Update app.py

app.py

@@ -4,10 +4,21 @@ import numpy as np
 from torchvision import models
 from scipy.ndimage import zoom
 import gradio as gr
+import pickle
+
 
 # Assuming you already have the 'ann_model' trained and 'pca' instance from the previous code
 language_mapping = {'malayalam': 0, 'english': 1, 'tamil': 2,'hindi':3,'kannada':4,'telugu':5}
 
+
+# Load the trained model
+with open('ann_model.pth', 'rb') as f:
+    ann_model = torch.load(f)
+
+# Load the PCA instance
+with open('pca.pkl', 'rb') as f:
+    pca = pickle.load(f)
+vgg16 = models.vgg16(pretrained=True).features
 # Function to load and preprocess a single audio file
 def preprocess_single_audio_vgg16(audio_file, vgg16_model, pca_instance):
     # Your existing preprocessing code goes here
@@ -44,7 +55,7 @@ def preprocess_single_audio_vgg16(audio_file, vgg16_model, pca_instance):
 
 def predict_language(audio_file_path):
     # Load VGG16 model
-    vgg16 = models.vgg16(pretrained=True).features
+    
 
     # Preprocess the single audio file using VGG16 for feature extraction
     preprocessed_features = preprocess_single_audio_vgg16(audio_file_path, vgg16, pca)