Update app.py

app.py

@@ -2,44 +2,27 @@ import gradio as gr
 from rembg import remove
 from PIL import Image
 import io
-import torch
-import numpy as np
-from RealESRGAN import RealESRGAN
-import cv2
 
-# Initialize RealESRGAN model
-device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
-model = RealESRGAN(device, scale=4)
-model.load_weights('weights/RealESRGAN_x4.pth', download=True)
-
-def background_remover_and_upscale(input_image):
-    # Remove background
-    output_img = remove(np.array(input_image))
-    
-    # Convert back to PIL Image for upscaling
-    output_img_rgb = cv2.cvtColor(output_img, cv2.COLOR_BGR2RGB)
-    output_img_pil = Image.fromarray(output_img_rgb)
-    
-    # Upscale image
-    sr_image = model.predict([output_img])
-    
-    # Return the upscaled image directly
-    return sr_image[0]
+def background_remover(input_image):
+    output_img = remove(input_image)  # Remove the background using the rembg library
+    # No need to convert to BytesIO, just return the PIL Image object
+    return output_img
 
 description = """
-✨ This app uses the rembg library to remove the background from uploaded images and then the RealESRGAN model to upscale the image.
-Simply upload your image and let the models do their work. Download the result immediately after!
+This app uses the rembg library to remove the background from uploaded images.
+Simply upload your image and let the model do its work. Download the result immediately after!
 """
 
 iface = gr.Interface(
-    fn=background_remover_and_upscale,
-    inputs=gr.Image(type='pil'),
+    fn=background_remover,
+    inputs=gr.inputs.Image(type='pil', label="Upload Image"),
     outputs="image",
     examples=["woman.jpg", "groot.jpg"],
-    title="Background Remover and Image Upscaler",
+    title="✨ Background Remover",
     description=description,
-    article="""This demo was created by KVI Kontent using Gradio.""",
     theme="soft"
 )
 
-iface.launch()
+
+# Launch the interface
+iface.launch(share=True)