Use tf load_img

app.py

@@ -1,6 +1,6 @@
 import gradio as gr
 from huggingface_hub import from_pretrained_keras
-from tensorflow.keras.preprocessing.image import array_to_img, img_to_array
+import tensorflow as tf
 
 from labels import CLASS_LABELS
 
@@ -8,11 +8,11 @@ from labels import CLASS_LABELS
 model = from_pretrained_keras("jsolow/grubguesser")
 
 
-def _preprocess(imgage_input):
-    img = array_to_img(imgage_input, scale=False)
-    img = img.resize((224, 224))
-    img = img_to_array(img)
-    return img / 255.0
+def _preprocess(image_path: str):
+    image = tf.keras.utils.load_img(image_path, target_size=(224, 224))
+    input_arr = tf.keras.utils.img_to_array(image)
+    input_arr = np.array([input_arr])  # Convert single image to a batch.
+    return input_arr
 
 
 def predict(image):