refactor

.gitignore

@@ -2,4 +2,5 @@
 .gradio/
 .vscode/
 
-imgs/
+__pycache__
+imgs

README.md

@@ -9,4 +9,5 @@ app_file: app.py
 pinned: false
 ---
 
-# Simple Pixelart Filter :p
+# Simple Pixelart Filter
+

app.py

@@ -1,59 +1,6 @@
-import cv2
 import gradio as gr
-import numpy as np
 
-
-def sort_by_brightness(palette: np.uint8):
-    # https://stackoverflow.com/a/596241
-    luminosity = (
-        0.2126 * palette[:, 2] + 0.7152 * palette[:, 1] + 0.0722 * palette[:, 0]
-    )
-    return palette[np.argsort(luminosity)]
-
-
-def display_palette(palette: np.uint8, sort=True):
-    swatch_size = 100
-    num_colors = palette.shape[0]
-    palette_image = np.zeros((swatch_size, swatch_size * num_colors, 3), dtype=np.uint8)
-
-    if sort:
-        palette = sort_by_brightness(palette)
-
-    for i, color in enumerate(palette):
-        palette_image[:, i * swatch_size : (i + 1) * swatch_size] = color
-
-    return palette_image
-
-
-def extract_color_palette(img, k: int):
-    pixels = img.reshape((-1, 3))
-    pixels = np.float32(pixels)
-
-    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 10, 1.0)
-    _, labels, centers = cv2.kmeans(
-        pixels, k, None, criteria, 10, cv2.KMEANS_RANDOM_CENTERS
-    )
-
-    palette = np.uint8(centers)
-    return palette, labels
-
-
-def pixelate(img, pixel_size: int, blur=False, use_palette=False, k=8):
-    palette = None
-    if use_palette:
-        palette, labels = extract_color_palette(img, k)
-        res = palette[labels.flatten()]
-        img = res.reshape((img.shape))
-        palette = display_palette(palette, sort=True)
-
-    if blur:
-        img = cv2.blur(img, (7, 7))
-
-    for i in range(0, img.shape[0], pixel_size):
-        for j in range(0, img.shape[1], pixel_size):
-            img[i : i + pixel_size, j : j + pixel_size] = img[i][j]
-
-    return img, palette
+from src.pixelate import pixelate
 
 
 def update_palette_visibility(use_palette):
@@ -103,6 +50,7 @@ with gr.Blocks() as demo:
         gr.Markdown("## Examples")
         gr.Examples(
             examples=[
+                ["example_images/bananas.jpg", 16, False, True, 8],
                 ["example_images/scream.jpg", 16, False, True, 4],
                 ["example_images/cat.jpg", 32, True, False, None],
                 ["example_images/ducks.jpg", 4, False, True, 2],

src/pixelate.py

@@ -0,0 +1,71 @@
+import cv2
+import numpy as np
+
+
+def sort_by_brightness(palette: np.uint8):
+    """
+    Sorts given color palette by brightness.
+    
+    https://stackoverflow.com/a/596241
+    """
+    
+    luminosity = (
+        0.2126 * palette[:, 2] + 0.7152 * palette[:, 1] + 0.0722 * palette[:, 0]
+    )
+    return palette[np.argsort(luminosity)]
+
+
+def display_palette(palette: np.uint8, sort=True):
+    """
+    Generates an image displaying given color palette.
+    """
+    swatch_size = 100
+    num_colors = palette.shape[0]
+    palette_image = np.zeros((swatch_size, swatch_size * num_colors, 3), dtype=np.uint8)
+
+    if sort:
+        palette = sort_by_brightness(palette)
+
+    for i, color in enumerate(palette):
+        palette_image[:, i * swatch_size : (i + 1) * swatch_size] = color
+
+    return palette_image
+
+
+def extract_color_palette(img, k: int):
+    """
+    Extracts color palette from the given image using k-means clustering.
+    """
+
+    pixels = img.reshape((-1, 3))
+    pixels = np.float32(pixels)
+
+    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 10, 1.0)
+    _, labels, centers = cv2.kmeans(
+        pixels, k, None, criteria, 10, cv2.KMEANS_RANDOM_CENTERS
+    )
+
+    palette = np.uint8(centers)
+    return palette, labels
+
+
+def pixelate(img, pixel_size: int, blur=False, use_palette=False, k=8):
+    """
+    Pixelates an image by reducing its pixel resolution and optionally applying blur effect and color quantization.
+    """
+
+    palette = None
+    if use_palette:
+        palette, labels = extract_color_palette(img, k)
+        res = palette[labels.flatten()]
+        img = res.reshape((img.shape))
+        palette = display_palette(palette, sort=True)
+
+    if blur:
+        img = cv2.blur(img, (7, 7))
+
+    for i in range(0, img.shape[0], pixel_size):
+        for j in range(0, img.shape[1], pixel_size):
+            img[i : i + pixel_size, j : j + pixel_size] = img[i][j]
+
+    return img, palette