Update app.py

app.py

@@ -34,7 +34,9 @@ detector = MTCNN()
 
 def deepfakespredict(select_model, input_img ):
 
-    tf.keras.backend.clear_session()
+    model = []
+    labels = ['real', 'fake']
+    pred = [0, 0]
     
     if select_model == "EfficientNetV2-B0":
         model = model_b0
@@ -72,7 +74,7 @@ def deepfakespredict(select_model, input_img ):
 
 title="EfficientNetV2 Deepfakes Image Detector"
 description="This is a demo implementation of EfficientNetV2 Deepfakes Image Detector. To use it, simply upload your image, or click one of the examples to load them."
-examples = [
+examples = [ [],[
                 ['deepfakes-test-images/Fake-1.jpg'],
                 ['deepfakes-test-images/Fake-2.jpg'],
                 ['deepfakes-test-images/Fake-3.jpg'],
@@ -84,6 +86,7 @@ examples = [
                 ['deepfakes-test-images/Real-3.jpg'],
                 ['deepfakes-test-images/Real-4.jpg'],
                 ['deepfakes-test-images/Real-5.jpg']
+                ]
            ]
             
 gr.Interface(deepfakespredict,
@@ -91,4 +94,5 @@ gr.Interface(deepfakespredict,
                      outputs=["text", gr.outputs.Image(type="pil", label="Detected face"), gr.outputs.Label(num_top_classes=None, type="auto", label="Confidence")],
                      title=title,
                      description=description
+                     examples=examples
                      ).launch()