changes to try and fix the classification error

app.py

@@ -4,12 +4,12 @@
 import gradio as gr
 import numpy as np
 import os
-from tensorflow.keras.models import load_model
+import tensorflow as tf
 
 ### -------------------------------- ###
 ###           model loading          ###
 ### -------------------------------- ###
-model = load_model('model.h5') # single file model from colab
+model = tf.keras.models.load_model('model.h5')
 
 ## --------------------------------- ###
 ###     reading: categories.txt      ###
@@ -73,17 +73,20 @@ The space was inspired by @Isabel's wonderful [cat or pug](https://huggingface.c
 samples = ['defective.jpeg', 'okay.jpeg']
 
 def preprocess(image):
-  image = np.array(image) / 255
-  image = np.expand_dims(image, axis=0)
-  return image
+    img_grayscale = image[:,:,1]
+    img_array = tf.keras.utils.img_to_array(img_grayscale)
+    img_array = tf.expand_dims(img_array, 0)
+    # image = np.array(image) / 255
+    # image = np.expand_dims(image, axis=0)
+    return img_array
   
 def predict_image(image):
-  pred = model.predict(preprocess(image))
-  results = {}
-  for row in pred:
-    for idx, item in enumerate(row):
-      results[labels[idx]] = float(item)
-  return results
+    pred = model.predict(preprocess(image))
+    results = {}
+    for row in pred:
+        for idx, item in enumerate(row):
+            results[labels[idx]] = float(item)
+    return results
 
 # generate img input and text label output
 image = gr.inputs.Image(shape=(300, 300), label="Upload Your Image Here")

model_test.h5

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:21c73dae526f60eedb1ee9645e0575917b3c86345324ca9018d8128c442e3ce0
-size 221962152