Apply fixes to preprocess for scaling and single batch pred index

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 from huggingface_hub import from_pretrained_keras
 import tensorflow as tf
+import numpy as np
 
 from labels import CLASS_LABELS
 
@@ -12,15 +13,14 @@ 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
+    return input_arr / 255.
 
 
 def predict(image):
     image_array = _preprocess(image)
-    predictions = model.predict(image_array)
+    predictions = model.predict(image_array)[0]  # single pred batch
     return {k:v for k, v in zip(CLASS_LABELS, predictions)}
 
-
 gr.Interface(
     predict,
     inputs=gr.inputs.Image(label="Upload food image", type="filepath"),