Update app.py

app.py

@@ -49,27 +49,12 @@ with gr.Blocks() as demo:
         <h2 style="text-align: center;">DreamTalk: When Expressive Talking Head Generation Meets Diffusion Probabilistic Models</h2>
         <p style="text-align: center;">
             DreamTalk is a diffusion-based audio-driven expressive talking head generation framework that can produce high-quality talking head videos across diverse speaking styles. DreamTalk exhibits robust performance with a diverse array of inputs, including songs, speech in multiple languages, noisy audio, and out-of-domain portraits.
-            <img src="https://github.com/ali-vilab/dreamtalk/raw/main/media/teaser.gif" />
+            <img src="https://github.com/ali-vilab/dreamtalk/raw/main/media/teaser.gif" style="margin: 0 auto" width="40%" />
         </p>
         """)
         with gr.Row():
             with gr.Column():
                 image_path = gr.Image(label="Image", type="filepath", sources=["upload"])
-                gr.Examples(
-                    examples = [
-                        "data/src_img/uncropped/face3.png",
-                        "data/src_img/uncropped/male_face.png",
-                        "data/src_img/uncropped/uncut_src_img.jpg",
-                        "data/src_img/cropped/chpa5.png",
-                        "data/src_img/cropped/cut_img.png",
-                        "data/src_img/cropped/f30.png",
-                        "data/src_img/cropped/menglu2.png",
-                        "data/src_img/cropped/nscu2.png",
-                        "data/src_img/cropped/zp1.png",
-                        "data/src_img/cropped/zt12.png"
-                    ],
-                    inputs=[image_path]
-                )
                 audio_input = gr.Audio(label="Audio input", type="filepath", sources=["upload"], value="data/audio/acknowledgement_english.m4a")
                 with gr.Row():
                     audio_list = gr.Dropdown(
@@ -122,6 +107,21 @@ with gr.Blocks() as demo:
                         ],
                         value = "M030_front_neutral_level1_001.mat"
                     )
+                gr.Examples(
+                    examples = [
+                        "data/src_img/uncropped/face3.png",
+                        "data/src_img/uncropped/male_face.png",
+                        "data/src_img/uncropped/uncut_src_img.jpg",
+                        "data/src_img/cropped/chpa5.png",
+                        "data/src_img/cropped/cut_img.png",
+                        "data/src_img/cropped/f30.png",
+                        "data/src_img/cropped/menglu2.png",
+                        "data/src_img/cropped/nscu2.png",
+                        "data/src_img/cropped/zp1.png",
+                        "data/src_img/cropped/zt12.png"
+                    ],
+                    inputs=[image_path]
+                )
                 run_btn = gr.Button("Run")
             with gr.Column():
                 output_video = gr.Video(format="mp4")