Update app.py

app.py

@@ -5,20 +5,8 @@ from diffusers.utils import load_image
 import spaces
 from panna.pipeline import PipelineSVDUpscale
 
-
 model = PipelineSVDUpscale(upscaler="instruct_ir")
-example_files = []
-root_url = "https://huggingface.co/spaces/multimodalart/stable-video-diffusion/resolve/main/images"
-examples = ["disaster_meme.png", "distracted_meme.png", "hide_meme.png", "success_meme.png", "willy_meme.png", "wink_meme.png"]
-for example in examples:
- load_image(f"{root_url}/{example}").save(example)
-tmp_output_dir = "outputs"
-os.makedirs(tmp_output_dir, exist_ok=True)
-title = ("# [Stable Video Diffusion](ttps://huggingface.co/stabilityai/stable-video-diffusion-img2vid-xt) with [InstructIR as Upscaler](https://huggingface.co/spaces/marcosv/InstructIR)\n"
- "The demo is part of [panna](https://github.com/asahi417/panna) project.")
-
 
-@spaces.GPU(duration=120)
 def infer(init_image, upscaler_prompt, num_frames, motion_bucket_id, noise_aug_strength, decode_chunk_size, fps, seed):
  base_count = len(glob(os.path.join(tmp_output_dir, "*.mp4")))
  video_path = os.path.join(tmp_output_dir, f"{base_count:06d}.mp4")
@@ -35,7 +23,6 @@ def infer(init_image, upscaler_prompt, num_frames, motion_bucket_id, noise_aug_s
  )
  return video_path
 
-
 with gr.Blocks() as demo:
  gr.Markdown(title)
  with gr.Row():
@@ -56,5 +43,5 @@ with gr.Blocks() as demo:
  inputs=[image, upscaler_prompt, num_frames, motion_bucket_id, noise_aug_strength, decode_chunk_size, fps, seed],
  outputs=[video]
  )
- gr.Examples(examples=examples, inputs=image)
-demo.launch(server_name="0.0.0.0")
+ gr.Examples(inputs=image)
+demo.launch()