more work on fog & c30

1 files changed, 53 insertions, 0 deletions

diff --git a/Scripts/gen_sdf b/Scripts/gen_sdf
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index 0000000..52ef487
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+++ b/Scripts/gen_sdf
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+#!/usr/bin/env python3
+
+import numpy as np
+import cv2
+import argparse
+import os
+
+def compute_sdf(img, scale_factor):
+    # Convert to binary image if not already
+    _, binary = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY)
+    
+    # Compute distance transform for both foreground and background
+    dist_transform_fg = cv2.distanceTransform(binary, cv2.DIST_L2, 5)
+    dist_transform_bg = cv2.distanceTransform(255 - binary, cv2.DIST_L2, 5)
+    
+    # Combine the distance fields and scale by factor
+    sdf = (dist_transform_fg - dist_transform_bg) / scale_factor
+    
+    # Normalize values to [0, 255] range
+    sdf_min = np.min(sdf)
+    sdf_max = np.max(sdf)
+    sdf = ((sdf - sdf_min) * 255 / (sdf_max - sdf_min))
+    
+    return sdf.astype(np.uint8)
+
+def main():
+    parser = argparse.ArgumentParser(description='Generate SDF from black and white image')
+    parser.add_argument('input_images', nargs='+', help='Path to input image(s)')
+    parser.add_argument('--scale', type=float, default=1.0, 
+                        help='Scale factor for distance (in texels)')
+    args = parser.parse_args()
+    
+    # Process each input image
+    for input_path in args.input_images:
+        # Get input and output paths
+        filename, ext = os.path.splitext(input_path)
+        output_path = f"{filename}-sdf{ext}"
+        
+        # Read input image
+        img = cv2.imread(input_path, cv2.IMREAD_GRAYSCALE)
+        if img is None:
+            print(f"Error: Could not read image {input_path}")
+            continue
+        
+        # Compute SDF with scale factor
+        sdf = compute_sdf(img, args.scale)
+        
+        # Save result
+        cv2.imwrite(output_path, sdf)
+        print(f"SDF generated and saved to {output_path}")
+
+if __name__ == "__main__":
+    main()