Chunk / JpegT

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Commit f4b5291c4ab2420e057808163367ddaf70743752

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1 parent f8dfbefc
Exists in master

Qaulity Calculatiing!

Showing 13 changed files with 457 additions and 166 deletions   Show diff stats
mjpeg/__init__.py
  Diff comments   View file @f4b5291
... ... @@ -2,7 +2,7 @@
2 2  
3 3 from libmjsteg import Jsteg
4 4  
5   -__all__ = ['Jpeg','colorMap','diffblock','diffblocks']
  5 +__all__ = ['Jpeg', 'colorMap', 'diffblock', 'diffblocks']
6 6  
7 7 # We need standard components from :mod:`numpy`, and some auxiliary
8 8 # functions from submodules.
... ... @@ -16,6 +16,7 @@ import pylab as plt
16 16  
17 17 import base
18 18 from dct import bdct, ibdct
  19 +from compress import *
19 20  
20 21 # The colour codes are defined in the JPEG standard. We store
21 22 # them here for easy reference by name::
... ... @@ -55,7 +56,7 @@ class Jpeg(Jsteg):
55 56 Jsteg.__init__(self, file, **kw)
56 57 self.verbosity = verbosity
57 58 if verbosity > 0:
58   - print "[Jpeg.__init__] Image size %ix%i" % (self.coef_arrays[0].shape)
  59 + print "[Jpeg.__init__] Image size %ix%i" % (self.image_width, self.image_height)
59 60 if key != None:
60 61 self.key = key
61 62 elif rndkey:
... ... @@ -290,6 +291,47 @@ class Jpeg(Jsteg):
290 291 self.coef_arrays[cID][v:v + 8, h:h + 8] = blocks[i, j]
291 292 self.Jsetblock(j, i, cID, bytearray(blocks[i, j].astype(np.int16)))
292 293  
  294 + def getSize(self):
  295 + return self.image_width, self.image_height
  296 +
  297 + def getQuality(self):
  298 + """
  299 + Qaulity rating algorithm from ImageMagick.
  300 +
  301 + e.g.
  302 + find ./ -name "*.jpg" | xargs -i sh -c "echo -n {} && identify -quiet -verbose {} |grep -E 'Quality' "
  303 +
  304 + Ref - http://stackoverflow.com/questions/2024947/is-it-possible-to-tell-the-quality-level-of-a-jpeg,http://www.imagemagick.org/discourse-server/viewtopic.php?f=1&t=20235
  305 + """
  306 + table0 = self.quant_tables[0].ravel()
  307 + table1 = self.quant_tables[1].ravel()
  308 + sum0 = np.sum(table0)
  309 + sum1 = np.sum(table1)
  310 + quality = None
  311 +
  312 + if sum0 != None:
  313 + if sum1 != None:
  314 + sum = sum0 + sum1
  315 + qvalue = table0[2] + table0[53] + table1[0] + table1[-1]
  316 + hashtable = bi_hash
  317 + sumtable = bi_sum
  318 + else:
  319 + sum = sum0
  320 + qvalue = table0[2] + table0[53]
  321 + hashtable = single_hash
  322 + sumtable = single_sum
  323 + else:
  324 + raise Exception("Quantization Tables Illegal")
  325 + return None
  326 +
  327 + for i in range(100):
  328 + if qvalue >= hashtable[i] or sum >= sumtable[i]:
  329 + break
  330 + quality = i + 1
  331 +
  332 + return quality
  333 +
  334 +
293 335 # Decompression
294 336 # -------------
295 337  
... ... @@ -404,3 +446,13 @@ def diffblocks(a, b):
404 446 cnt += 1
405 447 return diff, cnt
406 448  
  449 +
  450 +
  451 +
  452 +
  453 +
  454 +
  455 +
  456 +
  457 +
  458 +
... ...
