Update app.py

app.py

@@ -1,6 +1,8 @@
-import gradio as gr
-#import gradio.helpers
+import torch._dynamo
+torch._dynamo.config.suppress_errors = True
+
 import torch
+import gradio as gr
 import os
 import base64
 from glob import glob
@@ -23,7 +25,7 @@ pipe = StableVideoDiffusionPipeline.from_pretrained(
     variant="fp16"
 )
 
-pipe.save_pretrained("./model", variant="fp16")
+# pipe.save_pretrained("./model", variant="fp16")
 
 pipe.to("cuda")
 pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
@@ -105,8 +107,19 @@ def resize_image(image, output_size=(1024, 576)):
     cropped_image = resized_image.crop((left, top, right, bottom))
     return cropped_image
 
-with gr.Blocks() as demo:
-    image = gr.Image(label="Upload your image", type="pil", height=500)
+
+css = """
+#img-display-input {
+    max-height: 60vh;
+    object-fit: contain;
+}
+#vid-display-output *{
+    max-height: 60vh;
+}
+"""
+
+with gr.Blocks(css=css) as demo:
+    image = gr.Image(label="Upload your image", type="pil", elem_id="img-display-output")
     generate_btn = gr.Button("Generate")
     base64_out = gr.Textbox(label="Base64 Video")
     seed = gr.Slider(label="Seed", value=42, randomize=False, minimum=0, maximum=max_64_bit_int, step=1)