Update app.py

app.py

@@ -50,22 +50,22 @@ set_png_as_page_bg('background.webp')
 #     #CNN_class_index = json.load(open(f"{os.getcwd()}F:\Machine Learning Resources\ZebraHorse\model.json"))
 #     return model, CNN_class_index
 
-# def load_model():
-#     if not os.path.isfile('model.h5'):
-#         subprocess.run(['curl --output model.h5 "https://github.com/KaburaJ/Binary-Image-classification/blob/main/ZebraHorse/CNN%20Application/model.h5"'], shell=True)
+def load_model():
+    if not os.path.isfile('model.h5'):
+        subprocess.run(['curl --output model.h5 "https://github.com/KaburaJ/Binary-Image-classification/blob/main/ZebraHorse/CNN%20Application/model.h5"'], shell=True)
     
-#         tf.keras.models.load_model('model.h5', compile=False)
-#         return model
+        tf.keras.models.load_model('model.h5', compile=False)
+        return model
         
-def load_model():
-    # Load the model architecture
-    with open('model.json', 'r') as f:
-        model_from_json(f.read())
+# def load_model():
+#     # Load the model architecture
+#     with open('model.json', 'r') as f:
+#         model_from_json(f.read())
 
-    # Load the model weights
-    model.load_weights('model.h5')
-    #CNN_class_index = json.load(open(f"{os.getcwd()}F:\Machine Learning Resources\ZebraHorse\model.json"))
-    return model
+#     # Load the model weights
+#     model.load_weights('model.h5')
+#     #CNN_class_index = json.load(open(f"{os.getcwd()}F:\Machine Learning Resources\ZebraHorse\model.json"))
+#     return model
 
 
 def image_transformation(image):
@@ -106,7 +106,7 @@ def main():
         # labels = ohe.fit_transform(label).toarray()
 
         if pred_button:
-            image_prediction(image, model)
+            image_prediction(image)
             outputs = model.predict(image)
             _, y_hat = outputs.max(1)
             predicted_idx = str(y_hat.item())