Update app.py

app.py

@@ -4,7 +4,7 @@ import numpy as np
 import os
 
 # Load the model (ensure it's in the same directory as app.py)
-model_path = os.path.join(os.path.dirname(__file__), 'waste_classifier_model.keras')
+model_path = os.path.join(os.path.dirname(__file__), 'waste_classifier_mobilenetv2.h5')
 model = load_model(model_path)
 
 # Prediction function
@@ -14,14 +14,14 @@ def classify_image(image):
     
     image = np.array(image)
 
-    if image.shape != (128, 128, 3):
-        image = np.resize(image, (128, 128, 3))
+    if image.shape != (224, 224, 3):
+        image = np.resize(image, (224, 224, 3))
 
     image = image / 255.0
     image = np.expand_dims(image, axis=0)
 
     prediction = model.predict(image)
-    class_label = 'Organic' if prediction[0][0] > 0.5 else 'Recycleable'
+    class_label = 'Reyclabble' if prediction[0][0] > 0.5 else 'Organic'
     return class_label
 
 # Create Gradio interface