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import gradio as gr
from animesr.inference_animesr_video import main
from utils import url_download
MODEL_LIST = [
"kadirnar/AnimeSR_Paper_Model",
"kadirnar/AnimeSR_v2"
]
examples = [
["https://www.youtube.com/watch?v=KJeD4ErwO04", "kadirnar/AnimeSR_v2"]
#["https://www.youtube.com/watch?v=icPHcK_cCF4", "kadirnar/AnimeSR_v2"]
]
def AnimeSr_Video(
source: str,
model_id: str,
):
if source.startswith('http'):
source = url_download(source)
else:
source = source
main(source=source, model_id=model_id)
save_path = 'output.mp4'
return source, save_path
app = gr.Blocks()
with app:
gr.Markdown("# **<p align='center'>AnimeSR: Learning Real-World Super-Resolution Models for Animation Videos</p>**")
gr.Markdown(
"""
<p style='text-align: center'>
Follow me for more!
<br> <a href='https://twitter.com/kadirnar_ai' target='_blank'>twitter</a> | <a href='https://github.com/kadirnar' target='_blank'>github</a> | <a href='https://www.linkedin.com/in/kadir-nar/' target='_blank'>linkedin</a> |
</p>
"""
)
with gr.Row():
with gr.Column():
with gr.Tab("URL"):
input_text = gr.inputs.Textbox(lines=1, label="Video URL")
input_text_button = gr.Button(value="Predict")
with gr.Tab("Local"):
gr.Markdown("### **Video**")
input_video = gr.inputs.Video(label="Video")
input_video_button = gr.Button(value="Predict")
input_dropdown =gr.inputs.Dropdown(choices=MODEL_LIST)
with gr.Column():
output = gr.outputs.Video(label="Input Video")
with gr.Column():
video_gif = gr.outputs.Video(label="Output Video")
gr.Examples(examples, inputs=[input_text, input_dropdown], outputs=[output, video_gif], fn=AnimeSr_Video, cache_examples=False)
input_text_button.click(AnimeSr_Video, inputs=[input_text, input_dropdown], outputs=[output, video_gif])
input_video_button.click(AnimeSr_Video, inputs=[input_video, input_dropdown], outputs=[output, video_gif])
app.launch()
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