mjpeg/__init__.pyc
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mjpeg/compress.py
  Diff comments   View file @f4b5291
... ... @@ -5,179 +5,94 @@ from pylab import *
5 5  
6 6 # The standard quantisation tables for JPEG::
7 7  
8   -table0 = array(
9   - [ [ 16, 11, 10, 16, 24, 40, 51, 61 ],
10   - [ 12, 12, 14, 19, 26, 58, 60, 55 ],
11   - [ 14, 13, 16, 24, 40, 57, 69, 56 ],
12   - [ 14, 17, 22, 29, 51, 87, 80, 62 ],
13   - [ 18, 22, 37, 56, 68, 109, 103, 77 ],
14   - [ 24, 35, 55, 64, 81, 104, 113, 92 ],
15   - [ 49, 64, 78, 87, 103, 121, 120, 101 ],
16   - [ 72, 92, 95, 98, 112, 100, 103, 99 ] ] )
  8 +orig_table0 = array(
  9 + [[16, 11, 10, 16, 24, 40, 51, 61],
  10 + [12, 12, 14, 19, 26, 58, 60, 55],
  11 + [14, 13, 16, 24, 40, 57, 69, 56],
  12 + [14, 17, 22, 29, 51, 87, 80, 62],
  13 + [18, 22, 37, 56, 68, 109, 103, 77],
  14 + [24, 35, 55, 64, 81, 104, 113, 92],
  15 + [49, 64, 78, 87, 103, 121, 120, 101],
  16 + [72, 92, 95, 98, 112, 100, 103, 99]])
  17 +
  18 +orig_table1 = array(
  19 + [[17, 18, 24, 47, 99, 99, 99, 99],
  20 + [18, 21, 26, 66, 99, 99, 99, 99],
  21 + [24, 26, 56, 99, 99, 99, 99, 99],
  22 + [47, 66, 99, 99, 99, 99, 99, 99],
  23 + [99, 99, 99, 99, 99, 99, 99, 99],
  24 + [99, 99, 99, 99, 99, 99, 99, 99],
  25 + [99, 99, 99, 99, 99, 99, 99, 99],
  26 + [99, 99, 99, 99, 99, 99, 99, 99]])
  27 +
  28 +bi_hash = [
  29 + 1020, 1015, 932, 848, 780, 735, 702, 679, 660, 645,
  30 + 632, 623, 613, 607, 600, 594, 589, 585, 581, 571,
  31 + 555, 542, 529, 514, 494, 474, 457, 439, 424, 410,
  32 + 397, 386, 373, 364, 351, 341, 334, 324, 317, 309,
  33 + 299, 294, 287, 279, 274, 267, 262, 257, 251, 247,
  34 + 243, 237, 232, 227, 222, 217, 213, 207, 202, 198,
  35 + 192, 188, 183, 177, 173, 168, 163, 157, 153, 148,
  36 + 143, 139, 132, 128, 125, 119, 115, 108, 104, 99,
  37 + 94, 90, 84, 79, 74, 70, 64, 59, 55, 49,
  38 + 45, 40, 34, 30, 25, 20, 15, 11, 6, 4,
  39 + 0
  40 +]
  41 +
  42 +bi_sum = [
  43 + 32640, 32635, 32266, 31495, 30665, 29804, 29146, 28599, 28104,
  44 + 27670, 27225, 26725, 26210, 25716, 25240, 24789, 24373, 23946,
  45 + 23572, 22846, 21801, 20842, 19949, 19121, 18386, 17651, 16998,
  46 + 16349, 15800, 15247, 14783, 14321, 13859, 13535, 13081, 12702,
  47 + 12423, 12056, 11779, 11513, 11135, 10955, 10676, 10392, 10208,
  48 + 9928, 9747, 9564, 9369, 9193, 9017, 8822, 8639, 8458,
  49 + 8270, 8084, 7896, 7710, 7527, 7347, 7156, 6977, 6788,
  50 + 6607, 6422, 6236, 6054, 5867, 5684, 5495, 5305, 5128,
  51 + 4945, 4751, 4638, 4442, 4248, 4065, 3888, 3698, 3509,
  52 + 3326, 3139, 2957, 2775, 2586, 2405, 2216, 2037, 1846,
  53 + 1666, 1483, 1297, 1109, 927, 735, 554, 375, 201,
  54 + 128, 0
  55 +]
  56 +
  57 +single_hash = [
  58 + 510, 505, 422, 380, 355, 338, 326, 318, 311, 305,
  59 + 300, 297, 293, 291, 288, 286, 284, 283, 281, 280,
  60 + 279, 278, 277, 273, 262, 251, 243, 233, 225, 218,
  61 + 211, 205, 198, 193, 186, 181, 177, 172, 168, 164,
  62 + 158, 156, 152, 148, 145, 142, 139, 136, 133, 131,
  63 + 129, 126, 123, 120, 118, 115, 113, 110, 107, 105,
  64 + 102, 100, 97, 94, 92, 89, 87, 83, 81, 79,
  65 + 76, 74, 70, 68, 66, 63, 61, 57, 55, 52,
  66 + 50, 48, 44, 42, 39, 37, 34, 31, 29, 26,
