ii-pix/convert.py

"""Image converter to Apple II Double Hi-Res format."""

import argparse
import os.path

from PIL import Image
import colour
import numpy as np
import pygame
from sklearn import cluster

import dither as dither_pyx
import dither_pattern
import image as image_py
import palette as palette_py
import screen as screen_py


# TODO:
# - support LR/DLR
# - support HGR

class ClusterPalette:
    def __init__(self, image: Image):
        self._colours_cam = self._image_colours_cam(image)
        self._best_palette_distances = [1e9] * 16
        self._palettes_cam = np.empty((16, 16, 3), dtype=np.float32)
        self._palettes_rgb = np.empty((16, 16, 3), dtype=np.float32)

    def _image_colours_cam(self, image: Image):
        colours_rgb = np.asarray(image).reshape((-1, 3))
        with colour.utilities.suppress_warnings(colour_usage_warnings=True):
            colours_cam = colour.convert(colours_rgb, "RGB",
                                         "CAM16UCS").astype(np.float32)
        return colours_cam

    def _fit_global_palette(self):
        """Compute a 16-colour palette for the entire image to use as
        starting point for the sub-palettes.  This should help when the image
        has large blocks of colour since the sub-palettes will tend to pick the
        same colours."""
        clusters = cluster.MiniBatchKMeans(n_clusters=16, max_iter=10000)
        clusters.fit_predict(self._colours_cam)
        return clusters.cluster_centers_

    def iterate(self):
        self._global_palette = self._fit_global_palette()
        for palette_idx in range(16):
            palette_band_width = 3
            p_lower = max(palette_idx + 0.5 - (palette_band_width / 2), 0)
            p_upper = min(palette_idx + 0.5 + (palette_band_width / 2), 16)
            # TODO: dynamically tune palette cuts
            palette_pixels = self._colours_cam[
                             int(p_lower * (200 / 16)) * 320:int(p_upper * (
                                     200 / 16)) * 320, :]

            # TODO: clustering should be aware of the fact that we will
            #  down-quantize to a 4-bit RGB value afterwards.  i.e. we should
            #  not pick multiple centroids that will quantize to the same RGB
            #  value since we'll "waste" a palette entry.  This doesn't seem to
            #  be a major issue in practise though, and fixing it would require
            #  implementing our own (optimized) k-means.
            best_wce = self._best_palette_distances[palette_idx]
            # TODO: tune tolerance
            clusters = cluster.MiniBatchKMeans(
                n_clusters=16, max_iter=10000, init=self._global_palette,
                n_init=1)
            clusters.fit_predict(palette_pixels)
            if clusters.inertia_ < best_wce:
                self._palettes_cam[palette_idx, :, :] = np.array(
                    clusters.cluster_centers_).astype(np.float32)
                best_wce = clusters.inertia_
                self._best_palette_distances[palette_idx] = best_wce

                # Suppress divide by zero warning,
                # https://github.com/colour-science/colour/issues/900
                with colour.utilities.suppress_warnings(python_warnings=True):
                    palette_rgb = colour.convert(
                        self._palettes_cam[palette_idx], "CAM16UCS", "RGB")
                    # SHR colour palette only uses 4-bit values
                    palette_rgb = np.round(palette_rgb * 15) / 15
                    self._palettes_rgb[palette_idx, :, :] = palette_rgb.astype(
                        np.float32)

        return self._palettes_cam, self._palettes_rgb


def main():
    parser = argparse.ArgumentParser()
    parser.add_argument("input", type=str, help="Input image file to process.")
    parser.add_argument("output", type=str, help="Output file for converted "
                                                 "Apple II image.")
    parser.add_argument(
        "--lookahead", type=int, default=8,
        help=("How many pixels to look ahead to compensate for NTSC colour "
              "artifacts (default: 8)"))
    parser.add_argument(
        '--dither', type=str, choices=list(dither_pattern.PATTERNS.keys()),
        default=dither_pattern.DEFAULT_PATTERN,
        help="Error distribution pattern to apply when dithering (default: "
             + dither_pattern.DEFAULT_PATTERN + ")")
    parser.add_argument(
        '--show-input', action=argparse.BooleanOptionalAction, default=False,
        help="Whether to show the input image before conversion.")
    parser.add_argument(
        '--show-output', action=argparse.BooleanOptionalAction, default=True,
        help="Whether to show the output image after conversion.")
    parser.add_argument(
        '--palette', type=str, choices=list(set(palette_py.PALETTES.keys())),
        default=palette_py.DEFAULT_PALETTE,
        help='RGB colour palette to dither to.  "ntsc" blends colours over 8 '
             'pixels and gives better image quality on targets that '
             'use/emulate NTSC, but can be substantially slower.  Other '
             'palettes determine colours based on 4 pixel sequences '
             '(default: ' + palette_py.DEFAULT_PALETTE + ")")
    parser.add_argument(
        '--show-palette', type=str, choices=list(palette_py.PALETTES.keys()),
        help="RGB colour palette to use when --show_output (default: "
             "value of --palette)")
    parser.add_argument(
        '--verbose', action=argparse.BooleanOptionalAction,
        default=False, help="Show progress during conversion")
    parser.add_argument(
        '--gamma_correct', type=float, default=2.4,
        help='Gamma-correct image by this value (default: 2.4)'
    )
    args = parser.parse_args()
    if args.lookahead < 1:
        parser.error('--lookahead must be at least 1')

