forked from josch/img2pdf
307 lines
9.6 KiB
Python
307 lines
9.6 KiB
Python
|
#!/usr/bin/env python3
|
||
|
|
|
||
|
|
import sys
|
||
|
|
import numpy
|
||
|
|
import scipy.signal
|
||
|
|
import zlib
|
||
|
|
import struct
|
||
|
|
|
||
|
|
|
||
|
|
def find_closest_palette_color(color, palette):
|
||
|
|
if color.ndim == 0:
|
||
|
|
idx = (numpy.abs(palette - color)).argmin()
|
||
|
|
else:
|
||
|
|
# naive distance function by computing the euclidean distance in RGB space
|
||
|
|
idx = ((palette - color) ** 2).sum(axis=-1).argmin()
|
||
|
|
return palette[idx]
|
||
|
|
|
||
|
|
|
||
|
|
def floyd_steinberg(img, palette):
|
||
|
|
for y in range(img.shape[0]):
|
||
|
|
for x in range(img.shape[1]):
|
||
|
|
oldpixel = img[y, x]
|
||
|
|
newpixel = find_closest_palette_color(oldpixel, palette)
|
||
|
|
quant_error = oldpixel - newpixel
|
||
|
|
img[y, x] = newpixel
|
||
|
|
if x + 1 < img.shape[1]:
|
||
|
|
img[y, x + 1] += quant_error * 7 / 16
|
||
|
|
if y + 1 < img.shape[0]:
|
||
|
|
img[y + 1, x - 1] += quant_error * 3 / 16
|
||
|
|
img[y + 1, x] += quant_error * 5 / 16
|
||
|
|
if x + 1 < img.shape[1] and y + 1 < img.shape[0]:
|
||
|
|
img[y + 1, x + 1] += quant_error * 1 / 16
|
||
|
|
return img
|
||
|
|
|
||
|
|
|
||
|
|
def convolve_rgba(img, kernel):
|
||
|
|
return numpy.stack(
|
||
|
|
(
|
||
|
|
scipy.signal.convolve2d(img[:, :, 0], kernel, "same"),
|
||
|
|
scipy.signal.convolve2d(img[:, :, 1], kernel, "same"),
|
||
|
|
scipy.signal.convolve2d(img[:, :, 2], kernel, "same"),
|
||
|
|
scipy.signal.convolve2d(img[:, :, 3], kernel, "same"),
|
||
|
|
),
|
||
|
|
axis=-1,
|
||
|
|
)
|
||
|
|
|
||
|
|
|
||
|
|
def rgb2gray(img):
|
||
|
|
result = numpy.zeros((60, 60), dtype=numpy.dtype("int64"))
|
||
|
|
for y in range(img.shape[0]):
|
||
|
|
for x in range(img.shape[1]):
|
||
|
|
clin = sum(img[y, x] * [0.2126, 0.7152, 0.0722]) / 0xFFFF
|
||
|
|
if clin <= 0.0031308:
|
||
|
|
csrgb = 12.92 * clin
|
||
|
|
else:
|
||
|
|
csrgb = 1.055 * clin ** (1 / 2.4) - 0.055
|
||
|
|
result[y, x] = csrgb * 0xFFFF
|
||
|
|
return result
|
||
|
|
|
||
|
|
|
||
|
|
def palettize(img, pal):
|
||
|
|
result = numpy.zeros((img.shape[0], img.shape[1]), dtype=numpy.dtype("int64"))
|
||
|
|
for y in range(img.shape[0]):
|
||
|
|
for x in range(img.shape[1]):
|
||
|
|
for i, col in enumerate(pal):
|
||
|
|
if numpy.array_equal(img[y, x], col):
|
||
|
|
result[y, x] = i
|
||
|
|
break
|
||
|
|
else:
|
||
|
|
raise Exception()
|
||
|
|
return result
|
||
|
|
|
||
|
|
|
||
|
|
