Update app.py

app.py

@@ -18,7 +18,7 @@ category_index = label_map_util.create_category_index_from_labelmap(PATH_TO_LABE
 def pil_image_as_numpy_array(pilimg):
 
     img_array = tf.keras.utils.img_to_array(pilimg)
-    img_array = np.expand_dims(img_array, axis=0)
+    # img_array = np.expand_dims(img_array, axis=0)
     return img_array
     
 def load_image_into_numpy_array(path):
@@ -37,6 +37,7 @@ def load_model():
 def predict(image_np):
     
     image_np = pil_image_as_numpy_array(image_np)
+    image_np = np.expand_dims(image_np, axis=0)
     
     results = detection_model(image_np)
 
@@ -69,7 +70,7 @@ def predict2(pilimg):
 detection_model = load_model()
 
 # Specify paths to example images
-example_image_paths = ["test_1.jpg", "test_1.jpg"]
+example_image_paths = ["test_1.jpg"]
 
 # Create a list of example inputs and outputs using a for loop
 example_inputs = [Image.open(path) for path in example_image_paths]