Implement Nova Farma S1 Max: Layered terrain, water mechanics, Y-sorting, and asset cleanup

scripts/utils/clean_and_move_image.py

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+
+import cv2
+import numpy as np
+import os
+import argparse
+import sys
+
+def clean_and_save(input_path, output_path):
+    # Ensure directory exists
+    os.makedirs(os.path.dirname(output_path), exist_ok=True)
+
+    print(f"Processing: {input_path}")
+    
+    # Read image
+    img = cv2.imread(input_path)
+    if img is None:
+        print(f"Error: Could not read {input_path}")
+        sys.exit(1)
+
+    # Convert to RGBA
+    img = cv2.cvtColor(img, cv2.COLOR_BGR2BGRA)
+
+    # Convert to HSV for better color segmentation
+    hsv = cv2.cvtColor(img[:,:,:3], cv2.COLOR_BGR2HSV)
+
+    # Define Magenta range in HSV
+    # Magenta is around 300 degrees. OpenCV Hue is 0-179 (degrees/2). So 300/2 = 150.
+    # Range: 140 - 160 approx.
+    # We want to catch the solid pink background.
+    
+    # Lower and Upper bounds for Magenta/Pink
+    # Hue: 140-170, Saturation: > 50, Value: > 50
+    lower_magenta = np.array([140, 50, 50])
+    upper_magenta = np.array([170, 255, 255])
+    
+    mask = cv2.inRange(hsv, lower_magenta, upper_magenta)
+    
+    # Invert mask (keep non-magenta)
+    mask_inv = cv2.bitwise_not(mask)
+    
+    # Update alpha channel
+    # Where mask is 255 (magenta), alpha should be 0.
+    # We can just set the alpha channel to mask_inv directly.
+    # However, to avoid hard edges, we might want to erode/dilate, but for pixel/vector props hard cut is usually fine.
+    
+    # Let's perform a small morphological operation to remove pink noise on edges if any
+    kernel = np.ones((1,1), np.uint8)
+    mask_inv = cv2.morphologyEx(mask_inv, cv2.MORPH_OPEN, kernel)
+    
+    b, g, r, a = cv2.split(img)
+    img = cv2.merge((b, g, r, mask_inv))
+    
+    # Crop to content (optional but good for assets)
+    # Find bounding box of non-transparent area
+    coords = cv2.findNonZero(mask_inv)
+    if coords is not None:
+        x, y, w, h = cv2.boundingRect(coords)
+        # Add 1px padding if possible
+        x = max(0, x-1)
+        y = max(0, y-1)
+        w = min(img.shape[1]-x, w+2)
+        h = min(img.shape[0]-y, h+2)
+        img = img[y:y+h, x:x+w]
+    
+    # Save
+    cv2.imwrite(output_path, img)
+    print(f"Successfully saved cleaned image to {output_path}")
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description='Remove magenta background and save.')
+    parser.add_argument('input', help='Input file path')
+    parser.add_argument('output', help='Output file path')
+    args = parser.parse_args()
+
+    clean_and_save(args.input, args.output)