print_special = false;
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bool print_colors = false;
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bool print_progress = false;
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bool no_timestamps = false;
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std::string language = "en";
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std::string prompt;
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std::string model = "../../ggml-large.bin";
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std::vector<std::string> fname_inp = {};
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std::vector<std::string> fname_out = {};
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};
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struct whisper_print_user_data {
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const whisper_params * params;
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const std::vector<std::vector<float>> * pcmf32s;
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};
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// 500 -> 00:05.000
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// 6000 -> 01:00.000
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std::string to_timestamp(int64_t t, bool comma = false) {
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int64_t msec = t * 10;
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int64_t hr = msec / (1000 * 60 * 60);
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msec = msec - hr * (1000 * 60 * 60);
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int64_t min = msec / (1000 * 60);
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msec = msec - min * (1000 * 60);
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int64_t sec = msec / 1000;
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msec = msec - sec * 1000;
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char buf[32];
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snprintf(buf, sizeof(buf), "%02d:%02d:%02d%s%03d", (int) hr, (int) min, (int) sec, comma ? "," : ".", (int) msec);
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return std::string(buf);
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}
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int timestamp_to_sample(int64_t t, int n_samples) {
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return std::max(0, std::min((int) n_samples - 1, (int) ((t*WHISPER_SAMPLE_RATE)/100)));
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}
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void whisper_print_segment_callback(struct whisper_context * ctx, int n_new, void * user_data) {
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const auto & params = *((whisper_print_user_data *) user_data)->params;
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const auto & pcmf32s = *((whisper_print_user_data *) user_data)->pcmf32s;
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const int n_segments = whisper_full_n_segments(ctx);
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std::string speaker = "";
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int64_t t0;
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int64_t t1;
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// print the last n_new segments
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const int s0 = n_segments - n_new;
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if (s0 == 0) {
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printf("\n");
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}
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for (int i = s0; i < n_segments; i++) {
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if (!params.no_timestamps || params.diarize) {
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t0 = whisper_full_get_segment_t0(ctx, i);
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t1 = whisper_full_get_segment_t1(ctx, i);
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}
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if (!params.no_timestamps) {
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printf("[%s --> %s] ", to_timestamp(t0).c_str(), to_timestamp(t1).c_str());
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}
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if (params.diarize && pcmf32s.size() == 2) {
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const int64_t n_samples = pcmf32s[0].size();
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const int64_t is0 = timestamp_to_sample(t0, n_samples);
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const int64_t is1 = timestamp_to_sample(t1, n_samples);
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double energy0 = 0.0f;
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double energy1 = 0.0f;
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for (int64_t j = is0; j < is1; j++) {
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energy0 += fabs(pcmf32s[0][j]);
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energy1 += fabs(pcmf32s[1][j]);
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}
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if (energy0 > 1.1*energy1) {
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speaker = "(speaker 0)";
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} else if (energy1 > 1.1*energy0) {
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speaker = "(speaker 1)";
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} else {
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speaker = "(speaker ?)";
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}
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//printf("is0 = %lld, is1 = %lld, energy0 = %f, energy1 = %f, %s\n", is0, is1, energy0, energy1, speaker.c_str());
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}
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// colorful print bug
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//
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const char * text = whisper_full_get_segment_text(ctx, i);
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printf("%s%s", speaker.c_str(), text);
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// with timestamps or speakers: each segment on new line
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if (!params.no_timestamps || params.diarize) {
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printf("\n");
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}
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fflush(stdout);
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}
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}
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int run(whisper_params ¶ms, std::vector<std::vector<std::string>> &result) {
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if (params.fname_inp.empty()) {
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fprintf(stderr, "error: no input files specified\n");
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return 2;
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}
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if (params.language != "auto" && whisper_lang_id(params.language.c_str()) == -1) {
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fprintf(stderr, "error: unknown language '%s'\n", params.language.c_str());
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exit(0);
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}
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// whisper init
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struct whisper_context * ctx = whisper_init_from_file(params.model.c_str());
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if (ctx == nullptr) {
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fprintf(stderr, "error: failed to initialize whisper context\n");
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return 3;
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}
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// initial prompt
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std::vector<whisper_token> prompt_tokens;
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if (!params.prompt.empty()) {
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prompt_tokens.resize(1024);
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prompt_tokens.resize(whisper_tokenize(ctx, params.prompt.c_str(), prompt_tokens.data(), prompt_tokens.size()));
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fprintf(stderr, "\n");
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fprintf(stderr, "initial prompt: '%s'\n", params.prompt.c_str());
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fprintf(stderr, "initial tokens: [ ");
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for (int i = 0; i < (int) prompt_tokens.size(); ++i) {
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fprintf(stderr, "%d ", prompt_tokens[i]);
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}
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fprintf(stderr, "]\n");
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}
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for (int f = 0; f < (int) params.fname_inp.size(); ++f) {
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const auto fname_inp = params.fname_inp[f];
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const auto fname_out = f < (int)params.fname_out.size() && !params.fname_out[f].empty() ? params.fname_out[f] : params.fname_inp[f];
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std::vector<float> pcmf32; // mono-channel F32 PCM
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std::vector<std::vector<float>> pcmf32s; // stereo-channel F32 PCM
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if (!::read_wav(fname_inp, pcmf32, pcmf32s, params.diarize)) {
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fprintf(stderr, "error: failed to read WAV file '%s'\n", fname_inp.c_str());
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continue;
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}
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// print system information
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{
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fprintf(stderr, "\n");
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fprintf(stderr, "system_info: n_threads = %d / %d | %s\n",
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params.n_threads*params.n_processors, std::thread::hardware_concurrency(), whisper_print_system_info());
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}
