Update app.py

app.py

@@ -178,24 +178,6 @@ def run_inference(target, source, slider, adv_slider, settings):
         return None
 
 
-description = "Performs subject agnostic identity transfer from a source face to all target faces. \n\n" \
-              "Implementation and demo of FaceDancer, accepted to WACV 2023. \n\n" \
-              "Pre-print: https://arxiv.org/abs/2210.10473 \n\n" \
-              "Code: https://github.com/felixrosberg/FaceDancer \n\n" \
-               "\n\n" \
-              "Options:\n\n" \
-              "-Compare returns the target image concatenated with the results.\n\n" \
-              "-Anonymize will ignore the source image and perform an identity permutation of target faces.\n\n" \
-              "-Reconstruction attack will attempt to invert the face swap or the anonymization.\n\n" \
-              "-Adversarial defense will add a permutation noise that disrupts the reconstruction attack.\n\n" \
-              "NOTE: There is no guarantees with the anonymization process currently.\n\n" \
-              "NOTE: source image with too high resolution may not work properly!"
-examples = [["assets/rick.jpg", "assets/musk.jpg", 100, 10, ["compare"]],
-            ["assets/musk.jpg", "assets/musk.jpg", 100, 10, ["anonymize"]]]
-article = """
-Demo is based of recent research from my Ph.D work. Results expects to be published in the coming months.
-"""
-
 iface = gradio.Interface(run_inference,
                          [gradio.Image(shape=None, type="pil", label='Target'),
                           gradio.Image(shape=None, type="pil", label='Source'),
@@ -208,8 +190,5 @@ iface = gradio.Interface(run_inference,
                                                       label='Options')],
                          "image",
                          title="Face Swap",
-                         description=description,
-                         examples=examples,
-                         article=article,
                          layout="vertical")
 iface.launch()