Update app.py

app.py

@@ -25,9 +25,9 @@ zip_ref = zipfile.ZipFile(local_zip, 'r')
 zip_ref.extractall('deepfakes-test-images')
 zip_ref.close()
 
-with tf.device('/cpu:0'):
-    model_b0 = tf.keras.models.load_model("FINAL-EFFICIENTNETV2-B0")
-    model_s = tf.keras.models.load_model("FINAL-EFFICIENTNETV2-S")
+
+model_b0 = tf.keras.models.load_model("FINAL-EFFICIENTNETV2-B0")
+model_s = tf.keras.models.load_model("FINAL-EFFICIENTNETV2-S")
 
 detector = MTCNN()
 
@@ -73,20 +73,19 @@ 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 = [
-            [
+
                 ['deepfakes-test-images/Fake-1.jpg'],
                 ['deepfakes-test-images/Fake-2.jpg'],
                 ['deepfakes-test-images/Fake-3.jpg'],
                 ['deepfakes-test-images/Fake-4.jpg'],
-                ['deepfakes-test-images/Fake-5.jpg']
-            ],
-            [
+                ['deepfakes-test-images/Fake-5.jpg'],
+  
                 ['deepfakes-test-images/Real-1.jpg'],
                 ['deepfakes-test-images/Real-2.jpg'],
                 ['deepfakes-test-images/Real-3.jpg'],
                 ['deepfakes-test-images/Real-4.jpg'],
-                ['deepfakes-test-images/Real-5.jpg'],
-            ]
+                ['deepfakes-test-images/Real-5.jpg']
+
            ]
             
 gr.Interface(deepfakespredict,