    # palette = palette_py.PALETTES[args.palette]()
    screen = screen_py.SHR320Screen()

    # Conversion matrix from RGB to CAM16UCS colour values.  Indexed by
    # 24-bit RGB value
    rgb_to_cam16 = np.load("data/rgb_to_cam16ucs.npy")

    # Open and resize source image
    image = image_py.open(args.input)
    if args.show_input:
        image_py.resize(image, screen.X_RES, screen.Y_RES,
                        srgb_output=False).show()
    rgb = np.array(
        image_py.resize(image, screen.X_RES, screen.Y_RES,
                        gamma=args.gamma_correct)).astype(np.float32) / 255

    iigs_palette = np.empty((16, 16, 3), dtype=np.uint8)

    # TODO: flags
    penalty = 1e9  # 0  # 1e9
    iterations = 50  # 0

    pygame.init()
    # TODO: for some reason I need to execute this twice - the first time
    #  the window is created and immediately destroyed
    _ = pygame.display.set_mode((640, 400))
    canvas = pygame.display.set_mode((640, 400))
    canvas.fill((0, 0, 0))
    pygame.display.flip()

    total_image_error = 1e9
    cluster_palette = ClusterPalette(rgb)
    image_generation = 0
    for iteration in range(iterations):
        # TODO: clean this up - e.g. pass in an acceptance lambda to iterate()
        old_best_palette_distances = cluster_palette._best_palette_distances
        old_palettes_cam = cluster_palette._palettes_cam
        old_palettes_rgb = cluster_palette._palettes_rgb

        new_palettes_cam, new_palettes_rgb = cluster_palette.iterate()
        output_4bit, line_to_palette, new_total_image_error = \
            dither_pyx.dither_shr(
                rgb, new_palettes_cam, new_palettes_rgb, rgb_to_cam16,
                float(penalty)
            )

        if new_total_image_error < total_image_error:
            if total_image_error < 1e9:
                print("Improved quality +%f%% (%f)" % (
                    (1 - new_total_image_error / total_image_error) * 100,
                    new_total_image_error))
            total_image_error = new_total_image_error
            palettes_rgb = new_palettes_rgb
        else:
            cluster_palette._palettes_cam = old_palettes_cam
            cluster_palette._palettes_rgb = old_palettes_rgb
            cluster_palette._best_palette_distances = old_best_palette_distances
            continue

        image_generation += 1

        for i in range(16):
            iigs_palette[i, :, :] = (
                np.round(image_py.linear_to_srgb(
                    palettes_rgb[i, :, :] * 255) / 255 * 15)).astype(np.uint8)
            screen.set_palette(i, iigs_palette[i, :, :])

        screen.set_pixels(output_4bit)
        output_rgb = np.empty((200, 320, 3), dtype=np.uint8)
        for i in range(200):
            screen.line_palette[i] = line_to_palette[i]
            output_rgb[i, :, :] = (
                    palettes_rgb[line_to_palette[i]][
                        output_4bit[i, :]] * 255).astype(np.uint8)
        output_srgb = image_py.linear_to_srgb(output_rgb).astype(np.uint8)

        # dither = dither_pattern.PATTERNS[args.dither]()
        # bitmap = dither_pyx.dither_image(
        #     screen, rgb, dither, args.lookahead, args.verbose, rgb_to_cam16)

        # Show output image by rendering in target palette
        # output_palette_name = args.show_palette or args.palette
        # output_palette = palette_py.PALETTES[output_palette_name]()
        # output_screen = screen_py.DHGRScreen(output_palette)
        # if output_palette_name == "ntsc":
        #     output_srgb = output_screen.bitmap_to_image_ntsc(bitmap)
        # else:
        #     output_srgb = image_py.linear_to_srgb(
        #         output_screen.bitmap_to_image_rgb(bitmap)).astype(np.uint8)
        out_image = image_py.resize(
            Image.fromarray(output_srgb), screen.X_RES * 2, screen.Y_RES * 2,
            srgb_output=True)

        if args.show_output:
            surface = pygame.surfarray.make_surface(np.asarray(
                out_image).transpose((1, 0, 2)))
            canvas.blit(surface, (0, 0))
            pygame.display.flip()

    unique_colours = np.unique(iigs_palette.reshape(-1, 3), axis=0).shape[0]
    print("%d unique colours" % unique_colours)

    # Save Double hi-res image
    outfile = os.path.join(os.path.splitext(args.output)[0] + "-preview.png")
    out_image.save(outfile, "PNG")
    screen.pack()
    # with open(args.output, "wb") as f:
    #     f.write(bytes(screen.aux))
    #     f.write(bytes(screen.main))
    with open(args.output, "wb") as f:
        f.write(bytes(screen.memory))


if __name__ == "__main__":
    main()