app.py

from flask import Flask, request, render_template
from flask_cors import CORS, cross_origin
from configs import UNQ_CHARS
from utils import (
    load_model,
    predict_from_wavs,
    load_wav
)
import numpy as np

app = Flask(__name__)
cors = CORS(app)
app.config["CORS_HEADERS"] = "Content-Type"


@app.route("/", methods=["GET", "POST"])
@cross_origin()
def translate_sound():
    if request.method == "POST":
        # Get the sound file from the request
        wavs = request.files["sound_file"]
        # Save the sound file
        wavs.save("sound." + wavs.filename.split(".")[-1])
        w = [load_wav("sound." + wavs.filename.split(".")[-1])]
        # Assuming 'wavs' is the uploaded file
        # data, samplerate = sf.read(wavs.stream)
        # Process the sound file using your AI model
        model = load_model("trained_model.h5")
        sentences, char_indices = predict_from_wavs(model, w, UNQ_CHARS)

        # # Return the translation as a response
        return {"sentences": sentences}
        # return {"sentences": ["Hello World", "How are you"]}
    # Render the webpage with the file upload form
    return render_template("index.html", sentences=sentences)


if __name__ == "__main__":
    app.run(debug=True)