feat: Add Editor Mode (Palette, Eraser, Path Tiles), generate assets, enable WASD

scripts/slice_assets.py

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+
+import cv2
+import numpy as np
+import os
+import glob
+
+# Configuration
+# Input files (Generated images)
+INPUT_FILES = [
+    {
+        'path': '/Users/davidkotnik/.gemini/antigravity/brain/8233d64e-0c17-43b1-b8b5-fbc41754e56b/trees_adult_noir_1769706733583.png',
+        'prefix': 'tree_adult',
+        'output_folder': 'assets/DEMO_FAZA1/Trees'
+    },
+    {
+        'path': '/Users/davidkotnik/.gemini/antigravity/brain/8233d64e-0c17-43b1-b8b5-fbc41754e56b/dead_nature_noir_1769706761105.png',
+        'prefix': 'dead_nature',
+        'output_folder': 'assets/DEMO_FAZA1/Environment'
+    },
+    {
+        'path': '/Users/davidkotnik/.gemini/antigravity/brain/8233d64e-0c17-43b1-b8b5-fbc41754e56b/fence_sign_noir_1769706790281.png',
+        'prefix': 'fence_sign',
+        'output_folder': 'assets/DEMO_FAZA1/Environment'
+    },
+    {
+        'path': '/Users/davidkotnik/.gemini/antigravity/brain/8233d64e-0c17-43b1-b8b5-fbc41754e56b/muddy_path_noir_v2_1769706866951.png',
+        'prefix': 'path_tile',
+        'output_folder': 'assets/DEMO_FAZA1/Ground',
+        'mode': 'grid',
+        'grid_size': 256
+    }
+]
+
+BASE_DIR = '/Users/davidkotnik/repos/novafarma'
+
+def process_and_slice(file_data):
+    full_path = file_data['path']
+    prefix = file_data['prefix']
+    out_dir_rel = file_data['output_folder']
+    mode = file_data.get('mode', 'contour') # Default to contour
+    
+    out_dir = os.path.join(BASE_DIR, out_dir_rel)
+
+    if not os.path.exists(out_dir):
+        os.makedirs(out_dir)
+
+    print(f"Processing {prefix} from {full_path} in {mode} mode...")
+    
+    img = cv2.imread(full_path, cv2.IMREAD_COLOR)
+    if img is None:
+        print(f"Error loading {full_path}")
+        return
+
+    h, w = img.shape[:2]
+
+    if mode == 'grid':
+        # Split into fixed grid cells
+        tile_size = file_data.get('grid_size', 256)
+        rows = h // tile_size
+        cols = w // tile_size
+        
+        count = 0
+        for r in range(rows):
+            for c in range(cols):
+                y = r * tile_size
+                x = c * tile_size
+                
+                roi = img[y:y+tile_size, x:x+tile_size]
+                
+                # Check if tile is empty (all white/uniform?)
+                # Calculate variance or average color.
+                if np.mean(roi) > 250: # Mostly white
+                    continue
+                
+                # We can enable alpha here if needed, but for ground tiles usually we want Opaque?
+                # User wants "Tile Palette". Tiles usually have transparency if they are "Path on Grass".
+                # Let's clean white background using same threshold logic.
+                
+                roi_gray = cv2.cvtColor(roi, cv2.COLOR_BGR2GRAY)
+                _, roi_mask = cv2.threshold(roi_gray, 240, 255, cv2.THRESH_BINARY_INV)
+                
+                roi_bgra = cv2.cvtColor(roi, cv2.COLOR_BGR2BGRA)
+                roi_bgra[:, :, 3] = roi_mask
+                
+                # Save
+                filename = f"{prefix}_{count}.png"
+                out_path = os.path.join(out_dir, filename)
+                cv2.imwrite(out_path, roi_bgra)
+                print(f"  Saved Grid Tile {filename}")
+                count += 1
+                
+    else: # Contour mode (old logic)
+        # 1. Remove Background (White) -> Alpha
+        # Assuming white background.
+        # Convert to Gray for thresholding
+        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+        
+        # Threshold: Close to white (240+) is background
+        _, mask = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY_INV)
+        # mask: White (255) is OBJECT, Black (0) is BACKGROUND
+
+        # Clean mask (remove noise)
+        kernel = np.ones((3,3), np.uint8)
+        mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel, iterations=1)
+        # Dilate slightly to include outlines?
+        # mask = cv2.dilate(mask, kernel, iterations=1)
+
+        # 2. Find Contours (Separate Objects)
+        contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+        count = 0
+        for i, c in enumerate(contours):
+            area = cv2.contourArea(c)
+            if area < 500: # Filter small noise
+                continue
+            
+            # Bounding box
+            x, y, w, h = cv2.boundingRect(c)
+            
+            # Crop
+            roi = img[y:y+h, x:x+w]
+            
+            # Create alpha channel for ROI
+            # We need a mask for this specific object in the ROI
+            roi_gray = cv2.cvtColor(roi, cv2.COLOR_BGR2GRAY)
+            # Re-threshold ROI to get clean alpha
+            _, roi_mask = cv2.threshold(roi_gray, 240, 255, cv2.THRESH_BINARY_INV)
+            
+            # Convert ROI to BGRA
+            roi_bgra = cv2.cvtColor(roi, cv2.COLOR_BGR2BGRA)
+            roi_bgra[:, :, 3] = roi_mask
+
+            # Save
+            filename = f"{prefix}_{count}.png"
+            out_path = os.path.join(out_dir, filename)
+            cv2.imwrite(out_path, roi_bgra)
+            print(f"  Saved {filename}")
+            count += 1
+
+if __name__ == "__main__":
+    for f in INPUT_FILES:
+        process_and_slice(f)