  67 + 24, 21, 18, 16, 13, 11, 8, 6, 3, 2,
  68 + 0
  69 +]
  70 +
  71 +single_sum = [
  72 + 16320, 16315, 15946, 15277, 14655, 14073, 13623, 13230, 12859,
  73 + 12560, 12240, 11861, 11456, 11081, 10714, 10360, 10027, 9679,
  74 + 9368, 9056, 8680, 8331, 7995, 7668, 7376, 7084, 6823,
  75 + 6562, 6345, 6125, 5939, 5756, 5571, 5421, 5240, 5086,
  76 + 4976, 4829, 4719, 4616, 4463, 4393, 4280, 4166, 4092,
  77 + 3980, 3909, 3835, 3755, 3688, 3621, 3541, 3467, 3396,
  78 + 3323, 3247, 3170, 3096, 3021, 2952, 2874, 2804, 2727,
  79 + 2657, 2583, 2509, 2437, 2362, 2290, 2211, 2136, 2068,
  80 + 1996, 1915, 1858, 1773, 1692, 1620, 1552, 1477, 1398,
  81 + 1326, 1251, 1179, 1109, 1031, 961, 884, 814, 736,
  82 + 667, 592, 518, 441, 369, 292, 221, 151, 86,
  83 + 64, 0
  84 +]
17 85  
18   -table1 = array(
19   - [ [ 17, 18, 24, 47, 99, 99, 99, 99 ],
20   - [ 18, 21, 26, 66, 99, 99, 99, 99 ],
21   - [ 24, 26, 56, 99, 99, 99, 99, 99 ],
22   - [ 47, 66, 99, 99, 99, 99, 99, 99 ],
23   - [ 99, 99, 99, 99, 99, 99, 99, 99 ],
24   - [ 99, 99, 99, 99, 99, 99, 99, 99 ],
25   - [ 99, 99, 99, 99, 99, 99, 99, 99 ],
26   - [ 99, 99, 99, 99, 99, 99, 99, 99 ] ] )
27 86  
28   -# The quantTable function seems straight forward,
29   -# but has not been tested.
30 87  
31   -def quantTable(quality=50,tnum=0,force_baseline=False):
32   - if quality <= 0: quality = 1
33   - elif quality > 100: quality = 100
34   - if quality < 50: quality = 5000 / quality
35   - else: quality = 200 - quality*2
36 88  
37   - t = floor( (t * quality + 50) /100 )
38 89  
39   - t[t<1] = 1
40 90  
41   - if (force_baseline): t[t>255] = 255
42   - else: t[t>32767] = 32767 # max quantizer needed for 12 bits
43 91  
44   - return t
45 92  
46   -# I don't think this works.
47 93  
48   -def bdctmtx(n=8):
49   - (c,r) = meshgrid(range(n), range(n))
50   - (c0,r0) = meshgrid(r.flatten());
51   - (c1,r1) = meshgrid(c.flatten());
52 94  
53   - x = sqrt(float(2) / n)
54   - x *= cos( pi * (2*c + 1) * r / (2 * n));
55   - x[1,:] = x[1,:] / sqrt(2);
56 95  
57   - return x[r0+c0*n+1] * x[r1+c1*n+1]
58 96  
59   -def im2vec(im,blksize=8,padsize=0):
60   - """Reshape 2D image blocks into an array of column vectors
61 97  
62   - V=im2vec(im,blksize=8,padsize=0)
63   -
64   - IM is an image to be separated into non-overlapping blocks and
65   - reshaped into an MxN array containing N blocks reshaped into Mx1
66   - column vectors. im2vec is designed to be the inverse of vec2im.
67   -
68   - BLKSIZE is a scalar or 1x2 vector indicating the size of the blocks.
69   -
70   - PADSIZE is a scalar or 1x2 vector indicating the amount of vertical
71   - and horizontal space to be skipped between blocks in the image.
72   - Default is [0 0]. If PADSIZE is a scalar, the same amount of space
73   - is used for both directions. PADSIZE must be non-negative (blocks
74   - must be non-overlapping).
75   -
76   - ROWS indicates the number of rows of blocks found in the image.
77   - COLS indicates the number of columns of blocks found in the image.
78   - """
79   -
80   - blksize=blksize + array( [0,0] )
81   - padsize=padsize + array( [0,0] )
82   - if ( any( padsize < 0 ) ):
83   - raise InputException, "Pad size must be non-negative."
