Spaces:
Running
on
Zero
Running
on
Zero
File size: 3,171 Bytes
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import spaces
import os
import gradio as gr
from video_super_resolution.scripts.inference_sr import VEnhancer_sr
examples = [
["prompts/astronaut.mp4", "An astronaut flying in space, featuring a steady and smooth perspective", 4, 24, 250],
["prompts/cat.mp4", "A cat wearing sunglasses at a pool", 4, 24, 250],
["prompts/fish.mp4", "Clown fish swimming through the coral reef", 4, 24, 300],
["prompts/iron_man.mp4", "Iron Man flying in the sky", 4, 24, 250],
["prompts/raccoon.mp4", "A cute raccoon playing guitar in a boat on the ocean", 4, 24, 250],
["prompts/shanghai.mp4", "The bund Shanghai by Hokusai, in the style of Ukiyo", 4, 24, 250],
["prompts/gwen.mp4", "Gwen Stacy reading a book, black and white", 4, 24, 250],
]
# Define a GPU-decorated function for enhancement
@spaces.GPU(duration=1200)
def enhance_with_gpu(input_video, input_text):
return venhancer.enhance_a_video(input_video, input_text)
def venhancer_demo(result_dir="./tmp/"):
css = """#input_video {max-width: 1024px !important} #output_vid {max-width: 2048px; max-height:1280px}"""
global venhancer
venhancer = VEnhancer_sr(result_dir)
with gr.Blocks(analytics_enabled=False, css=css) as venhancer_iface:
gr.Markdown(
"<div align='center'> <h1> VEnhancer </span> </h1> \
<a style='font-size:18px;color: #000000' href='https://arxiv.org/abs/2501.02976'> [ArXiv] </a>\
<a style='font-size:18px;color: #000000' href='https://nju-pcalab.github.io/projects/STAR'> [Project Page] </a> \
<a style='font-size:18px;color: #000000' href='https://github.com/NJU-PCALab/STAR'> [Github] </a> </div>"
)
with gr.Tab(label="VEnhancer"):
with gr.Column():
with gr.Row():
with gr.Column():
with gr.Row():
input_video = gr.Video(label="Input Video", elem_id="input_video")
with gr.Row():
input_text = gr.Text(label="Prompts")
end_btn = gr.Button("Generate")
with gr.Row():
output_video = gr.Video(
label="Generated Video", elem_id="output_vid", autoplay=True, show_share_button=True
)
gr.Examples(
examples=examples,
inputs=[input_video, input_text],
outputs=[output_video],
fn=enhance_with_gpu, # Use the GPU-decorated function
cache_examples=False,
)
end_btn.click(
inputs=[input_video, input_text],
outputs=[output_video],
fn=enhance_with_gpu, # Use the GPU-decorated function
)
return venhancer_iface
if __name__ == "__main__":
result_dir = os.path.join("./", "results")
venhancer_iface = venhancer_demo(result_dir)
venhancer_iface.queue(max_size=12)
venhancer_iface.launch(max_threads=1) |