Create app.py

app.py

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+import gradio as gr
+import torch
+import numpy as np
+from torchvision import transforms
+from PIL import Image
+from torchvision.models.segmentation import deeplabv3_resnet101
+
+# Load Pretrained Model
+model = deeplabv3_resnet101(pretrained=True)
+model.eval()
+
+def remove_background(image):
+    # Preprocess image
+    transform = transforms.Compose([
+        transforms.ToTensor(),
+        transforms.Resize((512, 512)),
+    ])
+    
+    input_tensor = transform(image).unsqueeze(0)
+
+    # Perform inference
+    with torch.no_grad():
+        output = model(input_tensor)["out"][0]
+
+    # Create mask (Class 15 = Person)
+    mask = output.argmax(0).numpy()
+    mask = np.where(mask == 15, 255, 0).astype(np.uint8)
+
+    # Apply mask
+    image = np.array(image)
+    transparent_image = np.dstack((image, mask))
+
+    return Image.fromarray(transparent_image)
+
+# Create Gradio Interface
+iface = gr.Interface(
+    fn=remove_background,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Image(type="pil"),
+    title="AI Background Remover",
+    description="Upload an image and remove its background using AI."
+)
+
+iface.launch()