84   -
85   - (height,width) = im.shape
86   - (y,x) = blksize + padsize
87   -
88   - rows = int( ( height + padsize[0] ) / y )
89   - cols = int( ( width + padsize[1] ) / x )
90   -
91   - T = zeros( [y*rows,x*cols] )
92   -
93   - imy = y*rows - padsize[0]
94   - imx = x*cols - padsize[1]
95   -
96   - T[0:imy,0:imx] = im[0:imy,0:imx]
97   -
98   - T = reshape(T, [ cols, y, rows, x ] )
99   - T = transpose( T, [0,2,1,3])
100   - T = reshape( T, [ y, x, rows*cols ] )
101   - V = T[0:blksize[0], 0:blksize[1], 0:(rows*cols) ]
102   -
103   - return (reshape( V, [ rows*cols, y*x ] ), rows, cols)
104   -
105   -def vec2im(V,blksize=None,padsize=0,rows=None,cols=None):
106   - """Reshape and combine column vectors into a 2D image
107   -
108   - V is an MxN array containing N Mx1 column vectors which will be reshaped
109   - and combined to form image IM.
110   -
111   - PADSIZE is a scalar or a 1x2 vector indicating the amount of vertical and
112   - horizontal space to be added as a border between the reshaped vectors.
113   - Default is [0 0]. If PADSIZE is a scalar, the same amount of space is used
114   - for both directions.
115   -
116   - BLKSIZE is a scalar or a 1x2 vector indicating the size of the blocks.
117   - Default is sqrt(M).
118   -
119   - ROWS indicates the number of rows of blocks in the image. Default is
120   - floor(sqrt(N)).
121   -
122   - COLS indicates the number of columns of blocks in the image. Default
123   - is ceil(N/ROWS).
124   - """
125   -
126   - (n,m) = V.shape
127   -
128   - padsize = padsize + array( [0,0] )
129   - if ( any( padsize < 0 ) ):
130   - raise InputException, "Pad size must be non-negative."
131   -
132   - if blksize == None:
133   - bsize = floor(sqrt(m))
134   -
135   - blksize = blksize + array([0,0])
136   - if prod(blksize) != m:
137   - print m, blksize
138   - raise InputException, 'Block size does not match size of input vectors.'
139   -
140   - if rows == None:
141   - rows = floor(sqrt(n))
142   - if cols == None:
143   - cols = ceil(n/rows)
144   -
145   -# make image
146   -#
147   -# ::
148   -
149   - (y,x) = blksize + padsize
150   -
151   -# zero() returns float64 and causes T to become a floating point array
152   -# This is a bug; integer input should give integer return
153   -#
154   -# ::
155   -
156   - T = zeros( [rows*cols, y, x] )
157   - T[0:n, 0:blksize[0], 0:blksize[1]] = \
158   - reshape( V, [n, blksize[0], blksize[1] ] )
159   - T = reshape(T, [rows,cols,y,x] )
160   - T = transpose( T, [0,2,1,3] )
161   - T = reshape(T, [y*rows,x*cols] )
162   - return T[0:(y*rows-padsize[0]), 0:(x*cols-padsize[1]) ]
163   -
164   -def quantise(C,Q):
165   - """Quantise DCT coefficients using the quantisation matrix Q."""
166   - return C / repmat( Q, C.shape / Q.shape )
167   -
168   -def dequantise(C,Q):
169   - """Dequantise JPEG coefficients using the quantisation matrix Q."""
170   - return C * repmat( Q, C.shape / Q.shape )
171   -
172   -def bdct(A,blksize=8):
173   - """Blocked discrete cosine transform for JPEG compression."""
174   - dctm = bdctmtx(blksize)
175   - (v,r,c) = im2vec(a,blksize)
176   - return vec2im(dot(dctm,v),blksize,rows=r,cols=c)
177   -
178   -def ibdct(A,blksize=8):
179   - """Inverse blocked discrete cosine transform"""
180   - dctm = bdctmtx(blksize)
181   - (v,r,c) = im2vec(a,blksize)
182   - return vec2im(dot(transpose(dctm),v),blksize,rows=r,cols=c)
183 98  
... ...
mjpeg/compress.pyc 0 → 100644
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msteg/steganalysis/MPB.py
  Diff comments   View file @f4b5291
... ... @@ -16,6 +16,10 @@ import pickle
16 16 import cv2
17 17 from sklearn import svm
18 18  
  19 +# from numba import jit
  20 +
  21 +
  22 +
19 23 base_dir = '/home/hadoop/data/HeadShoulder/'
20 24  
21 25  
... ... @@ -82,7 +86,7 @@ class MPB(StegBase):
82 86 # 1.422729s
83 87 return TPM
84 88  
85   -
  89 + @jit
86 90 def get_trans_prob_mat(self, ciq, T=4):
87 91 """
88 92 Calculate Transition Probability Matrix.
