Update app.py

app.py

@@ -4,17 +4,19 @@ import numpy as np
 import tensorflow as tf
 import gradio as gr
 from sklearn.preprocessing import LabelEncoder
+import pandas as pd
 
 # Load the pre-trained model
 model_path = 'sound_to_text_model.h5'
 model = tf.keras.models.load_model(model_path)
 
-# Initialize the encoder (make sure it's fitted to your labels)
-# Note: You need to fit the encoder to your actual labels before saving/loading the model
-# For example, you can use the same encoder you used during training
+# Load the labels from labels.csv
+labels_df = pd.read_csv('labels.csv')  # Make sure this path is correct
+training_labels = labels_df['Label'].tolist()  # Assuming the column name is 'Label'
+
+# Initialize the encoder and fit it to your labels
 encoder = LabelEncoder()
-# Assuming you have a list of labels used during training (e.g., y)
-# encoder.fit(y)  # Uncomment and run this if you haven't already fitted the encoder
+encoder.fit(training_labels)  # Fit the encoder to your labels
 
 # Function to extract features from audio
 def extract_features(file_path):