Update app.py

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 import tensorflow as tf
 import tensorflow_hub as hub
 import numpy as np
-from PIL import Image, ImageEnhance, ImageFilter
+from PIL import Image
 from rembg import remove
 
 # Load the neural style transfer model from TensorFlow Hub
@@ -46,30 +46,6 @@ def apply_style_transfer(content_image, style_image, intensity=1.0):
 
     return tensor_to_image(stylized_image)
 
-# Function to enhance the image to make it glistening
-def enhance_image(image):
-    # Convert to Image for processing
-    if isinstance(image, np.ndarray):
-        image = Image.fromarray(image)
-
-    # Enhance color
-    enhancer = ImageEnhance.Color(image)
-    image = enhancer.enhance(1.5)  # Increase color saturation
-
-    # Enhance contrast
-    enhancer = ImageEnhance.Contrast(image)
-    image = enhancer.enhance(1.3)  # Increase contrast
-
-    # Apply a slight blur to simulate glow
-    image = image.filter(ImageFilter.GaussianBlur(radius=2))
-
-    # Optionally add noise (uncomment to use)
-    # noise = np.random.normal(0, 25, (image.height, image.width, 3))
-    # noise_image = np.array(image) + noise
-    # image = Image.fromarray(np.clip(noise_image, 0, 255).astype(np.uint8))
-
-    return image
-
 # Function to process image
 def process_image(content_image, style_image):
     # Ensure style_image is a PIL Image
@@ -101,10 +77,7 @@ def process_image(content_image, style_image):
 
     combined_image = Image.fromarray(np.clip(combined_image_np, 0, 255).astype(np.uint8))
 
-    # Apply enhancement to make it glistening
-    enhanced_image = enhance_image(combined_image)
-
-    return enhanced_image
+    return combined_image
 
 # Gradio interface setup
 image1 = gr.Image(label="Content Image")