can work on gradio

Video-P2P/run.py

@@ -978,7 +978,7 @@ def main(
         inversion.append( Image.fromarray((sequence1[i] * 255).numpy().astype(np.uint8)) )
         videop2p.append( Image.fromarray((sequence2[i] * 255).numpy().astype(np.uint8)) )
 
-    inversion[0].save(save_name_1, save_all=True, append_images=inversion[1:], optimize=False, loop=0, duration=250)
+    # inversion[0].save(save_name_1, save_all=True, append_images=inversion[1:], optimize=False, loop=0, duration=250)
     videop2p[0].save(save_name_2, save_all=True, append_images=videop2p[1:], optimize=False, loop=0, duration=250)
 
 

app_training.py

@@ -85,23 +85,23 @@ def create_training_demo(trainer: Trainer,
                 validation_prompt = gr.Text(
                     label='Validation Prompt',
                     placeholder=
-                    'prompt to test the model, e.g: a Iron-man is surfing')
+                    'prompt to test the model, e.g: a Lego man is surfing')
                 blend_word_1 = gr.Text(
-                    label='blend_word(input)',
+                    label='blend_word(source)',
                     placeholder=
                     'man')
                 blend_word_2 = gr.Text(
-                    label='blend_word(output)',
+                    label='blend_word(target)',
                     placeholder=
-                    'Iron-Man')
+                    'man')
                 eq_params_1 = gr.Text(
                     label='reweight_word',
                     placeholder=
-                    'Iron-Man')
+                    'Lego')
                 eq_params_2 = gr.Text(
                     label='reweight_value',
                     placeholder=
-                    '4')
+                    '8')
             with gr.Column():
                 gr.Markdown('Upload Settings')
                 with gr.Row():

trainer.py

@@ -151,7 +151,7 @@ class Trainer:
                         base_model=base_model,
                         training_prompt=training_prompt,
                         test_prompt=validation_prompt,
-                        test_image_dir='samples')
+                        test_image_dir='results')
 
         message = 'Training completed!'
         print(message)