... ...
msteg/steganalysis/MPB.pyc
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msteg/steganalysis/__init__.pyc
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msteg/steganography/F4.pyc
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msteg/steganography/F5.pyc
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msteg/steganography/__init__.pyc
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res/compress.py 0 → 100644
  Diff comments   View file @f4b5291
... ... @@ -0,0 +1,183 @@
  1 +## -*- coding: utf-8 -*-
  2 +
  3 +
  4 +from pylab import *
  5 +
  6 +# The standard quantisation tables for JPEG::
  7 +
  8 +table0 = array(
  9 + [ [ 16, 11, 10, 16, 24, 40, 51, 61 ],
  10 + [ 12, 12, 14, 19, 26, 58, 60, 55 ],
  11 + [ 14, 13, 16, 24, 40, 57, 69, 56 ],
  12 + [ 14, 17, 22, 29, 51, 87, 80, 62 ],
  13 + [ 18, 22, 37, 56, 68, 109, 103, 77 ],
  14 + [ 24, 35, 55, 64, 81, 104, 113, 92 ],
  15 + [ 49, 64, 78, 87, 103, 121, 120, 101 ],
  16 + [ 72, 92, 95, 98, 112, 100, 103, 99 ] ] )
  17 +
  18 +table1 = array(
  19 + [ [ 17, 18, 24, 47, 99, 99, 99, 99 ],
  20 + [ 18, 21, 26, 66, 99, 99, 99, 99 ],
  21 + [ 24, 26, 56, 99, 99, 99, 99, 99 ],
  22 + [ 47, 66, 99, 99, 99, 99, 99, 99 ],
  23 + [ 99, 99, 99, 99, 99, 99, 99, 99 ],
  24 + [ 99, 99, 99, 99, 99, 99, 99, 99 ],
  25 + [ 99, 99, 99, 99, 99, 99, 99, 99 ],
  26 + [ 99, 99, 99, 99, 99, 99, 99, 99 ] ] )
  27 +
  28 +# The quantTable function seems straight forward,
  29 +# but has not been tested.
  30 +
  31 +def quantTable(quality=50,tnum=0,force_baseline=False):
  32 + if quality <= 0: quality = 1
  33 + elif quality > 100: quality = 100
  34 + if quality < 50: quality = 5000 / quality
  35 + else: quality = 200 - quality*2
  36 +
  37 + t = floor( (t * quality + 50) /100 )
  38 +
  39 + t[t<1] = 1
  40 +
  41 + if (force_baseline): t[t>255] = 255
  42 + else: t[t>32767] = 32767 # max quantizer needed for 12 bits
  43 +
  44 + return t
  45 +
  46 +# I don't think this works.
  47 +
  48 +def bdctmtx(n=8):
  49 + (c,r) = meshgrid(range(n), range(n))
  50 + (c0,r0) = meshgrid(r.flatten());
  51 + (c1,r1) = meshgrid(c.flatten());
  52 +
  53 + x = sqrt(float(2) / n)
  54 + x *= cos( pi * (2*c + 1) * r / (2 * n));
  55 + x[1,:] = x[1,:] / sqrt(2);
  56 +
  57 + return x[r0+c0*n+1] * x[r1+c1*n+1]
  58 +
  59 +def im2vec(im,blksize=8,padsize=0):
  60 + """Reshape 2D image blocks into an array of column vectors
  61 +
  62 + V=im2vec(im,blksize=8,padsize=0)
  63 +
  64 + IM is an image to be separated into non-overlapping blocks and
  65 + reshaped into an MxN array containing N blocks reshaped into Mx1
  66 + column vectors. im2vec is designed to be the inverse of vec2im.
  67 +
  68 + BLKSIZE is a scalar or 1x2 vector indicating the size of the blocks.
  69 +
  70 + PADSIZE is a scalar or 1x2 vector indicating the amount of vertical
  71 + and horizontal space to be skipped between blocks in the image.
  72 + Default is [0 0]. If PADSIZE is a scalar, the same amount of space
  73 + is used for both directions. PADSIZE must be non-negative (blocks
  74 + must be non-overlapping).