def write_png(data, path, bitdepth, colortype, palette=None):
|
||
|
|
with open(path, "wb") as f:
|
||
|
|
f.write(b"\x89PNG\r\n\x1A\n")
|
||
|
|
# PNG image type Colour type Allowed bit depths
|
||
|
|
# Greyscale 0 1, 2, 4, 8, 16
|
||
|
|
# Truecolour 2 8, 16
|
||
|
|
# Indexed-colour 3 1, 2, 4, 8
|
||
|
|
# Greyscale with alpha 4 8, 16
|
||
|
|
# Truecolour with alpha 6 8, 16
|
||
|
|
block = b"IHDR" + struct.pack(
|
||
|
|
">IIBBBBB",
|
||
|
|
data.shape[1], # width
|
||
|
|
data.shape[0], # height
|
||
|
|
bitdepth, # bitdepth
|
||
|
|
colortype, # colortype
|
||
|
|
0, # compression
|
||
|
|
0, # filtertype
|
||
|
|
0, # interlaced
|
||
|
|
)
|
||
|
|
f.write(
|
||
|
|
struct.pack(">I", len(block) - 4)
|
||
|
|
+ block
|
||
|
|
+ struct.pack(">I", zlib.crc32(block))
|
||
|
|
)
|
||
|
|
if palette is not None:
|
||
|
|
block = b"PLTE"
|
||
|
|
for col in palette:
|
||
|
|
block += struct.pack(">BBB", col[0], col[1], col[2])
|
||
|
|
f.write(
|
||
|
|
struct.pack(">I", len(block) - 4)
|
||
|
|
+ block
|
||
|
|
+ struct.pack(">I", zlib.crc32(block))
|
||
|
|
)
|
||
|
|
raw = b""
|
||
|
|
for y in range(data.shape[0]):
|
||
|
|
raw += b"\0"
|
||
|
|
if bitdepth == 16:
|
||
|
|
raw += data[y].astype(">u2").tobytes()
|
||
|
|
elif bitdepth == 8:
|
||
|
|
raw += data[y].astype(">u1").tobytes()
|
||
|
|
elif bitdepth in [4, 2, 1]:
|
||
|
|
valsperbyte = 8 // bitdepth
|
||
|
|
for x in range(0, data.shape[1], valsperbyte):
|
||
|
|
val = 0
|
||
|
|
for j in range(valsperbyte):
|
||
|
|
if x + j >= data.shape[1]:
|
||
|
|
break
|
||
|
|
val |= (data[y, x + j].astype(">u2") & (2 ** bitdepth - 1)) << (
|
||
|
|
(valsperbyte - j - 1) * bitdepth
|
||
|
|
)
|
||
|
|
raw += struct.pack(">B", val)
|
||
|
|
else:
|
||
|
|
raise Exception()
|
||
|
|
compressed = zlib.compress(raw)
|
||
|
|
block = b"IDAT" + compressed
|
||
|
|
f.write(
|
||
|
|
struct.pack(">I", len(compressed))
|
||
|
|
+ block
|
||
|
|
+ struct.pack(">I", zlib.crc32(block))
|
||
|
|
)
|
||
|
|
block = b"IEND"
|
||
|
|
f.write(struct.pack(">I", 0) + block + struct.pack(">I", zlib.crc32(block)))
|
||
|
|
|
||
|
|
|
||
|
|
def main():
|
||
|
|
outdir = sys.argv[1]
|
||
|
|
|
||
|
|
# create a 256 color palette by first writing 16 shades of gray
|
||
|
|
# and then writing an array of RGB colors with 6, 8 and 5 levels
|
||
|
|
# for red, green and blue, respectively
|
||
|
|
pal8 = numpy.zeros((256, 3), dtype=numpy.dtype("int64"))
|
||
|
|
i = 0
|
||
|
|
for gray in range(15, 255, 15):
|
||
|
|
pal8[i] = [gray, gray, gray]
|
||
|
|
i += 1
|
||
|
|
