Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+from PIL import Image, ImageFilter
+import numpy as np
+
+# Load the segmentation pipeline
+pipe = pipeline("image-segmentation", model="mattmdjaga/segformer_b2_clothes")
+
+# Simplified refine_mask function
+def refine_mask(mask):
+    """Simplify and smooth the segmentation mask."""
+    mask_array = np.array(mask)
+    mask_array = (mask_array > 128).astype(np.uint8) * 255  # Threshold to binary mask
+    refined_mask = Image.fromarray(mask_array).filter(ImageFilter.GaussianBlur(0.5))  # Smooth edges
+    return refined_mask
+
+# Function to blur the background
+def blur_background(image, blur_radius):
+    # Perform segmentation
+    result = pipe(image)
+    
+    # Extract the background mask
+    background_mask = None
+    for entry in result:
+        if entry["label"] == "Background":
+            background_mask = refine_mask(entry["mask"])  # Refine the background mask
+            break
+    
+    if background_mask is None:
+        return image  # If no background is detected, return the original image
+    
+    # Convert the image and mask to NumPy arrays
+    image_np = np.array(image)
+    background_mask_np = np.array(background_mask)
+    
+    # Create a blurred version of the entire image
+    blurred_image = image.filter(ImageFilter.GaussianBlur(radius=blur_radius))
+    blurred_np = np.array(blurred_image)
+    
+    # Combine the original image and the blurred background
+    final_image = np.where(background_mask_np[..., None] == 255, blurred_np, image_np).astype(np.uint8)
+    
+    # Convert back to PIL image
+    return Image.fromarray(final_image)
+
+# Example inputs for Gradio
+examples = [["1.jpg"", 10] ,["2.jpg"", 10]  ,["3.jpg"", 10] ] # Example: Image with a blur intensity of 10
+
+# Gradio interface
+interface = gr.Interface(
+    fn=blur_background,
+    inputs=[
+        gr.Image(type="pil"),  # Input image
+        gr.Slider(1, 50, step=1, label="Blur Intensity")  # Slider for blur radius
+    ],
+    outputs=gr.Image(type="pil"),  # Output image with blurred background
+    examples=examples,  # Provide examples as a nested list
+    title="Blur Background with Refined Mask",
+    description="Upload an image and adjust the slider to control the background blur level. The background edges are smoothed for better blending."
+)
+
+# Launch the app
+interface.launch()