stitch_tiles.py

import os
from PIL import Image

# Configuration
tile_size = 128
output_size = 256
input_dir = "./minimap_data_processed"
output_dir = f"./stitched_{input_dir.strip('./').strip("_processed")}"
os.makedirs(output_dir, exist_ok=True)

# Maximum tile coordinates
min_x, max_x = 0,0   # x in range(min_x, max_x, 2)
min_y, max_y = 0,0    # y in range(min_y, max_y, 2)

for file in os.listdir(input_dir):
    base = file.rsplit(".", 1)[0]   # remove extension
    _, x, y = base.split("_")
    x, y = int(x), int(y)
    min_x = min(min_x, x)
    max_x = max(max_x, x)
    min_y = min(min_y, y)
    max_y = max(max_y, y)

x_steps     = len(range(min_x, max_x + 2, 2))
y_steps     = len(range(min_y, max_y + 2, 2))
total_steps = x_steps * y_steps
done        = 0
saved       = 0

# Process in 2x2 steps (0, 2, 4...)
for x in range(min_x, max_x + 2, 2):
    for y in range(min_y, max_y + 2, 2):
        # Change the coordinates to start from 0, 0
        col = (x - min_x)
        row_raw = (y - min_y)
        max_row = (max_y - min_y) # Number of rows (0-based top = max_y)
        row = max_row - row_raw # Flip: high y -> low row index (top of image)

        # Create a blank 256x256 canvas (RGBA for transparency)
        canvas = Image.new("RGBA", (output_size, output_size), (0, 0, 0, 0))
        has_any_tile = False

        # Check the 4 tiles for this 256x256 block
        offsets = [(0, 0), (1, 0), (0, 1), (1, 1)]
        for dx, dy in offsets:
            tile_name = f"rader_{x + dx}_{y + dy}.png"
            tile_path = os.path.join(input_dir, tile_name)

            if os.path.exists(tile_path):
                img = Image.open(tile_path).convert("RGBA")
                # dy = 0 -> bottom half (lower y = more south)
                # dy = 1 -> top half (higher y = north)
                paste_y = (1-dy) * tile_size
                canvas.paste(img, (dx * tile_size, paste_y))
                has_any_tile = True

        done += 1
        # Save only if at least one tile existed
        if has_any_tile:
            out_col = col // 2
            out_row = row // 2

            canvas.save(f"{output_dir}/tile_{out_col}_{out_row}.webp", "WEBP", quality=82, method=6)
            saved +=1
        print(f"\rProgress: {done}/{total_steps} ({done / total_steps * 100:.1f}%)", end="", flush=True)

print()
print("Batch processing complete.")