app.py

from sldl.video import VideoSR
from sldl.image import ImageSR

import gradio as gr
import tempfile
import shutil
import torch
import ffmpeg
import time
from PIL import Image

cc = 2
if torch.backends.mps.is_available():
    device = 'mps'
    cc = 5
elif torch.cuda.is_available():
    device = 'cuda'
    cc = 10
else:
    device = 'cpu'

vbsrgan = VideoSR('BSRGAN').to(device)
vresrgan = VideoSR('RealESRGAN').to(device)
ibsrgan = ImageSR('BSRGAN').to(device)
iresrgan = ImageSR('RealESRGAN').to(device)

def upscale_video(input_video, output_video, progress, mname):
    modelname = mname.lower()
    model = vbsrgan
    if modelname == 'bsrgan (default)':
        # do nothing
        pass
    elif modelname == 'real esrgan':
        model = vresrgan
    model(input_video, output_video, progress.tqdm)

def upscale_image(input_image, output_image, mname):
    modelname = mname.lower()
    model = ibsrgan
    if modelname == 'bsrgan (default)':
        # do nothing
        pass
    elif modelname == 'real esrgan':
        model = iresrgan
    shutil.copy(input_image, output_image)
    model(output_image)

# Gradio interface
def video_upscaling_interface(input_text, model_name, progress=gr.Progress()):
    if input_text:
        progress(0, desc="Converting the video...")
        temp_dir = tempfile.mkdtemp()
        input_video_path = f"{temp_dir}/input_video"
        output_video_path = f"{temp_dir}/output_video.mp4"
        ffmpeg.input(input_text).output(input_video_path + '.mp4').run()

        # Upscale the video
        upscale_video(input_video_path + '.mp4', output_video_path, progress, model_name)

        return [output_video_path, output_video_path]
    else:
        return ["no_vid.mp4", "no_vid.mp4"]


def image_upscaling_interface(input_text, model_name):
    if input_text:
        temp_dir = tempfile.mkdtemp()
        input_image_path = f"{temp_dir}/input_image.jpg"
        output_image_path = f"{temp_dir}/output_image.jpg"
        input_text.save(input_image_path)
        upscale_image(input_image_path, output_image_path, model_name)
        return [output_image_path, output_image_path]
    else:
        return ["no_image.jpg", "no_image.jpg"]
    

css = "footer {display: none !important;} .gradio-container {min-height: 0px !important;}"


with gr.Blocks(css=css) as demo:
    gr.Markdown('''
# Upscale
## A CVSYS Project

### NOTICE: This is running on a free Hugging Face Space, so it will be quite slow. Expect it to take _hours_ to upscale 5 minutes. Please be mindful and _DO NOT_ upscale videos longer than 15 seconds! Thank you!

[Check out Upscale on GitHub!](https://github.com/cv-sys/upscale)

## Want Faster Inference?

Duplicate this space for faster inference! We recommend using an A10G or A100. 

<a href="https://huggingface.co/spaces/cvsys/upscale?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14"></a>

Please note that after you upload an image, it may take several minutes before the progress bar appears. This is because we first convert your video to ensure the correct format.
''')
    # with gr.Tab("Image"):
    #     with gr.Row():
    #         with gr.Column():
    #             iinp = gr.Image(label="Upload Image", interactive=True, type="pil")
    #             imod = gr.Dropdown(
    #                 ["BSRGAN (Default)", "Real ESRGAN"],
    #                 value="BSRGAN (Default)",
    #                 interactive=True,
    #                 label="Model"
    #             )
    #         with gr.Column():
    #             iout = gr.Image(label="View Image", interactive=False, type="filepath")
    #             ifile = gr.File(label="Download Image", interactive=False)
    #     ibtn = gr.Button(value="Upscale Image")
    with gr.Tab("Video"):
        with gr.Row():
            with gr.Column():
                vinp = gr.Video(label="Upload Video", interactive=True)
                vmod = gr.Dropdown(
                    ["BSRGAN (Default)", "Real ESRGAN"],
                    value="BSRGAN (Default)",
                    interactive=True,
                    label="Model"
                )
            with gr.Column():
                vout = gr.Video(label="Watch Video", interactive=False)
                vfile = gr.File(label="Download Video", interactive=False)
        vbtn = gr.Button(value="Upscale Video")
    # ibtn.click(image_upscaling_interface, [iinp, imod], outputs=[iout, ifile])
    vbtn.click(video_upscaling_interface, [vinp, vmod], outputs=[vout, vfile])
    demo.queue(concurrency_count=cc)
    demo.launch()