Reverting back to mobilenetv3 model

app.py

@@ -9,12 +9,12 @@ IMG_HEIGHT = 64
 IMG_WIDTH = 64
 
 # Load the saved Keras model
-model = load_model("cnn_1.keras")
+model = load_model("model_01.keras")
 
 # Define the labels for ASL classes
 labels = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J',
          'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T',
-          'U', 'V', 'W', 'X', 'Y', 'Z', 'del', 'nothing', 'space']  
+          'U', 'V', 'W', 'X', 'Y']  
 
 def preprocess_frame(frame):
     """Preprocess the video frame for the ASL model."""
@@ -52,7 +52,7 @@ def preprocess_frame_cnn(frame):
 
 def predict_asl(frame):
     """Predict the ASL sign and return the label and probabilities."""
-    processed_frame = preprocess_frame_cnn(frame)
+    processed_frame = preprocess_frame(frame)
     predictions = model.predict(processed_frame)  # Predict probabilities
     predicted_label = labels[np.argmax(predictions)]  # Get the class with the highest probability