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use std::path::Path;
use deepspeech::Model;
pub struct DeepSpeechModel {
pub model: Model,
}
impl DeepSpeechModel {
pub fn instantiate_from(model_dir_str: String) -> Self {
let dir_path = Path::new(&model_dir_str);
let mut graph_name: Box<Path> = dir_path.join("output_graph.pb").into_boxed_path();
let mut scorer_name: Option<Box<Path>> = None;
for file in dir_path.read_dir().into_iter().flatten() {
let file_path = file.unwrap().path();
if file_path.is_file() {
if let Some(ext) = file_path.extension() {
if ext == "pb" || ext == "pbmm" || ext == "tflite" {
graph_name = file_path.into_boxed_path();
} else if ext == "scorer" {
scorer_name = Some(file_path.into_boxed_path());
}
}
}
}
let mut model = Model::load_from_files(&graph_name).unwrap();
if let Some(scorer) = scorer_name {
model.enable_external_scorer(&scorer).unwrap();
}
DeepSpeechModel { model }
}
pub fn model(&mut self) -> &mut Model {
&mut self.model
}
}