from math import log2, pow
import os

import numpy as np
from scipy.fftpack import fft
import basic_pitch
import basic_pitch.inference
from basic_pitch import ICASSP_2022_MODEL_PATH
from tempfile import NamedTemporaryFile

import gradio as gr

def transcribe(audio_path):
    # model_output, midi_data, note_events = predict("generated_0.wav")
    model_output, midi_data, note_events = basic_pitch.inference.predict(
        audio_path=audio_path,
        model_or_model_path=ICASSP_2022_MODEL_PATH,
        )

    with NamedTemporaryFile("wb", suffix=".mid", delete=False) as file:
        try:
            midi_data.write(file)
            print(f"midi file saved to {file.name}")
        except Exception as e:
            print(f"Error while writing midi file: {e}")
            raise e

    return gr.DownloadButton(
        value=file.name,
        label=f"Download MIDI file {file.name}",
        visible=True)


with gr.Blocks() as demo:
    transcribe_button = gr.Button("Transcribe")
    audio = gr.Audio("audio", type="filepath")

    d = gr.DownloadButton("Download the file", visible=False)
    transcribe_button.click(transcribe, inputs=[audio], outputs=d)
if __name__ == "__main__":
    demo.launch()