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 = 'auto'

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:
        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

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()