normal_map.py

from PIL import Image

def load_normal_map(path):
    img = Image.open(path).convert("RGB")
    width, height = img.size

    normals = []

    for y in range(height):
        row = []
        for x in range(width):
            r, g, b = img.getpixel((x, y))
            nx = (r / 255.0) * 2.0 - 1.0
            ny = (g / 255.0) * 2.0 - 1.0
            nz = (b / 255.0) * 2.0 - 1.0
            row.append((nx, ny, nz))
        normals.append(row)

    return normals, width, height

def save_heightmap(heights, output_path):
    height = len(heights)
    width = len(heights[0]) if height > 0 else 0

    flat_values = [val for row in heights for val in row]
    min_val = min(flat_values)
    max_val = max(flat_values)

    if max_val - min_val == 0:
        normalized = [[128 for _ in range(width)] for _ in range(height)] 
    else:
        normalized = [
            [int((val - min_val) / (max_val - min_val) * 255) for val in row]
            for row in heights
        ]

    img = Image.new('L', (width, height))
    for y in range(height):
        for x in range(width):
            img.putpixel((x, y), normalized[y][x])

    img.save(output_path)

if __name__ == "__main__":
    normals, width, height = load_normal_map("normals.png")

    heights_x_first = [[0]]
    # Fill up the first row
    for x in range(1, width):
        nx, ny, nz = normals[0][x]
        x_slope = nx / nz
        heights_x_first[0].append(heights_x_first[0][x - 1] + x_slope)

    # Fill up the columns
    for y in range(1, height):
        row = []
        for x in range(0, width):
            nx, ny, nz = normals[y][x]
            y_slope = ny / nz
            row.append(heights_x_first[y - 1][x] + y_slope)
        heights_x_first.append(row)

    save_heightmap(heights_x_first, "height_x_first.png")

    heights_y_first = [[0]]
    # Fill up the first column
    for y in range(1, height):
        nx, ny, nz = normals[y][0]
        y_slope = ny / nz
        heights_y_first.append([heights_y_first[y - 1][0] + y_slope])

    # Fill up the columns
    for y in range(0, height):
        for x in range(1, width):
            nx, ny, nz = normals[y][x]
            x_slope = nx / nz
            heights_y_first[y].append(heights_y_first[y][x - 1] + x_slope)

    save_heightmap(heights_y_first, "height_y_first.png")