  75 +
  76 + ROWS indicates the number of rows of blocks found in the image.
  77 + COLS indicates the number of columns of blocks found in the image.
  78 + """
  79 +
  80 + blksize=blksize + array( [0,0] )
  81 + padsize=padsize + array( [0,0] )
  82 + if ( any( padsize < 0 ) ):
  83 + raise InputException, "Pad size must be non-negative."
  84 +
  85 + (height,width) = im.shape
  86 + (y,x) = blksize + padsize
  87 +
  88 + rows = int( ( height + padsize[0] ) / y )
  89 + cols = int( ( width + padsize[1] ) / x )
  90 +
  91 + T = zeros( [y*rows,x*cols] )
  92 +
  93 + imy = y*rows - padsize[0]
  94 + imx = x*cols - padsize[1]
  95 +
  96 + T[0:imy,0:imx] = im[0:imy,0:imx]
  97 +
  98 + T = reshape(T, [ cols, y, rows, x ] )
  99 + T = transpose( T, [0,2,1,3])
  100 + T = reshape( T, [ y, x, rows*cols ] )
  101 + V = T[0:blksize[0], 0:blksize[1], 0:(rows*cols) ]
  102 +
  103 + return (reshape( V, [ rows*cols, y*x ] ), rows, cols)
  104 +
  105 +def vec2im(V,blksize=None,padsize=0,rows=None,cols=None):
  106 + """Reshape and combine column vectors into a 2D image
  107 +
  108 + V is an MxN array containing N Mx1 column vectors which will be reshaped
  109 + and combined to form image IM.
  110 +
  111 + PADSIZE is a scalar or a 1x2 vector indicating the amount of vertical and
  112 + horizontal space to be added as a border between the reshaped vectors.
  113 + Default is [0 0]. If PADSIZE is a scalar, the same amount of space is used
  114 + for both directions.
  115 +
  116 + BLKSIZE is a scalar or a 1x2 vector indicating the size of the blocks.
  117 + Default is sqrt(M).
  118 +
  119 + ROWS indicates the number of rows of blocks in the image. Default is
  120 + floor(sqrt(N)).
  121 +
  122 + COLS indicates the number of columns of blocks in the image. Default
  123 + is ceil(N/ROWS).
  124 + """
  125 +
  126 + (n,m) = V.shape
  127 +
  128 + padsize = padsize + array( [0,0] )
  129 + if ( any( padsize < 0 ) ):
  130 + raise InputException, "Pad size must be non-negative."
  131 +
  132 + if blksize == None:
  133 + bsize = floor(sqrt(m))
  134 +
  135 + blksize = blksize + array([0,0])
  136 + if prod(blksize) != m:
  137 + print m, blksize
  138 + raise InputException, 'Block size does not match size of input vectors.'
  139 +
  140 + if rows == None:
  141 + rows = floor(sqrt(n))
  142 + if cols == None:
  143 + cols = ceil(n/rows)
  144 +
  145 +# make image
  146 +#
  147 +# ::
  148 +
  149 + (y,x) = blksize + padsize
  150 +
  151 +# zero() returns float64 and causes T to become a floating point array
  152 +# This is a bug; integer input should give integer return
  153 +#
  154 +# ::
  155 +
  156 + T = zeros( [rows*cols, y, x] )
  157 + T[0:n, 0:blksize[0], 0:blksize[1]] = \
  158 + reshape( V, [n, blksize[0], blksize[1] ] )
  159 + T = reshape(T, [rows,cols,y,x] )
  160 + T = transpose( T, [0,2,1,3] )
  161 + T = reshape(T, [y*rows,x*cols] )
  162 + return T[0:(y*rows-padsize[0]), 0:(x*cols-padsize[1]) ]
  163 +
  164 +def quantise(C,Q):
  165 + """Quantise DCT coefficients using the quantisation matrix Q."""
  166 + return C / repmat( Q, C.shape / Q.shape )
  167 +
  168 +def dequantise(C,Q):
  169 + """Dequantise JPEG coefficients using the quantisation matrix Q."""
  170 + return C * repmat( Q, C.shape / Q.shape )
  171 +
  172 +def bdct(A,blksize=8):
  173 + """Blocked discrete cosine transform for JPEG compression."""
