Update app.py

app.py

@@ -7,7 +7,25 @@ with CustomObjectScope({'RandomHeight': RandomHeight}):
     model_0 = tf.keras.models.load_model('bestmodel.h5')
 
 def classify_image(inp):
-    inp = inp.reshape((-1, 224, 224, 3))
+    # Convert to PIL Image if we have a numpy array
+    if isinstance(image_array, np.ndarray):
+        image = Image.fromarray(image_array)
+    else:
+        image = image_array
+    
+    # Resize image to 224x224
+    image = image.resize((224, 224), Image.Resampling.LANCZOS)
+    
+    # Convert to numpy array and ensure correct shape
+    image_array = np.array(image)
+    
+    # Handle grayscale images
+    if len(image_array.shape) == 2:
+        image_array = np.stack([image_array] * 3, axis=-1)
+    
+    # Add batch dimension and ensure correct shape
+    inp = image_array.reshape((-1, 224, 224, 3))
+    # inp = inp.reshape((-1, 224, 224, 3))
     prediction = model_0.predict(inp)
     output  = ""
     if prediction[0][prediction.argmax()] < 0.84: