Fix next_level image glitch: reset camera scroll and improve image color quantization

scripts/process_next_level.py

@@ -1,26 +1,34 @@
 from PIL import Image
+import numpy as np
+from scipy.cluster.vq import kmeans, vq
 
-img = Image.open('assets/next_level.png').convert('L') # Convert to grayscale
-img = img.quantize(colors=4) # Quantize to 4 colors
-img = img.convert('RGB')
-# Force colors to exactly GB shades
-palette = [(224, 248, 208), (136, 192, 112), (52, 104, 86), (8, 24, 32)]
-# Actually the game uses generic colors or grayscale. Let's use 4 grayscale values:
-gb_palette = [(255,255,255), (170,170,170), (85,85,85), (0,0,0)]
+# Open original and convert to grayscale
+img = Image.open('assets/next_level_original.png').convert('L')
+pixels = np.array(img, dtype=float)
 
-new_img = Image.new('RGB', img.size)
-for y in range(img.height):
-    for x in range(img.width):
-        p = img.getpixel((x, y))
-        # Find closest color in gb_palette
-        best_c = gb_palette[0]
-        min_dist = 1000000
-        for c in gb_palette:
-            dist = (p[0]-c[0])**2 + (p[1]-c[1])**2 + (p[2]-c[2])**2
-            if dist < min_dist:
-                min_dist = dist
-                best_c = c
-        new_img.putpixel((x, y), best_c)
+# Flatten for clustering
+flat_pixels = pixels.flatten()
 
+# Find 4 clusters
+centroids, _ = kmeans(flat_pixels, 4)
+
+# Sort centroids by brightness (dark to light)
+sorted_centroids = np.sort(centroids)
+
+# Map centroids to GB colors
+# GB palette: 0=Black, 1=Dark Gray, 2=Light Gray, 3=White
+gb_colors = np.array([0, 85, 170, 255])
+
+# Find the closest centroid for each pixel
+# Assign the corresponding GB color
+quantized_pixels = np.zeros_like(flat_pixels, dtype=np.uint8)
+for i, p in enumerate(flat_pixels):
+    dist = np.abs(sorted_centroids - p)
+    closest_idx = np.argmin(dist)
+    quantized_pixels[i] = gb_colors[closest_idx]
+
+# Reshape back to image
+quantized_img_data = quantized_pixels.reshape(pixels.shape)
+new_img = Image.fromarray(quantized_img_data, mode='L').convert('RGB')
 new_img.save('assets/next_level.png')
-print("Processed next_level.png")
+print("Processed next_level.png with k-means clustering!")