Update app.py

app.py

@@ -178,6 +178,24 @@ 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'),
@@ -190,5 +208,8 @@ iface = gradio.Interface(run_inference,
                                                       label='Options')],
                          "image",
                          title="Face Swap",
+                         description=description,
+                         examples=examples,
+                         article=article,
                          layout="vertical")
-iface.launch()
+iface.launch()