diff --git a/convert.py b/convert.py index d18842f..188a247 100644 --- a/convert.py +++ b/convert.py @@ -11,6 +11,8 @@ import colour from PIL import Image import numpy as np from pyclustering.cluster.kmedians import kmedians +from pyclustering.cluster.kmeans import kmeans +from pyclustering.utils.metric import distance_metric, type_metric from pyclustering.cluster.center_initializer import kmeans_plusplus_initializer import dither as dither_pyx @@ -25,7 +27,7 @@ import screen as screen_py # - support HGR def cluster_palette(image: Image): - line_to_palette = {} + # line_to_palette = {} # shuffle_lines = liprint(st(range(200)) # random.shuffle(shuffle_lines) @@ -40,13 +42,13 @@ def cluster_palette(image: Image): # else: # line_to_palette[line] = np.clip(int(line / (200 / 16)) + 2, 0, 15) - for line in range(200): - if line % 3 == 0: - line_to_palette[line] = int(line / (200 / 16)) - elif line % 3 == 1: - line_to_palette[line] = np.clip(int(line / (200 / 16)) + 1, 0, 15) - else: - line_to_palette[line] = np.clip(int(line / (200 / 16)) + 2, 0, 15) + # for line in range(200): + # if line % 3 == 0: + # line_to_palette[line] = int(line / (200 / 16)) + # elif line % 3 == 1: + # line_to_palette[line] = np.clip(int(line / (200 / 16)) + 1, 0, 15) + # else: + # line_to_palette[line] = np.clip(int(line / (200 / 16)) + 2, 0, 15) colours_rgb = np.asarray(image).reshape((-1, 3)) with colour.utilities.suppress_warnings(colour_usage_warnings=True): @@ -55,6 +57,7 @@ def cluster_palette(image: Image): palettes_rgb = np.empty((16, 16, 3), dtype=np.float32) palettes_cam = np.empty((16, 16, 3), dtype=np.float32) for palette_idx in range(16): + print("Fitting palette %d" % palette_idx) p_lower = max(palette_idx - 2, 0) p_upper = min(palette_idx + 2, 16) palette_pixels = colours_cam[ @@ -71,12 +74,23 @@ def cluster_palette(image: Image): # 16, palette_pixels, fixed_centroids=fixed_centroids, # tolerance=1e-6) - initial_centers = kmeans_plusplus_initializer( - palette_pixels, 16).initialize() - kmedians_instance = kmedians(palette_pixels, initial_centers) - kmedians_instance.process() + best_wce = 1e9 + best_medians = None + for i in range(500): + # print(i) + initial_centers = kmeans_plusplus_initializer( + palette_pixels, 16).initialize() + kmedians_instance = kmedians( + palette_pixels, initial_centers, tolerance=0.1, itermax=100, + metric=distance_metric(type_metric.MANHATTAN)) + kmedians_instance.process() + if kmedians_instance.get_total_wce() < best_wce: + best_wce = kmedians_instance.get_total_wce() + print(i, best_wce) + best_medians = kmedians_instance + print("Best %f" % best_wce) palettes_cam[palette_idx, :, :] = np.array( - kmedians_instance.get_medians()).astype(np.float32) + best_medians.get_medians()).astype(np.float32) # palette_colours = collections.defaultdict(list) # for line in range(200): @@ -122,7 +136,7 @@ def cluster_palette(image: Image): # line_pixels, palettes_cam, best_palette) # line_to_palette[line] = best_palette # print(line, line_to_palette[line]) - return palettes_cam, palettes_rgb, line_to_palette + return palettes_cam, palettes_rgb def main(): @@ -185,7 +199,7 @@ def main(): gamma=args.gamma_correct, srgb_output=True)).astype( np.float32) / 255 - palettes_cam, palettes_rgb, line_to_palette = cluster_palette(rgb) + palettes_cam, palettes_rgb = cluster_palette(rgb) # print(palette_rgb) # screen.set_palette(0, (image_py.linear_to_srgb_array(palette_rgb) * # 15).astype(np.uint8)) @@ -193,36 +207,37 @@ def main(): screen.set_palette(i, (np.round(palettes_rgb[i, :, :] * 15)).astype( np.uint8)) - output_4bit, line_to_palette = dither_pyx.dither_shr( - rgb, palettes_cam, palettes_rgb, rgb_to_cam16) - screen.set_pixels(output_4bit) - output_rgb = np.zeros((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) + for penalty in [1,2,3,4,5,6,7,8,9,10,1e9]: + output_4bit, line_to_palette = dither_pyx.dither_shr( + rgb, palettes_cam, palettes_rgb, rgb_to_cam16, float(penalty)) + screen.set_pixels(output_4bit) + output_rgb = np.zeros((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) + # 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, screen.Y_RES, - srgb_output=False) # XXX true + # 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, screen.Y_RES, + srgb_output=False) # XXX true - if args.show_output: - out_image.show() + if args.show_output: + out_image.show() # Save Double hi-res image outfile = os.path.join(os.path.splitext(args.output)[0] + "-preview.png") diff --git a/dither.pyx b/dither.pyx index 2506115..cea6a28 100644 --- a/dither.pyx +++ b/dither.pyx @@ -339,7 +339,7 @@ import colour @cython.boundscheck(False) @cython.wraparound(False) -def dither_shr(float[:, :, ::1] working_image, float[:, :, ::1] palettes_cam, float[:, :, ::1] palettes_rgb, float[:,::1] rgb_to_cam16ucs): +def dither_shr(float[:, :, ::1] working_image, float[:, :, ::1] palettes_cam, float[:, :, ::1] palettes_rgb, float[:,::1] rgb_to_cam16ucs, float penalty): cdef int y, x, idx, best_colour_idx, best_palette cdef float best_distance, distance cdef float[::1] best_colour_rgb, pixel_cam, colour_rgb, colour_cam @@ -354,13 +354,13 @@ def dither_shr(float[:, :, ::1] working_image, float[:, :, ::1] palettes_cam, fl cdef int[::1] line_to_palette = np.zeros(200, dtype=np.int32) best_palette = 15 for y in range(200): - print(y) + # print(y) for x in range(320): colour_cam = convert_rgb_to_cam16ucs( rgb_to_cam16ucs, working_image[y,x,0], working_image[y,x,1], working_image[y,x,2]) line_cam[x, :] = colour_cam - best_palette = best_palette_for_line(line_cam, palettes_cam, (y * 16 / 200), best_palette) + best_palette = best_palette_for_line(line_cam, palettes_cam, (y * 16 / 200), best_palette, penalty) # print("-->", best_palette) palette_rgb = palettes_rgb[best_palette, :, :] line_to_palette[y] = best_palette @@ -509,7 +509,7 @@ def k_means_with_fixed_centroids( @cython.boundscheck(False) @cython.wraparound(False) -cdef int best_palette_for_line(float [:, ::1] line_cam, float[:, :, ::1] palettes_cam, int base_palette_idx, int last_palette_idx) nogil: +cdef int best_palette_for_line(float [:, ::1] line_cam, float[:, :, ::1] palettes_cam, int base_palette_idx, int last_palette_idx, float last_penalty) nogil: cdef int palette_idx, best_palette_idx, palette_entry_idx, pixel_idx cdef float best_total_dist, total_dist, best_pixel_dist, pixel_dist cdef float[:, ::1] palette_cam @@ -517,20 +517,23 @@ cdef int best_palette_for_line(float [:, ::1] line_cam, float[:, :, ::1] palette best_total_dist = 1e9 best_palette_idx = -1 + cdef float penalty cdef int line_size = line_cam.shape[0] for palette_idx in range(16): palette_cam = palettes_cam[palette_idx, :, :] if palette_idx < (base_palette_idx - 1) or palette_idx > (base_palette_idx + 1): continue if palette_idx == last_palette_idx: - continue + penalty = last_penalty + else: + penalty = 1.0 total_dist = 0 best_pixel_dist = 1e9 for pixel_idx in range(line_size): pixel_cam = line_cam[pixel_idx] for palette_entry_idx in range(16): palette_entry = palette_cam[palette_entry_idx, :] - pixel_dist = colour_distance_squared(pixel_cam, palette_entry) + pixel_dist = colour_distance_squared(pixel_cam, palette_entry) * penalty if pixel_dist < best_pixel_dist: best_pixel_dist = pixel_dist total_dist += best_pixel_dist