openai_translator.py

from whisper import load_model, _MODELS
from os.path import splitext
from os.path import exists
from os import getcwd
import urllib.request


class translator:
    def __init__(self,transcribe_queue,model):
        self.status_queue=transcribe_queue
        self.status_queue.put({"percent":0.0,"state":"Getting Model"})
        path="https://openaipublic.azureedge.net/main/whisper/models/ed3a0b6b1c0edf879ad9b11b1af5a0e6ab5db9205f891f668f8b0e6c6326e34e/base.pt"
        if not exists(model+".pt"):
            urllib.request.urlretrieve(_MODELS[model], model+".pt")
        self.model = load_model(model,download_root=getcwd())
        self.status_queue.put({"percent":25,"state":"Model Found"})
    def audioToText(self,fileName):
        print("starting translation")
        self.status_queue.put({"percent":33,"state":"Starting Translation"})
        result = self.model.transcribe(fileName)
        name, extension = splitext(fileName)
        self.status_queue.put({"percent":95,"state":"Translation Complete"})
        with open(name+".txt", "w+") as text_file:
            text_file.write(result["text"])
        self.status_queue.put({"percent":100,"state":"done"})