compress.py
3.17 KB
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## -*- coding: utf-8 -*-
from numpy import array
# from pylab import *
# The standard quantisation tables for JPEG::
orig_table0 = array(
[[16, 11, 10, 16, 24, 40, 51, 61],
[12, 12, 14, 19, 26, 58, 60, 55],
[14, 13, 16, 24, 40, 57, 69, 56],
[14, 17, 22, 29, 51, 87, 80, 62],
[18, 22, 37, 56, 68, 109, 103, 77],
[24, 35, 55, 64, 81, 104, 113, 92],
[49, 64, 78, 87, 103, 121, 120, 101],
[72, 92, 95, 98, 112, 100, 103, 99]])
orig_table1 = array(
[[17, 18, 24, 47, 99, 99, 99, 99],
[18, 21, 26, 66, 99, 99, 99, 99],
[24, 26, 56, 99, 99, 99, 99, 99],
[47, 66, 99, 99, 99, 99, 99, 99],
[99, 99, 99, 99, 99, 99, 99, 99],
[99, 99, 99, 99, 99, 99, 99, 99],
[99, 99, 99, 99, 99, 99, 99, 99],
[99, 99, 99, 99, 99, 99, 99, 99]])
bi_hash = [
1020, 1015, 932, 848, 780, 735, 702, 679, 660, 645,
632, 623, 613, 607, 600, 594, 589, 585, 581, 571,
555, 542, 529, 514, 494, 474, 457, 439, 424, 410,
397, 386, 373, 364, 351, 341, 334, 324, 317, 309,
299, 294, 287, 279, 274, 267, 262, 257, 251, 247,
243, 237, 232, 227, 222, 217, 213, 207, 202, 198,
192, 188, 183, 177, 173, 168, 163, 157, 153, 148,
143, 139, 132, 128, 125, 119, 115, 108, 104, 99,
94, 90, 84, 79, 74, 70, 64, 59, 55, 49,
45, 40, 34, 30, 25, 20, 15, 11, 6, 4,
0
]
bi_sum = [
32640, 32635, 32266, 31495, 30665, 29804, 29146, 28599, 28104,
27670, 27225, 26725, 26210, 25716, 25240, 24789, 24373, 23946,
23572, 22846, 21801, 20842, 19949, 19121, 18386, 17651, 16998,
16349, 15800, 15247, 14783, 14321, 13859, 13535, 13081, 12702,
12423, 12056, 11779, 11513, 11135, 10955, 10676, 10392, 10208,
9928, 9747, 9564, 9369, 9193, 9017, 8822, 8639, 8458,
8270, 8084, 7896, 7710, 7527, 7347, 7156, 6977, 6788,
6607, 6422, 6236, 6054, 5867, 5684, 5495, 5305, 5128,
4945, 4751, 4638, 4442, 4248, 4065, 3888, 3698, 3509,
3326, 3139, 2957, 2775, 2586, 2405, 2216, 2037, 1846,
1666, 1483, 1297, 1109, 927, 735, 554, 375, 201,
128, 0
]
single_hash = [
510, 505, 422, 380, 355, 338, 326, 318, 311, 305,
300, 297, 293, 291, 288, 286, 284, 283, 281, 280,
279, 278, 277, 273, 262, 251, 243, 233, 225, 218,
211, 205, 198, 193, 186, 181, 177, 172, 168, 164,
158, 156, 152, 148, 145, 142, 139, 136, 133, 131,
129, 126, 123, 120, 118, 115, 113, 110, 107, 105,
102, 100, 97, 94, 92, 89, 87, 83, 81, 79,
76, 74, 70, 68, 66, 63, 61, 57, 55, 52,
50, 48, 44, 42, 39, 37, 34, 31, 29, 26,
24, 21, 18, 16, 13, 11, 8, 6, 3, 2,
0
]
single_sum = [
16320, 16315, 15946, 15277, 14655, 14073, 13623, 13230, 12859,
12560, 12240, 11861, 11456, 11081, 10714, 10360, 10027, 9679,
9368, 9056, 8680, 8331, 7995, 7668, 7376, 7084, 6823,
6562, 6345, 6125, 5939, 5756, 5571, 5421, 5240, 5086,
4976, 4829, 4719, 4616, 4463, 4393, 4280, 4166, 4092,
3980, 3909, 3835, 3755, 3688, 3621, 3541, 3467, 3396,
3323, 3247, 3170, 3096, 3021, 2952, 2874, 2804, 2727,
2657, 2583, 2509, 2437, 2362, 2290, 2211, 2136, 2068,
1996, 1915, 1858, 1773, 1692, 1620, 1552, 1477, 1398,
1326, 1251, 1179, 1109, 1031, 961, 884, 814, 736,
667, 592, 518, 441, 369, 292, 221, 151, 86,
64, 0
]