app.py

import gradio as gr
import torch
import cv2
import numpy as np

from basicsr.archs.srvgg_arch import SRVGGNetCompact
from realesrgan import RealESRGANer

# Modell-Konfiguration für realesr-general-x4v3.pth
model_path = 'realesr-general-x4v3.pth'
model = SRVGGNetCompact(
    num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu'
)

upsampler = RealESRGANer(
    scale=4,
    model_path=model_path,
    model=model,
    tile=0,
    tile_pad=10,
    pre_pad=0,
    half=True if torch.cuda.is_available() else False
)

def upscale(image):
    try:
        image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
        output, _ = upsampler.enhance(image, outscale=4)
        output = cv2.cvtColor(output, cv2.COLOR_BGR2RGB)
        return output
    except Exception as e:
        return f"Fehler beim Upscaling: {e}"

demo = gr.Interface(
    fn=upscale,
    inputs=gr.Image(type="numpy"),
    outputs=gr.Image(type="numpy"),
    title="Real-ESRGAN Upscaler (x4)",
    description="Lade ein Bild hoch, das mit Real-ESRGAN hochskaliert werden soll."
)

demo.launch()