for red in 0, 0x33, 0x66, 0x99, 0xCC, 0xFF:
|
||
|
|
for green in 0, 0x24, 0x49, 0x6D, 0x92, 0xB6, 0xDB, 0xFF:
|
||
|
|
for blue in 0, 0x40, 0x80, 0xBF, 0xFF:
|
||
|
|
pal8[i] = [red, green, blue]
|
||
|
|
i += 1
|
||
|
|
assert i == 256
|
||
|
|
|
||
|
|
# windows 16 color palette
|
||
|
|
pal4 = numpy.array(
|
||
|
|
[
|
||
|
|
[0x00, 0x00, 0x00],
|
||
|
|
[0x80, 0x00, 0x00],
|
||
|
|
[0x00, 0x80, 0x00],
|
||
|
|
[0x80, 0x80, 0x00],
|
||
|
|
[0x00, 0x00, 0x80],
|
||
|
|
[0x80, 0x00, 0x80],
|
||
|
|
[0x00, 0x80, 0x80],
|
||
|
|
[0xC0, 0xC0, 0xC0],
|
||
|
|
[0x80, 0x80, 0x80],
|
||
|
|
[0xFF, 0x00, 0x00],
|
||
|
|
[0x00, 0xFF, 0x00],
|
||
|
|
[0xFF, 0x00, 0x00],
|
||
|
|
[0x00, 0xFF, 0x00],
|
||
|
|
[0xFF, 0x00, 0xFF],
|
||
|
|
[0x00, 0xFF, 0x00],
|
||
|
|
[0xFF, 0xFF, 0xFF],
|
||
|
|
],
|
||
|
|
dtype=numpy.dtype("int64"),
|
||
|
|
)
|
||
|
|
|
||
|
|
# choose values slightly off red, lime and blue because otherwise
|
||
|
|
# imagemagick will classify the image as Depth: 8/1-bit
|
||
|
|
pal2 = numpy.array(
|
||
|
|
[[0, 0, 0], [0xFE, 0, 0], [0, 0xFE, 0], [0, 0, 0xFE]],
|
||
|
|
dtype=numpy.dtype("int64"),
|
||
|
|
)
|
||
|
|
|
||
|
|
# don't choose black and white or otherwise imagemagick will classify the
|
||
|
|
# image as bilevel with 8/1-bit depth instead of palette with 8-bit color
|
||
|
|
# don't choose gray colors or otherwise imagemagick will classify the
|
||
|
|
# image as grayscale
|
||
|
|
pal1 = numpy.array(
|
||
|
|
[[0x01, 0x02, 0x03], [0xFE, 0xFD, 0xFC]], dtype=numpy.dtype("int64")
|
||
|
|
)
|
||
|
|
|
||
|
|
# gaussian kernel with sigma=3
|
||
|
|
kernel = numpy.array(
|
||
|
|
[
|
||
|
|
[0.011362, 0.014962, 0.017649, 0.018648, 0.017649, 0.014962, 0.011362],
|
||
|
|
[0.014962, 0.019703, 0.02324, 0.024556, 0.02324, 0.019703, 0.014962],
|
||
|
|
[0.017649, 0.02324, 0.027413, 0.028964, 0.027413, 0.02324, 0.017649],
|
||
|
|
[0.018648, 0.024556, 0.028964, 0.030603, 0.028964, 0.024556, 0.018648],
|
||
|
|
[0.017649, 0.02324, 0.027413, 0.028964, 0.027413, 0.02324, 0.017649],
|
||
|
|
[0.014962, 0.019703, 0.02324, 0.024556, 0.02324, 0.019703, 0.014962],
|
||
|
|
[0.011362, 0.014962, 0.017649, 0.018648, 0.017649, 0.014962, 0.011362],
|
||
|
|
],
|
||
|
|
numpy.float,
|
||
|
|
)
|
||
|
|
|
||
|
|
# constructs a 2D array of a circle with a width of 36
|
||
|
|
circle = list()
|
||
|
|
offsets_36 = [14, 11, 9, 7, 6, 5, 4, 3, 3, 2, 2, 1, 1, 1, 0, 0, 0, 0]
|
||
|
|
for offs in offsets_36 + offsets_36[::-1]:
|
||
|
|
circle.append([0] * offs + [1] * (len(offsets_36) - offs) * 2 + [0] * offs)
|
||
