Create app.py

app.py

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+import gradio as gr
+import torch
+import spaces
+from PIL import Image
+from torchvision import transforms
+from transformers import AutoModelForImageSegmentation
+
+device = 'cuda' if torch.cuda.is_available() else 'cpu'
+model = AutoModelForImageSegmentation.from_pretrained(
+    'joelseytre/toonout', trust_remote_code=True
+).eval().to(device)
+
+@spaces.GPU
+def remove_background(image, resolution="1024x1024"):
+    if image is None:
+        return None
+    
+    res = int(resolution.split('x')[0])
+    if image.mode != 'RGB':
+        image = image.convert('RGB')
+    
+    original_size = image.size
+    transform = transforms.Compose([
+        transforms.Resize((res, res)),
+        transforms.ToTensor(),
+        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
+    ])
+    
+    input_tensor = transform(image).unsqueeze(0).to(device)
+    
+    with torch.no_grad():
+        preds = model(input_tensor)[-1].sigmoid().cpu()
+    
+    pred = preds[0].squeeze()
+    mask = transforms.ToPILImage()(pred).resize(original_size)
+    
+    output = image.copy()
+    output.putalpha(mask)
+    return output
+
+demo = gr.Interface(
+    fn=remove_background,
+    inputs=[
+        gr.Image(type="pil", label="Upload Image"),
+        gr.Dropdown(["512x512", "1024x1024", "2048x2048"], value="1024x1024", label="Resolution")
+    ],
+    outputs=gr.Image(type="pil", label="Result"),
+    title="ToonOut - Anime Background Removal",
+    description="99.5% accuracy on anime/cartoon images. MIT License - free for commercial use."
+)
+
+demo.launch()