  174 + dctm = bdctmtx(blksize)
  175 + (v,r,c) = im2vec(a,blksize)
  176 + return vec2im(dot(dctm,v),blksize,rows=r,cols=c)
  177 +
  178 +def ibdct(A,blksize=8):
  179 + """Inverse blocked discrete cosine transform"""
  180 + dctm = bdctmtx(blksize)
  181 + (v,r,c) = im2vec(a,blksize)
  182 + return vec2im(dot(transpose(dctm),v),blksize,rows=r,cols=c)
  183 +
... ...
res/quality.c 0 → 100644
  Diff comments   View file @f4b5291
... ... @@ -0,0 +1,134 @@
  1 +static void JPEGSetImageQuality(struct jpeg_decompress_struct *jpeg_info,
  2 + Image *image)
  3 +{
  4 + image->quality=UndefinedCompressionQuality;
  5 +#if defined(D_PROGRESSIVE_SUPPORTED)
  6 + if (image->compression == LosslessJPEGCompression)
  7 + {
  8 + image->quality=100;
  9 + (void) LogMagickEvent(CoderEvent,GetMagickModule(),
  10 + "Quality: 100 (lossless)");
  11 + }
  12 + else
  13 +#endif
  14 + {
  15 + ssize_t
  16 + j,
  17 + qvalue,
  18 + sum;
  19 +
  20 + register ssize_t
  21 + i;
  22 +
  23 + /*
  24 + Determine the JPEG compression quality from the quantization tables.
  25 + */
  26 + sum=0;
  27 + for (i=0; i < NUM_QUANT_TBLS; i++)
  28 + {
  29 + if (jpeg_info->quant_tbl_ptrs[i] != NULL)
  30 + for (j=0; j < DCTSIZE2; j++)
  31 + sum+=jpeg_info->quant_tbl_ptrs[i]->quantval[j];
  32 + }
  33 + if ((jpeg_info->quant_tbl_ptrs[0] != NULL) &&
  34 + (jpeg_info->quant_tbl_ptrs[1] != NULL))
  35 + {
  36 + ssize_t
  37 + hash[101] =
  38 + {
  39 + 1020, 1015, 932, 848, 780, 735, 702, 679, 660, 645,
  40 + 632, 623, 613, 607, 600, 594, 589, 585, 581, 571,
  41 + 555, 542, 529, 514, 494, 474, 457, 439, 424, 410,
  42 + 397, 386, 373, 364, 351, 341, 334, 324, 317, 309,
  43 + 299, 294, 287, 279, 274, 267, 262, 257, 251, 247,
  44 + 243, 237, 232, 227, 222, 217, 213, 207, 202, 198,
  45 + 192, 188, 183, 177, 173, 168, 163, 157, 153, 148,
  46 + 143, 139, 132, 128, 125, 119, 115, 108, 104, 99,
  47 + 94, 90, 84, 79, 74, 70, 64, 59, 55, 49,
  48 + 45, 40, 34, 30, 25, 20, 15, 11, 6, 4,
  49 + 0
  50 + },
  51 + sums[101] =
  52 + {
  53 + 32640, 32635, 32266, 31495, 30665, 29804, 29146, 28599, 28104,
  54 + 27670, 27225, 26725, 26210, 25716, 25240, 24789, 24373, 23946,
  55 + 23572, 22846, 21801, 20842, 19949, 19121, 18386, 17651, 16998,
  56 + 16349, 15800, 15247, 14783, 14321, 13859, 13535, 13081, 12702,
  57 + 12423, 12056, 11779, 11513, 11135, 10955, 10676, 10392, 10208,
  58 + 9928, 9747, 9564, 9369, 9193, 9017, 8822, 8639, 8458,
  59 + 8270, 8084, 7896, 7710, 7527, 7347, 7156, 6977, 6788,
  60 + 6607, 6422, 6236, 6054, 5867, 5684, 5495, 5305, 5128,
  61 + 4945, 4751, 4638, 4442, 4248, 4065, 3888, 3698, 3509,
  62 + 3326, 3139, 2957, 2775, 2586, 2405, 2216, 2037, 1846,
  63 + 1666, 1483, 1297, 1109, 927, 735, 554, 375, 201,
  64 + 128, 0
  65 + };
  66 +
  67 + qvalue=(ssize_t) (jpeg_info->quant_tbl_ptrs[0]->quantval[2]+
  68 + jpeg_info->quant_tbl_ptrs[0]->quantval[53]+
  69 + jpeg_info->quant_tbl_ptrs[1]->quantval[0]+
  70 + jpeg_info->quant_tbl_ptrs[1]->quantval[DCTSIZE2-1]);
