d3e050d6
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staged.
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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 ] ] )
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 ] ] )
# The quantTable function seems straight forward,
# but has not been tested.
def quantTable(quality=50,tnum=0,force_baseline=False):
if quality <= 0: quality = 1
elif quality > 100: quality = 100
if quality < 50: quality = 5000 / quality
else: quality = 200 - quality*2
t = floor( (t * quality + 50) /100 )
t[t<1] = 1
if (force_baseline): t[t>255] = 255
else: t[t>32767] = 32767 # max quantizer needed for 12 bits
return t
# I don't think this works.
def bdctmtx(n=8):
(c,r) = meshgrid(range(n), range(n))
(c0,r0) = meshgrid(r.flatten());
(c1,r1) = meshgrid(c.flatten());
x = sqrt(float(2) / n)
x *= cos( pi * (2*c + 1) * r / (2 * n));
x[1,:] = x[1,:] / sqrt(2);
return x[r0+c0*n+1] * x[r1+c1*n+1]
def im2vec(im,blksize=8,padsize=0):
"""Reshape 2D image blocks into an array of column vectors
V=im2vec(im,blksize=8,padsize=0)
IM is an image to be separated into non-overlapping blocks and
reshaped into an MxN array containing N blocks reshaped into Mx1
column vectors. im2vec is designed to be the inverse of vec2im.
BLKSIZE is a scalar or 1x2 vector indicating the size of the blocks.
PADSIZE is a scalar or 1x2 vector indicating the amount of vertical
and horizontal space to be skipped between blocks in the image.
Default is [0 0]. If PADSIZE is a scalar, the same amount of space
is used for both directions. PADSIZE must be non-negative (blocks
must be non-overlapping).
ROWS indicates the number of rows of blocks found in the image.
COLS indicates the number of columns of blocks found in the image.
"""
blksize=blksize + array( [0,0] )
padsize=padsize + array( [0,0] )
if ( any( padsize < 0 ) ):
raise InputException, "Pad size must be non-negative."
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