add error description

.gitignore

@@ -1,2 +1,3 @@
 results/*
-results_all/*
+results_all/*
+*.pt

app.py

@@ -17,6 +17,12 @@ def inference_app(
         seed,
         inference_steps):
     
+    print('inference info:')
+    print('ref video:',embedding_dir)
+    print('prompt:',prompt)
+    print('motion type:',motion_type)
+    print('infer steps:',inference_steps)
+
     return inference_main(
         embedding_dir=embedding_dir,
         prompt=prompt, 
@@ -202,7 +208,6 @@ if __name__ == "__main__":
             </a>
             <br>
             <strong>Please consider starring <span style="color: orange">&#9733;</span> the <a href="https://github.com/EnVision-Research/MotionInversion" target="_blank" rel="noopener noreferrer">GitHub Repo</a> if you find this useful!</strong>
-            </p>
         """
         )
         with gr.Tabs(elem_classes=["tabs"]):
@@ -219,12 +224,27 @@ if __name__ == "__main__":
                     output_video = gr.Video(label="Output Video")
                     generated_prompt = gr.Textbox(label="Generated Prompt")
 
+                    with gr.Accordion('Encounter Errors', open=False):
+                        gr.Markdown('''
+                                    <strong>Generally, inference time for one video often takes 45~50s on ZeroGPU</strong>.
+
+                                    <br>
+                                    <strong>You have exceeded your GPU quota</strong>: A limitation set by HF. Retry in an hour.           
+                                    <br>
+                                    <strong>GPU task aborted</strong>: Possibly caused by ZeroGPU being used by too many people, the inference time excceeds the time limit. You may try again later, or clone the repo and run it locally. 
+                                    <br>
+                                    
+                                    If any other issues occur, please feel free to contact us through the community or by email ([email protected]). We will try our best to help you :)
+
+                                    ''')
+
+
             with gr.Accordion("Advanced Settings", open=False):
                 with gr.Row():
                     inference_steps = gr.Number(label="Inference Steps", value=30)
                     motion_type = gr.Dropdown(label="Motion Type", choices=["camera", "object"], value="object")
 
-            gr.Examples(examples=examples_inference,inputs=[preview_video,text_input,motion_type,checkpoint_dropdown])
+        gr.Examples(examples=examples_inference,inputs=[preview_video,text_input,motion_type,checkpoint_dropdown])
 
         checkpoint_dropdown.change(fn=update_preview_video, inputs=checkpoint_dropdown, outputs=preview_video)
         inference_button.click(inference_model, inputs=[text_input, checkpoint_dropdown,inference_steps,motion_type, seed], outputs=output_video)

attn_ctrl.py

@@ -245,7 +245,7 @@ def register_attention_control(unet, config=None):
                 additional_info['removeMFromV'] = config.strategy.get('removeMFromV', False)
                 additional_info['vSpatial_frameSubtraction'] = config.strategy.get('vSpatial_frameSubtraction', False)
                 net_.forward = temp_attn_forward(net_, additional_info)
-                print('register Motion V embedding at ', block_name)
+                # print('register Motion V embedding at ', block_name)
                 return count + 1
             else:
                 return count

models/unet/motion_embeddings.py

@@ -8,7 +8,7 @@ class MotionEmbedding(nn.Module):
     def __init__(self, embed_dim: int = None, max_seq_length: int = 32, wh: int = 1):
         super().__init__()
         self.embed = nn.Parameter(torch.zeros(wh, max_seq_length, embed_dim))
-        print('register spatial motion embedding with', wh)
+        # print('register spatial motion embedding with', wh)
 
         self.scale = 1.0
         self.trained_length = -1
@@ -216,8 +216,8 @@ def inject_motion_embeddings(model, combinations=None, config=None):
             setattr(parent_module, module_name, new_module)
 
     inject_layers = list(set(inject_layers))
-    for name in inject_layers:
-        print(f"Injecting motion embedding at {name}")
+    # for name in inject_layers:
+        # print(f"Injecting motion embedding at {name}")
 
     parameters_list = []
     for name, para in model.named_parameters():

requirements.txt

@@ -50,4 +50,7 @@ transformers==4.45.2
 triton==3.0.0
 typing_extensions==4.12.2
 urllib3==2.2.3
-zipp==3.20.2
+zipp==3.20.2
+gradio==4.44.0
+gradio-imageslider==0.0.20
+gradio-client==1.3.0