# Grayish-white versions of the Sci-Fi Panels maps (asked for by the user on 2026-10-12:
# "Do the textures grayish white").
#
#   <key>_base.png + <key>_orm.png  ->  <key>_base_gw.png, <key>_orm_gw.png   (same folder, originals unchanged)
#
# Base colour: the pack has three flat tones, black paint (0.133), grey metal (~0.43) and white paint (0.965).
# TONE maps them into one light range, so every panel reads grayish white and its design stays as a soft
# two-tone. The pack's ambient-occlusion channel (ORM red) is multiplied in, so slots, vents, seams and holes
# stay visible as grey lines.
# ORM: only the metallic channel (blue) changes. The pack marks its paint as half metal (0.5) and its bare
# metal as 0.8; a light colour with that much metal mirrors the surroundings and takes their colour instead
# of looking white. Paint becomes 0, metal becomes METAL_OUT[1]. Occlusion and roughness are kept.
# Normal maps are used as they are.
#
# Run:  python make_graywhite.py [folder]        (default: the folder this file is in)
# The same recipe works on the 4K originals once they are named <key>_base.png / <key>_orm.png.
import os, sys, glob
import numpy as np
from PIL import Image

# sRGB-encoded input value -> sRGB-encoded output value (piecewise linear)
TONE = [(0.000, 0.40),      # open holes of the gratings: stay clearly darker
        (0.133, 0.68),      # black paint  -> light grey
        (0.430, 0.77),      # grey metal   -> pale grey
        (0.965, 0.88),      # white paint  -> off-white
        (1.000, 0.885)]
AO_STRENGTH = 0.85          # how much of the occlusion map is multiplied into the colour (0 = none)
METAL_IN = (0.5, 0.8)       # the pack's metallic values for paint and for bare metal
METAL_OUT = (0.0, 0.3)      # what they become

def convert(base_path, orm_path, out_base, out_orm):
    a = np.asarray(Image.open(base_path).convert('RGB'), dtype=np.float32) / 255.0
    y = 0.2126 * a[..., 0] + 0.7152 * a[..., 1] + 0.0722 * a[..., 2]
    xs, ys = zip(*TONE)
    out = np.interp(y, xs, ys)
    if os.path.exists(orm_path):
        orm_im = Image.open(orm_path).convert('RGB')
        o = np.asarray(orm_im, dtype=np.float32) / 255.0
        ao = orm_im.resize((a.shape[1], a.shape[0]), Image.LANCZOS) if orm_im.size != (a.shape[1], a.shape[0]) else orm_im
        ao = np.asarray(ao, dtype=np.float32)[..., 0] / 255.0
        out = out * (1.0 - AO_STRENGTH * (1.0 - ao))
        o = o.copy()
        o[..., 2] = np.interp(o[..., 2], METAL_IN, METAL_OUT)
        Image.fromarray(np.clip(o * 255.0 + 0.5, 0, 255).astype(np.uint8), 'RGB').save(out_orm, optimize=True)
    g = np.clip(out * 255.0 + 0.5, 0, 255).astype(np.uint8)
    Image.merge('RGB', (Image.fromarray(g),) * 3).save(out_base, optimize=True)
    return float(out.mean())

if __name__ == '__main__':
    folder = sys.argv[1] if len(sys.argv) > 1 else os.path.dirname(os.path.abspath(__file__))
    for f in sorted(glob.glob(os.path.join(folder, '*_base.png'))):
        key = os.path.basename(f)[:-len('_base.png')]
        m = convert(f, os.path.join(folder, key + '_orm.png'),
                    os.path.join(folder, key + '_base_gw.png'), os.path.join(folder, key + '_orm_gw.png'))
        print('%-10s mean %.3f' % (key, m))