Update app.py

app.py

@@ -12,72 +12,103 @@ import gradio as gr
 
 # Function to convert image to sketch
 def convert_to_sketch(img, blur_strength, brightness, contrast):
-    # Convert PIL Image to numpy array (BGR format for OpenCV)
-    img = np.array(img)
-    
-    # Convert the image to grayscale (use RGB2GRAY for PIL images)
-    img_gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
-    
-    # Invert the grayscale image
-    img_inverted = cv2.bitwise_not(img_gray)
-    
-    # Apply Gaussian blur to the inverted image
-    img_blur = cv2.GaussianBlur(img_inverted, (blur_strength, blur_strength), sigmaX=0, sigmaY=0)
-    
-    # Blend the grayscale and blurred inverted images to create the sketch effect
-    img_blend = cv2.divide(img_gray, 255 - img_blur, scale=256)
-    
-    # Create a white background
-    white_background = 255 * np.ones_like(img_blend)
-    
-    # Add the blended image to the white background
-    sketch_with_bg = cv2.addWeighted(img_blend, 1, white_background, 1, 0)
-    
-    # Adjust brightness and contrast
-    sketch_with_bg = adjust_brightness_contrast(sketch_with_bg, brightness, contrast)
-    
-    return sketch_with_bg
+    try:
+        # Convert PIL Image to numpy array (BGR format for OpenCV)
+        img = np.array(img)
+        
+        # Ensure blur_strength is odd
+        blur_strength = max(1, int(blur_strength))
+        if blur_strength % 2 == 0:
+            blur_strength += 1
+            
+        # Convert the image to grayscale
+        img_gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
+        
+        # Invert the grayscale image
+        img_inverted = 255 - img_gray
+        
+        # Apply Gaussian blur to the inverted image
+        img_blur = cv2.GaussianBlur(img_inverted, (blur_strength, blur_strength), 0)
+        
+        # Blend the grayscale and blurred inverted images
+        # Avoid division by zero by adding a small constant
+        denominator = 255 - img_blur
+        denominator[denominator == 0] = 1  # Prevent division by zero
+        
+        img_blend = cv2.multiply(img_gray, 256.0 / denominator)
+        
+        # Clip values to valid range
+        img_blend = np.clip(img_blend, 0, 255).astype(np.uint8)
+        
+        # Adjust brightness and contrast
+        sketch_with_bg = adjust_brightness_contrast(img_blend, brightness, contrast)
+        
+        return sketch_with_bg
+        
+    except Exception as e:
+        print(f"Error in convert_to_sketch: {str(e)}")
+        return None
 
 # Function to adjust brightness and contrast
 def adjust_brightness_contrast(img, brightness, contrast):
-    # Apply contrast adjustment
-    img = cv2.convertScaleAbs(img, alpha=contrast, beta=brightness)
-    return img
+    try:
+        # Ensure brightness is within valid range
+        brightness = float(brightness)
+        contrast = float(contrast)
+        
+        # Apply contrast first
+        img = cv2.convertScaleAbs(img, alpha=contrast)
+        
+        # Apply brightness
+        if brightness > 0:
+            img = cv2.add(img, np.ones_like(img) * brightness)
+        else:
+            img = cv2.subtract(img, np.ones_like(img) * abs(brightness))
+            
+        # Ensure output is in valid range
+        img = np.clip(img, 0, 255).astype(np.uint8)
+        return img
+        
+    except Exception as e:
+        print(f"Error in adjust_brightness_contrast: {str(e)}")
+        return None
 
 # Gradio interface function
 def sketch_interface(image, blur_strength, brightness, contrast):
-    # Convert the input image to a sketch with adjustments
-    sketch = convert_to_sketch(image, blur_strength, brightness, contrast)
-
-    # Check if the sketch image is non-empty
-    if sketch is None or sketch.size == 0:
-        print("Error: Sketch is empty!")
+    if image is None:
+        print("Error: No input image provided!")
         return None
-
-    # Convert the processed numpy array back to a PIL Image
-    output_image = Image.fromarray(sketch)
-    
-    # Ensure the output image is valid
-    if output_image is None:
-        print("Error: Output image is None!")
+        
+    try:
+        # Convert the input image to a sketch with adjustments
+        sketch = convert_to_sketch(image, blur_strength, brightness, contrast)
+        
+        if sketch is None:
+            print("Error: Sketch conversion failed!")
+            return None
+            
+        # Convert the processed numpy array back to a PIL Image
+        output_image = Image.fromarray(sketch)
+        
+        return output_image
+        
+    except Exception as e:
+        print(f"Error in sketch_interface: {str(e)}")
         return None
 
-    # Return the processed sketch image
-    return output_image
-
 # Create Gradio interface
 interface = gr.Interface(
     fn=sketch_interface,
     inputs=[
         gr.Image(type="pil", label="Upload Image"),
-        gr.Slider(1, 51, step=2, label="Blur Strength", value=21),
-        gr.Slider(-100, 100, label="Brightness", value=0),
-        gr.Slider(1, 3, step=0.1, label="Contrast", value=1)
+        gr.Slider(minimum=1, maximum=51, step=2, value=21, label="Blur Strength"),
+        gr.Slider(minimum=-100, maximum=100, value=0, label="Brightness"),
+        gr.Slider(minimum=0.1, maximum=3, step=0.1, value=1, label="Contrast")
     ],
-    outputs=[gr.Image(type="pil", label="Sketch Output")],
+    outputs=gr.Image(type="pil", label="Sketch Output"),
     title="Cartoon to Sketch Converter",
     description="Upload an image to convert it into a sketch, adjust the blur strength, brightness, and contrast for different effects."
 )
 
 # Launch the Gradio app
-interface.launch()
+interface.launch()