Update app.py

app.py

@@ -3,46 +3,36 @@ import cv2
 import numpy as np
 from PIL import Image
 
-def cartoonize_image(img, median_blur_value, block_size, c_value, d_value, sigma_color, sigma_space):
+def pencil_effect(img, high_blur_value, block_size, c_value):
     # Convert to grayscale
     gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
 
-    # Apply median blur
-    gray = cv2.medianBlur(gray, median_blur_value)
+    # Apply high Gaussian blur
+    blurred = cv2.GaussianBlur(gray, (high_blur_value, high_blur_value), 0)
 
     # Adaptive thresholding for edges
-    edges = cv2.adaptiveThreshold(gray, 255,
+    edges = cv2.adaptiveThreshold(blurred, 255,
                                   cv2.ADAPTIVE_THRESH_MEAN_C,
                                   cv2.THRESH_BINARY,
                                   blockSize=block_size,
                                   C=c_value)
 
-    # Bilateral filter for color smoothing (reduce colors)
-    color = cv2.bilateralFilter(img, d=d_value, sigmaColor=sigma_color, sigmaSpace=sigma_space)
+    return edges
 
-    # Convert color image to grayscale and then back to BGR
-    color_gray = cv2.cvtColor(color, cv2.COLOR_BGR2GRAY)
-    
-    # Reduce colors by applying a threshold on the grayscale image
-    _, color_thresh = cv2.threshold(color_gray, 200, 255, cv2.THRESH_BINARY_INV)
-
-    # Create a sketch effect by blending edges with the smoothed color image
-    sketch = cv2.bitwise_and(color, color, mask=edges)
-
-    # Ensure both images are of the same size before blending
-    if sketch.shape[:2] != img.shape[:2]:
-        sketch = cv2.resize(sketch, (img.shape[1], img.shape[0]))
+def cartoonize_image(img, high_blur_value, block_size, c_value):
+    # Apply pencil effect to get edges
+    edges = pencil_effect(img, high_blur_value, block_size, c_value)
 
-    # Combine the sketch with a desaturated version of the original image
-    desaturated_color = cv2.addWeighted(color, 0.3, np.zeros_like(color), 0.7, 0)  # Reduce saturation
+    # Reduce colors using bilateral filter
+    color = cv2.bilateralFilter(img, d=9, sigmaColor=100, sigmaSpace=100)
 
-    # Blend sketch and desaturated color image
-    cartoon = cv2.addWeighted(desaturated_color, 0.5, sketch, 0.5, 0)
+    # Combine edges with color image to create a more artistic effect
+    cartoon = cv2.bitwise_and(color, color, mask=edges)
 
     return cartoon
 
 # Streamlit app layout
-st.title("Image Cartoonizer")
+st.title("Pencil Effect Cartoonizer")
 st.subheader("Upload an image and adjust parameters")
 
 # Upload image
@@ -56,17 +46,14 @@ if uploaded_file is not None:
     # Create a container for sliders on the left side
     with st.sidebar:
         st.header("Adjust Parameters")
-        median_blur_value = st.slider("Median Blur Value", min_value=3, max_value=11, value=5, step=2)
+        high_blur_value = st.slider("High Blur Value", min_value=3, max_value=31, value=21, step=2)  # Increased range for more blur
         block_size = st.slider("Block Size", min_value=3, max_value=21, value=9, step=2)
         c_value = st.slider("C Value", min_value=0, max_value=20, value=5)  # Increased default value for more effect
-        d_value = st.slider("Diameter (d)", min_value=1, max_value=15, value=9)
-        sigma_color = st.slider("Sigma Color", min_value=0, max_value=400, value=100)  # Reduced for more sketch effect
-        sigma_space = st.slider("Sigma Space", min_value=0, max_value=400, value=100)  # Reduced for more sketch effect
 
     # Show a spinner while processing the cartoonization
     with st.spinner('Processing...'):
         # Cartoonize the image with selected parameters in real-time
-        cartoon_image = cartoonize_image(img, median_blur_value, block_size, c_value, d_value, sigma_color, sigma_space)
+        cartoon_image = cartoonize_image(img, high_blur_value, block_size, c_value)
 
     # Display original and cartoonized images side by side on the right side
     col1, col2 = st.columns(2)
@@ -75,18 +62,18 @@ if uploaded_file is not None:
         st.image(img.astype(np.uint8), caption='Original Image', use_column_width=True)
 
     with col2:
-        st.image(cartoon_image.astype(np.uint8), caption='Cartoonized Image', use_column_width=True)
+        st.image(cartoon_image.astype(np.uint8), caption='Pencil Effect Cartoonized Image', use_column_width=True)
 
     # Download button for cartoonized image
     if st.button("Download Cartoonized Image"):
         # Convert the cartoonized image to PIL format for download
         cartoon_image_pil = Image.fromarray(cartoon_image)
-        cartoon_image_pil.save("cartoonized_image.png")
+        cartoon_image_pil.save("pencil_cartoonized_image.png")
         
-        with open("cartoonized_image.png", "rb") as f:
+        with open("pencil_cartoonized_image.png", "rb") as f:
             st.download_button(
                 label="Download Image",
                 data=f,
-                file_name="cartoonized_image.png",
+                file_name="pencil_cartoonized_image.png",
                 mime="image/png"
             )