redo changes, use older TF version

app.py

@@ -28,12 +28,12 @@ def check_forgery_df(img):
     pred2= model_M2.predict(x, verbose=0)   
 
 
-    # Ensure pred1 and pred2 are numpy arrays before proceeding
-    if isinstance(pred1, dict):
-        print("pred1 is dict!")
-        pred1 = pred1[next(iter(pred1))]
-    if isinstance(pred2, dict):
-        pred2 = pred2[next(iter(pred2))]
+#    # Ensure pred1 and pred2 are numpy arrays before proceeding
+#    if isinstance(pred1, dict):
+#        print("pred1 is dict!")
+#        pred1 = pred1[next(iter(pred1))]
+#    if isinstance(pred2, dict):
+#        pred2 = pred2[next(iter(pred2))]
 
     
     pred = np.max([pred1,pred2], axis=0)   
@@ -61,21 +61,21 @@ if uploaded_file is not None:
     model_path1 = "IMVIP_Supplementary_Material/models/model1/"
     model_path2 = "IMVIP_Supplementary_Material/models/model2/"
     
-    tfsm_layer1 = tf.keras.layers.TFSMLayer(model_path1, call_endpoint='serving_default')
-    tfsm_layer2 = tf.keras.layers.TFSMLayer(model_path2, call_endpoint='serving_default')
+    #tfsm_layer1 = tf.keras.layers.TFSMLayer(model_path1, call_endpoint='serving_default')
+    #tfsm_layer2 = tf.keras.layers.TFSMLayer(model_path2, call_endpoint='serving_default')
+    #
+    #input_shape = (256, 256, 3)
+    #inputs = Input(shape=input_shape)
+
+    ##create the model
+    #outputs1 = tfsm_layer1(inputs)
+    #model_M1 = Model(inputs, outputs1)
+
+    #outputs2 = tfsm_layer2(inputs)
+    #model_M2 = Model(inputs, outputs2)
     
-    input_shape = (256, 256, 3)
-    inputs = Input(shape=input_shape)
-
-    #create the model
-    outputs1 = tfsm_layer1(inputs)
-    model_M1 = Model(inputs, outputs1)
-
-    outputs2 = tfsm_layer2(inputs)
-    model_M2 = Model(inputs, outputs2)
-    
-    #model_M1 = tf.keras.layers.TFSMLayer("IMVIP_Supplementary_Material/models/model1/") #tf.keras.models.load_model("IMVIP_Supplementary_Material/models/model1/")
-    #model_M2 = tf.keras.models.load_model("IMVIP_Supplementary_Material/models/model2/")
+    model_M1 = tf.keras.models.load_model("IMVIP_Supplementary_Material/models/model1/") #tf.keras.models.load_model("IMVIP_Supplementary_Material/models/model1/")
+    model_M2 = tf.keras.models.load_model("IMVIP_Supplementary_Material/models/model2/")
 
     # Convert the file to an opencv image.
     file_bytes = np.asarray(bytearray(uploaded_file.read()), dtype=np.uint8)