ii-pix/dither.pyx
2021-03-15 15:10:33 +00:00

269 lines
10 KiB
Cython

# cython: infer_types=True
# cython: profile=True
cimport cython
import functools
import numpy as np
# cimport numpy as np
from cython.view cimport array as cvarray
from libc.stdlib cimport malloc, free
# TODO: use a cdef class
cdef struct Dither:
float* pattern # Flattened dither pattern
int x_shape
int y_shape
int x_origin
int y_origin
cdef struct Image:
float* flat # Flattened image array
int shape0
int shape1
int shape2
cdef float clip(float a, float min_value, float max_value) nogil:
return min(max(a, min_value), max_value)
cdef int dither_bounds_xl(Dither *dither, int x) nogil:
cdef int el = max(dither.x_origin - x, 0)
cdef int xl = x - dither.x_origin + el
return xl
cdef int dither_bounds_xr(Dither *dither, int x_res, int x) nogil:
cdef int er = min(dither.x_shape, x_res - x)
cdef int xr = x - dither.x_origin + er
return xr
cdef int dither_bounds_yt(Dither *dither, int y) nogil:
cdef int et = max(dither.y_origin - y, 0)
cdef int yt = y - dither.y_origin + et
return yt
cdef int dither_bounds_yb(Dither *dither, int y_res, int y) nogil:
cdef int eb = min(dither.y_shape, y_res - y)
cdef int yb = y - dither.y_origin + eb
return yb
@cython.boundscheck(False)
@cython.wraparound(False)
@functools.lru_cache(None)
def lookahead_options(screen, lookahead, last_pixel_4bit, x):
options_4bit = np.empty((2 ** lookahead, lookahead), dtype=np.uint8)
options_rgb = np.empty((2 ** lookahead, lookahead, 3), dtype=np.float32)
for i in range(2 ** lookahead):
output_pixel_nbit = last_pixel_nbit
for j in range(lookahead):
xx = x + j
palette_choices_4bit, palette_choices_rgb = \
screen.pixel_palette_options(output_pixel_4bit, xx)
output_pixel_4bit = palette_choices_4bit[(i & (1 << j)) >> j]
output_pixel_rgb = np.array(
palette_choices_rgb[(i & (1 << j)) >> j])
options_4bit[i, j] = output_pixel_4bit
options_rgb[i, j, :] = output_pixel_rgb
return options_nbit, options_rgb
@cython.boundscheck(False)
@cython.wraparound(False)
cdef int dither_lookahead(Dither* dither,
Image* image_rgb, int x, int y, unsigned char[:, ::1] options_4bit,
float[:, :, ::1] options_rgb, int lookahead, unsigned char[:, ::1] distances, int x_res):
cdef int xl = dither_bounds_xl(dither, x)
cdef int xr = dither_bounds_xr(dither, x_res, x)
# X coord value of larger of dither bounding box or lookahead horizon
cdef int xxr = min(max(x + lookahead, xr), x_res)
cdef int i, j, k, l
cdef int lah_shape0 = 2 ** lookahead
cdef int lah_shape1 = lookahead + xr - xl
cdef int lah_shape2 = 3
cdef float *lah_image_rgb = <float *> malloc(lah_shape0 * lah_shape1 * lah_shape2 * sizeof(float))
for i in range(2**lookahead):
# Copies of input pixels so we can dither in bulk
for j in range(xxr - x):
for k in range(3):
lah_image_rgb[i * lah_shape1 * lah_shape2 + j * lah_shape2 + k] = image_rgb.flat[
y * image_rgb.shape1 * image_rgb.shape2 + (x+j) * image_rgb.shape2 + k]
# Leave enough space at right of image so we can dither the last of our lookahead pixels.
for j in range(xxr - x, lookahead + xr - xl):
for k in range(3):
lah_image_rgb[i * lah_shape1 * lah_shape2 + j * lah_shape2 + k] = 0
cdef float[3] quant_error
for i in range(2 ** lookahead):
for j in range(xxr - x):
xl = dither_bounds_xl(dither, j)
xr = dither_bounds_xr(dither, x_res - x, j)
# Don't update the input at position x (since we've already chosen
# fixed outputs), but do propagate quantization errors to positions >x
# so we can compensate for how good/bad these choices were
# options_rgb choices are fixed, but we can still distribute
# quantization error from having made these choices, in order to compute
# the total error
for k in range(3):
quant_error[k] = lah_image_rgb[i * lah_shape1 * lah_shape2 + j * lah_shape2 + k] - options_rgb[i, j, k]
apply_one_line(dither, xl, xr, j, &lah_image_rgb[i * lah_shape1 * lah_shape2], lah_shape2, quant_error)
cdef unsigned char bit4
cdef int best
cdef int best_error = 2**31-1
cdef int total_error
cdef long flat, dist
cdef long r, g, b
for i in range(2**lookahead):
total_error = 0
for j in range(lookahead):
# Clip lah_image_rgb into 0..255 range to prepare for computing colour distance
r = <long>lah_image_rgb[i * lah_shape1 * lah_shape2 + j * lah_shape2 + 0]
g = <long>lah_image_rgb[i * lah_shape1 * lah_shape2 + j * lah_shape2 + 1]
b = <long>lah_image_rgb[i * lah_shape1 * lah_shape2 + j * lah_shape2 + 2]
flat = (r << 16) + (g << 8) + b
bit4 = options_nbit[i, j]
dist = distances[flat, bit4]
total_error += dist ** 2
if total_error >= best_error:
break
if total_error < best_error:
best_error = total_error
best = i
free(lah_image_rgb)
return best
cdef void apply_one_line(Dither* dither, int xl, int xr, int x, float[] image, int image_shape1, float[] quant_error) nogil:
cdef int i, j
cdef float error
for i in range(xl, xr):
for j in range(3):
error = dither.pattern[i - x + dither.x_origin] * quant_error[j]
image[i * image_shape1 + j] = clip(image[i * image_shape1 + j] + error, 0, 255)
cdef void apply(Dither* dither, int x_res, int y_res, int x, int y, Image* image, float[] quant_error):
cdef int i, j, k
cdef int yt = dither_bounds_yt(dither, y)
cdef int yb = dither_bounds_yb(dither, y_res, y)
cdef int xl = dither_bounds_xl(dither, x)
cdef int xr = dither_bounds_xr(dither, x_res, x)