  71 + for (i=0; i < 100; i++)
  72 + {
  73 + if ((qvalue < hash[i]) && (sum < sums[i]))
  74 + continue;
  75 + if (((qvalue <= hash[i]) && (sum <= sums[i])) || (i >= 50))
  76 + image->quality=(size_t) i+1;
  77 + if (image->debug != MagickFalse)
  78 + (void) LogMagickEvent(CoderEvent,GetMagickModule(),
  79 + "Quality: %.20g (%s)",(double) i+1,(qvalue <= hash[i]) &&
  80 + (sum <= sums[i]) ? "exact" : "approximate");
  81 + break;
  82 + }
  83 + }
  84 + else
  85 + if (jpeg_info->quant_tbl_ptrs[0] != NULL)
  86 + {
  87 + ssize_t
  88 + hash[101] =
  89 + {
  90 + 510, 505, 422, 380, 355, 338, 326, 318, 311, 305,
  91 + 300, 297, 293, 291, 288, 286, 284, 283, 281, 280,
  92 + 279, 278, 277, 273, 262, 251, 243, 233, 225, 218,
  93 + 211, 205, 198, 193, 186, 181, 177, 172, 168, 164,
  94 + 158, 156, 152, 148, 145, 142, 139, 136, 133, 131,
  95 + 129, 126, 123, 120, 118, 115, 113, 110, 107, 105,
  96 + 102, 100, 97, 94, 92, 89, 87, 83, 81, 79,
  97 + 76, 74, 70, 68, 66, 63, 61, 57, 55, 52,
  98 + 50, 48, 44, 42, 39, 37, 34, 31, 29, 26,
  99 + 24, 21, 18, 16, 13, 11, 8, 6, 3, 2,
  100 + 0
  101 + },
  102 + sums[101] =
  103 + {
  104 + 16320, 16315, 15946, 15277, 14655, 14073, 13623, 13230, 12859,
  105 + 12560, 12240, 11861, 11456, 11081, 10714, 10360, 10027, 9679,
  106 + 9368, 9056, 8680, 8331, 7995, 7668, 7376, 7084, 6823,
  107 + 6562, 6345, 6125, 5939, 5756, 5571, 5421, 5240, 5086,
  108 + 4976, 4829, 4719, 4616, 4463, 4393, 4280, 4166, 4092,
  109 + 3980, 3909, 3835, 3755, 3688, 3621, 3541, 3467, 3396,
  110 + 3323, 3247, 3170, 3096, 3021, 2952, 2874, 2804, 2727,
  111 + 2657, 2583, 2509, 2437, 2362, 2290, 2211, 2136, 2068,
  112 + 1996, 1915, 1858, 1773, 1692, 1620, 1552, 1477, 1398,
  113 + 1326, 1251, 1179, 1109, 1031, 961, 884, 814, 736,
  114 + 667, 592, 518, 441, 369, 292, 221, 151, 86,
  115 + 64, 0
  116 + };
  117 +
  118 + qvalue=(ssize_t) (jpeg_info->quant_tbl_ptrs[0]->quantval[2]+
  119 + jpeg_info->quant_tbl_ptrs[0]->quantval[53]);
  120 + for (i=0; i < 100; i++)
  121 + {
  122 + if ((qvalue < hash[i]) && (sum < sums[i]))
  123 + continue;
  124 + if (((qvalue <= hash[i]) && (sum <= sums[i])) || (i >= 50))
  125 + image->quality=(size_t) i+1;
  126 + if (image->debug != MagickFalse)
  127 + (void) LogMagickEvent(CoderEvent,GetMagickModule(),
  128 + "Quality: %.20g (%s)",(double) i+1,(qvalue <= hash[i]) &&
  129 + (sum <= sums[i]) ? "exact" : "approximate");
  130 + break;
  131 + }
  132 + }
  133 + }
  134 +}
... ...
test_jpeg.py
  Diff comments   View file @f4b5291
... ... @@ -167,7 +167,10 @@ if __name__ == &#39;__main__&#39;:
167 167  
168 168 # test_bitbyte()
169 169  
170   - ima = mjpeg.Jpeg("res/test3.jpg", key=sample_key)
  170 + ima = mjpeg.Jpeg("res/lena.jpg", key=sample_key)
  171 + print ima.getQuality()
  172 + sys.exit(0)
  173 +
171 174 # imb = mjpeg.Jpeg("res/new.jpg",key=sample_key)
172 175 imc = mjpeg.Jpeg("res/steged.jpg", key=sample_key)
173 176 print ima.Jgetcompdim(0)
... ...