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// print some info about the processing
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{
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fprintf(stderr, "\n");
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if (!whisper_is_multilingual(ctx)) {
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if (params.language != "en" || params.translate) {
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params.language = "en";
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params.translate = false;
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fprintf(stderr, "%s: WARNING: model is not multilingual, ignoring language and translation options\n", __func__);
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}
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}
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fprintf(stderr, "%s: processing '%s' (%d samples, %.1f sec), %d threads, %d processors, lang = %s, task = %s, timestamps = %d ...\n",
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__func__, fname_inp.c_str(), int(pcmf32.size()), float(pcmf32.size())/WHISPER_SAMPLE_RATE,
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params.n_threads, params.n_processors,
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params.language.c_str(),
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params.translate ? "translate" : "transcribe",
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params.no_timestamps ? 0 : 1);
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fprintf(stderr, "\n");
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}
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// run the inference
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{
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whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
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wparams.strategy = params.beam_size > 1 ? WHISPER_SAMPLING_BEAM_SEARCH : WHISPER_SAMPLING_GREEDY;
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wparams.print_realtime = false;
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wparams.print_progress = params.print_progress;
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wparams.print_timestamps = !params.no_timestamps;
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wparams.print_special = params.print_special;
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wparams.translate = params.translate;
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wparams.language = params.language.c_str();
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wparams.n_threads = params.n_threads;
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wparams.n_max_text_ctx = params.max_context >= 0 ? params.max_context : wparams.n_max_text_ctx;
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wparams.offset_ms = params.offset_t_ms;
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wparams.duration_ms = params.duration_ms;
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wparams.token_timestamps = params.output_wts || params.max_len > 0;
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wparams.thold_pt = params.word_thold;
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wparams.entropy_thold = params.entropy_thold;
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wparams.logprob_thold = params.logprob_thold;
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wparams.max_len = params.output_wts && params.max_len == 0 ? 60 : params.max_len;
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wparams.speed_up = params.speed_up;
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wparams.greedy.best_of = params.best_of;
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wparams.beam_search.beam_size = params.beam_size;
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wparams.prompt_tokens = prompt_tokens.empty() ? nullptr : prompt_tokens.data();
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wparams.prompt_n_tokens = prompt_tokens.empty() ? 0 : prompt_tokens.size();
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whisper_print_user_data user_data = { ¶ms, &pcmf32s };
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// this callback is called on each new segment
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if (!wparams.print_realtime) {
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wparams.new_segment_callback = whisper_print_segment_callback;
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wparams.new_segment_callback_user_data = &user_data;
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}
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// example for abort mechanism
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// in this example, we do not abort the processing, but we could if the flag is set to true
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// the callback is called before every encoder run - if it returns false, the processing is aborted
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{
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static bool is_aborted = false; // NOTE: this should be atomic to avoid data race
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wparams.encoder_begin_callback = [](struct whisper_context * /*ctx*/, void * user_data) {
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bool is_aborted = *(bool*)user_data;
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return !is_aborted;
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};
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wparams.encoder_begin_callback_user_data = &is_aborted;
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}
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if (whisper_full_parallel(ctx, wparams, pcmf32.data(), pcmf32.size(), params.n_processors) != 0) {
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fprintf(stderr, "failed to process audio\n");
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return 10;
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}
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}
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}
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const int n_segments = whisper_full_n_segments(ctx);
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result.resize(n_segments);
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for (int i = 0; i < n_segments; ++i) {
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const char * text = whisper_full_get_segment_text(ctx, i);
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const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
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const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
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result[i].emplace_back(to_timestamp(t0, true));
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result[i].emplace_back(to_timestamp(t1, true));
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result[i].emplace_back(text);
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}
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whisper_print_timings(ctx);
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whisper_free(ctx);
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return 0;
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}
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Napi::Object whisper(const Napi::CallbackInfo& info) {
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Napi::Env env = info.Env();
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if (info.Length() <= 0 || !info[0].IsObject()) {
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Napi::TypeError::New(env, "object expected").ThrowAsJavaScriptException();
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}
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whisper_params params;
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std::vector<std::vector<std::string>> result;
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Napi::Object whisper_params = info[0].As<Napi::Object>();
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std::string language = whisper_params.Get("language").As<Napi::String>();
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std::string model = whisper_params.Get("model").As<Napi::String>();
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std::string input = whisper_params.Get("fname_inp").As<Napi::String>();
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params.language = language;
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params.model = model;
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params.fname_inp.emplace_back(input);
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// run model
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run(params, result);
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fprintf(stderr, "RESULT:\n");
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for (auto sentence:result) {
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fprintf(stderr, "t0: %s, t1: %s, content: %s \n",
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sentence[0].c_str(), sentence[1].c_str(), sentence[2].c_str());
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}
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Napi::Object res = Napi::Array::New(env, result.size());
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for (uint64_t i = 0; i < result.size(); ++i) {
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Napi::Object tmp = Napi::Array::New(env, 3);
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for (uint64_t j = 0; j < 3; ++j) {
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tmp[j] = Napi::String::New(env, result[i][j]);
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}
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res[i] = tmp;
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}
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return res;
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}
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Napi::Object Init(Napi::Env env, Napi::Object exports) {
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exports.Set(
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Napi::String::New(env, "whisper"),
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Napi::Function::New(env, whisper)
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);
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return exports;
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}
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NODE_API_MODULE(whisper, Init);
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