|
|
|
||
|
|
alpha = numpy.zeros((60, 60, 4), dtype=numpy.dtype("int64"))
|
||
|
|
|
||
|
|
# draw three circles
|
||
|
|
for (xpos, ypos, color) in [
|
||
|
|
(12, 3, [0xFFFF, 0, 0, 0xFFFF]),
|
||
|
|
(21, 21, [0, 0xFFFF, 0, 0xFFFF]),
|
||
|
|
(3, 21, [0, 0, 0xFFFF, 0xFFFF]),
|
||
|
|
]:
|
||
|
|
for x, row in enumerate(circle):
|
||
|
|
for y, pos in enumerate(row):
|
||
|
|
if pos:
|
||
|
|
alpha[y + ypos, x + xpos] += color
|
||
|
|
alpha = numpy.clip(alpha, 0, 0xFFFF)
|
||
|
|
alpha = convolve_rgba(alpha, kernel)
|
||
|
|
|
||
|
|
write_png(alpha, outdir + "/alpha.png", 16, 6)
|
||
|
|
|
||
|
|
normal16 = alpha[:, :, 0:3]
|
||
|
|
write_png(normal16, outdir + "/normal16.png", 16, 2)
|
||
|
|
|
||
|
|
write_png(normal16 / 0xFFFF * 0xFF, outdir + "/normal.png", 8, 2)
|
||
|
|
|
||
|
|
write_png(0xFF - normal16 / 0xFFFF * 0xFF, outdir + "/inverse.png", 8, 2)
|
||
|
|
|
||
|
|
gray16 = rgb2gray(normal16)
|
||
|
|
|
||
|
|
write_png(gray16, outdir + "/gray16.png", 16, 0)
|
||
|
|
|
||
|
|
write_png(gray16 / 0xFFFF * 0xFF, outdir + "/gray8.png", 8, 0)
|
||
|
|
|
||
|
|
write_png(
|
||
|
|
floyd_steinberg(gray16, numpy.arange(16) / 0xF * 0xFFFF) / 0xFFFF * 0xF,
|
||
|
|
outdir + "/gray4.png",
|
||
|
|
4,
|
||
|
|
0,
|
||
|
|
)
|
||
|
|
|
||
|
|
write_png(
|
||
|
|
floyd_steinberg(gray16, numpy.arange(4) / 0x3 * 0xFFFF) / 0xFFFF * 0x3,
|
||
|
|
outdir + "/gray2.png",
|
||
|
|
2,
|
||
|
|
0,
|
||
|
|
)
|
||
|
|
|
||
|
|
write_png(
|
||
|
|
floyd_steinberg(gray16, numpy.arange(2) / 0x1 * 0xFFFF) / 0xFFFF * 0x1,
|
||
|
|
outdir + "/gray1.png",
|
||
|
|
1,
|
||
|
|
0,
|
||
|
|
)
|
||
|
|
|
||
|
|
write_png(
|
||
|
|
palettize(
|
||
|
|
floyd_steinberg(normal16, pal8 * 0xFFFF / 0xFF) / 0xFFFF * 0xFF, pal8
|
||
|
|
),
|
||
|
|
outdir + "/palette8.png",
|
||
|
|
8,
|
||
|
|
3,
|
||
|
|
pal8,
|
||
|
|
)
|
||
|
|
|
||
|
|
write_png(
|
||
|
|
palettize(
|
||
|
|
floyd_steinberg(normal16, pal4 * 0xFFFF / 0xFF) / 0xFFFF * 0xFF, pal4
|
||
|
|
),
|
||
|
|
outdir + "/palette4.png",
|
||
|
|
4,
|
||
|
|
3,
|
||
|
|
pal4,
|
||
|
|
)
|
||
|
|
|
||
|
|
write_png(
|
||
|
|
palettize(
|
||
|
|
floyd_steinberg(normal16, pal2 * 0xFFFF / 0xFF) / 0xFFFF * 0xFF, pal2
|
||
|
|
),
|
||
|
|
outdir + "/palette2.png",
|
||
|
|
2,
|
||
|
|
3,
|
||
|
|
pal2,
|
||
|
|
)
|
||
|
|
|
||
|
|
write_png(
|
||
|
|
palettize(
|
||
|
|
floyd_steinberg(normal16, pal1 * 0xFFFF / 0xFF) / 0xFFFF * 0xFF, pal1
|
||
|
|
),
|
||
|
|
outdir + "/palette1.png",
|
||
|
|
1,
|
||
|
|
3,
|
||
|
|
pal1,
|
||
|
|
)
|
||
|
|
|
||
|
|
|
||
|
|
main()
|