cdef float error
# We could avoid clipping here, i.e. allow RGB values to extend beyond
# 0..255 to capture a larger range of residual error. This is faster
# but seems to reduce image quality.
# TODO: is this still true?
for i in range(yt, yb):
for j in range(xl, xr):
for k in range(3):
error = dither.pattern[(i - y) * dither.x_shape + j - x + dither.x_origin] * quant_error[k]
image.flat[i * image.shape1 * image.shape2 + j * image.shape2 + k] = clip(
image.flat[i * image.shape1 * image.shape2 + j * image.shape2 + k] + error, 0, 255)
@cython.boundscheck(False)
@cython.wraparound(False)
def find_nearest_colour(float[::1] pixel_rgb, unsigned char[::1] options_4bit, unsigned char[:, ::1] options_rgb, unsigned char[:, ::1] distances):
cdef int best, dist
cdef unsigned char bit4
cdef int best_dist = 2**8
cdef long flat
for i in range(options_4bit.shape[0]):
flat = (<long>pixel_rgb[0] << 16) + (<long>pixel_rgb[1] << 8) + <long>pixel_rgb[2]
bit4 = options_nbit[i]
dist = distances[flat, bit4]
if dist < best_dist:
best_dist = dist
best = i
return options_nbit[best], options_rgb[best, :]
@cython.boundscheck(False)
@cython.wraparound(False)
def dither_image(screen, float[:, :, ::1] image_rgb, dither, int lookahead, unsigned char verbose):
cdef (unsigned char)[:, ::1] image_nbit = np.empty(
(image_rgb.shape[0], image_rgb.shape[1]), dtype=np.uint8)
cdef int yres = screen.Y_RES
cdef int xres = screen.X_RES
cdef int y, x, i
cdef float[3] quant_error
cdef (unsigned char)[:, ::1] options_nbit
cdef float[:, :, ::1] options_rgb
cdef unsigned char output_pixel_nbit
cdef float[3] input_pixel_rgb
# Flatten python image array for more efficient access
cdef Image cimage_rgb
cimage_rgb.flat = <float *> malloc(image_rgb.shape[0] * image_rgb.shape[1] * image_rgb.shape[2] * sizeof(float))
cimage_rgb.shape0 = image_rgb.shape[0]
cimage_rgb.shape1 = image_rgb.shape[1]
cimage_rgb.shape2 = image_rgb.shape[2]
for y in range(cimage_rgb.shape0):
for x in range(cimage_rgb.shape1):
for i in range(cimage_rgb.shape2):
cimage_rgb.flat[y * cimage_rgb.shape1 * cimage_rgb.shape2 + x * cimage_rgb.shape2 + i] = (
image_rgb[y, x, i])
# Flatten python dither pattern array for more efficient access
cdef Dither cdither
cdither.y_shape = dither.PATTERN.shape[0]
cdither.x_shape = dither.PATTERN.shape[1]
cdither.y_origin = dither.ORIGIN[0]
cdither.x_origin = dither.ORIGIN[1]
# Convert dither.PATTERN to a malloced array which is faster to access
cdither.pattern = <float *> malloc(cdither.x_shape * cdither.y_shape * sizeof(float))
for i in range(cdither.y_shape):
for j in range(cdither.x_shape):
cdither.pattern[i * cdither.x_shape + j] = dither.PATTERN[i, j, 0]
cdef (unsigned char)[:, ::1] distances = screen.palette.distances
for y in range(yres):
if verbose:
print("%d/%d" % (y, yres))
output_pixel_nbit = 0
for x in range(xres):
for i in range(3):
input_pixel_rgb[i] = cimage_rgb.flat[
y * cimage_rgb.shape1 * cimage_rgb.shape2 + x * cimage_rgb.shape2 + i]
if lookahead:
palette_choices_4bit, palette_choices_rgb = lookahead_options(
screen, lookahead, output_pixel_4bit, x % 4)
best_idx = dither_lookahead(
&cdither, &cimage_rgb, x, y, palette_choices_4bit, palette_choices_rgb, lookahead, distances, xres)
output_pixel_4bit = palette_choices_4bit[best_idx, 0]
output_pixel_rgb = palette_choices_rgb[best_idx, 0, :]
else:
palette_choices_4bit, palette_choices_rgb = screen.pixel_palette_options(output_pixel_4bit, x)
output_pixel_4bit, output_pixel_rgb = \
find_nearest_colour(input_pixel_rgb, palette_choices_4bit, palette_choices_rgb, distances)
for i in range(3):
quant_error[i] = input_pixel_rgb[i] - output_pixel_rgb[i]
image_4bit[y, x] = output_pixel_4bit
apply(&cdither, xres, yres, x, y, &cimage_rgb, quant_error)
for i in range(3):
image_rgb[y, x, i] = output_pixel_rgb[i]
free(cdither.pattern)
free(cimage_rgb.flat)
return image_nbit, np.array(image_rgb)