app.py

app.py

@@ -0,0 +1,43 @@
+import gradio as gr
+import torch
+import os
+import requests
+from basicsr.archs.rrdbnet_arch import RRDBNet
+from realesrgan import RealESRGANer
+from PIL import Image
+import numpy as np
+
+# Ensure model weights exist
+MODEL_URL = 'https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth'
+MODEL_PATH = 'weights/RealESRGAN_x4plus.pth'
+
+os.makedirs('weights', exist_ok=True)
+if not os.path.exists(MODEL_PATH):
+    print('Downloading model...')
+    response = requests.get(MODEL_URL, stream=True)
+    with open(MODEL_PATH, 'wb') as f:
+        for chunk in response.iter_content(chunk_size=8192):
+            f.write(chunk)
+
+# Load Real-ESRGAN model
+device = 'cuda' if torch.cuda.is_available() else 'cpu'
+model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4)
+upscaler = RealESRGANer(scale=4, model_path=MODEL_PATH, model=model, tile=400, tile_pad=10, pre_pad=0, half=True)
+
+# Image upscale function
+def upscale_image(image):
+    img = np.array(image)
+    output, _ = upscaler.enhance(img, outscale=4)
+    return image, Image.fromarray(output)
+
+# Gradio UI
+iface = gr.Interface(
+    fn=upscale_image,
+    inputs=gr.Image(type='pil'),
+    outputs=[gr.Image(type='pil', label='Original Image'), gr.Image(type='pil', label='Upscaled Image')],
+    title='Image Upscaler',
+    description='Upload an image to see the before and after upscaling using Real-ESRGAN.'
+)
+
+if __name__ == '__main__':
+    iface.launch()