sample

from flask import Flask, render_template, request, flash


app = Flask(__name__)
app.secret_key = "thomas"

@app.route('/')
def home():
    return render_template('home.html')
    


@app.route('/login', methods=['POST','GET'])
def login():
    return render_template('login.html')
    check()

def check():
    database = {'admin':'admin'}
    uname=request.form['uname']
    passw=request.form['pass']
    if uname not in database :
        
        return render_template('login.html',info='WRONG USERNAME OR PASSWORD')
    else:
        if database[uname] != passw:
            
            return render_template('login.html',info='WRONG USERNAME OR PASSWORD')
        else:
            return render_template('prediction.html',info='WELCOME TO MUSIC CLASSIFIER')

    

@app.route('/prediction', methods=['POST','GET'])
def phome():
    return render_template('prediction.html',info='WELCOME TO MUSIC CLASSIFIER')

def prediction():
    aud = request.files['aud']
    aud_path = "./images" + aud.filename
    aud.save(aud_path)
    return render_template('prediction.html',info='FILE IS UPLOADED')


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









from flask import Flask, render_template, request, flash
from cv2 import cv2
from librosa import librosa
from librosa import display
from numpy import numpy as np
from matplotlib import pyplot as plt
from tensorflow.keras.models import load_model
from sklearn.preprocessing import MinMaxScaler

app = Flask(__name__)
app.secret_key = "thomas"

model = load_model('imageclass.h5')  # Replace with the actual path to your model
class_labels = ['Blue', 'Classical', 'Country', 'Disco', 'Hiphop', 'Jazz', 'Metal', 'Pop', 'Reggae', 'Rock']

@app.route('/')
def home():
    return render_template('home.html')

@app.route('/login', methods=['POST', 'GET'])
def login():
    return render_template('login.html')

@app.route('/check_login', methods=['POST'])
def check_login():
    database = {'admin': 'admin'}
    uname = request.form['uname']
    passw = request.form['pass']

    if uname not in database or database[uname] != passw:
        return render_template('login.html', info='WRONG USERNAME OR PASSWORD')

    return render_template('prediction.html', info='WELCOME TO MUSIC CLASSIFIER')

@app.route('/prediction', methods=['POST', 'GET'])
def phome():
    return render_template('prediction.html', info='WELCOME TO MUSIC CLASSIFIER')

@app.route('/predict_music', methods=['POST'])
def predict_music():
    aud = request.files['aud']
    aud_path = "./images/" + aud.filename
    aud.save(aud_path)

    # Load the external audio file
    y, sr = librosa.load(aud_path)

    # ... (rest of your model prediction code)

    # Make predictions using the loaded model
    predictions = model.predict(np.expand_dims(spectrogram_resized, axis=0))

    # Get the predicted label
    predicted_label = class_labels[np.argmax(predictions)]

    return render_template('prediction.html', info=f'Predicted Label: {predicted_label}')

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