Mercurial > hg > pydct
changeset 0:63af49cca5d2
initial import
| author | pmeerw@pan |
|---|---|
| date | Tue, 06 May 2008 23:01:28 +0200 |
| parents | |
| children | 9aa2dd7d0de7 |
| files | .hgignore README pydct/__init__.py pydct/dct.py pydct/perceptual.py pydct/t4x4.py pydct/t8x8.py pydct/tNxM.py pydct/tNxN.py setup.py |
| diffstat | 9 files changed, 317 insertions(+), 0 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/.hgignore Tue May 06 23:01:28 2008 +0200 @@ -0,0 +1,23 @@ +syntax: glob + +*.elc +*.orig +*.rej +*~ +*.mergebackup +*.o +*.so +*.pyc +*.swp +*.prof +tests/.coverage* +tests/annotated +tests/*.err +build +MANIFEST +.DS_Store +tags +cscope.* + +syntax: regexp +^\.pc/
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/pydct/__init__.py Tue May 06 23:01:28 2008 +0200 @@ -0,0 +1,6 @@ +from dct import fdct, idct, zigzag +from t4x4 import fdct4x4, idct4x4 +from t8x8 import fdct8x8, idct8x8, fdct8x8x8, idct8x8x8, do_f8x8, do_i8x8, build_vector_from_8x8, set_8x8_from_vector +from tNxM import fdct2d, idct2d +from tNxN import fdctNxN, idctNxN +from perceptual import watson_slack
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/pydct/dct.py Tue May 06 23:01:28 2008 +0200 @@ -0,0 +1,54 @@ +import numpy, math + +__dctN = {} + +def __init_dctN(n): + global __dctN + if not __dctN.has_key(n): + c = numpy.empty((n, n), numpy.float) + c[0,:] = 1.0 / math.sqrt(n) + __cosf = lambda i, j: numpy.cos(math.pi * (2*j + 1) * (i + 1) / (2.0 * n)) + c[1:,:] = math.sqrt(2.0 / n) * numpy.fromfunction(__cosf, (n-1, n)) + __dctN[n] = c + return __dctN[n] + +def fdct(v): + ''' + Forward DCT on vector. + ''' + c = __init_dctN(len(v)) + return numpy.dot(c, v) + +def idct(v): + ''' + Inverse DCT on vector. + ''' + c = __init_dctN(len(v)) + return numpy.dot(numpy.transpose(c), v) + +def zigzag(x): + """Generates zig-zag scan sequence for two dimensional array.""" + j = 0 + i = 0 + while True: + + if i == x.shape[0]: j += 2; i = x.shape[0]-1 + else: j = 0 + while i >= 0 and j < x.shape[1]: + # run up + yield i, j + i -= 1 + j += 1 + + if j > x.shape[1]: break + + if j == x.shape[1]: j = x.shape[1]-1; i += 2 + else: i = 0 + while j >= 0 and i < x.shape[0]: + # run down + yield i, j + i += 1 + j -= 1 + + if i > x.shape[0]: break +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/pydct/perceptual.py Tue May 06 23:01:28 2008 +0200 @@ -0,0 +1,39 @@ +import numpy + +JPEG_luma_Q = numpy.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]]) + +JPEG_chroma_Q = numpy.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]]) + +def watson_slack(b, c00): + # table of sensitivity values + t = numpy.array( \ + [1.404, 1.011, 1.169, 1.664, 2.408, 3.433, 4.796, 6.563,\ + 1.011, 1.452, 1.323, 1.529, 2.006, 2.716, 3.679, 4.939,\ + 1.169, 1.323, 2.241, 2.594, 2.988, 3.649, 4.604, 5.883,\ + 1.664, 1.529, 2.594, 3.773, 4.559, 5.305, 6.281, 7.600,\ + 2.408, 2.006, 2.988, 4.559, 6.152, 7.463, 8.713, 10.175,\ + 3.433, 2.716, 3.649, 5.305, 7.463, 9.625, 11.588, 13.519,\ + 4.796, 3.679, 4.604, 6.281, 8.713, 11.588, 14.500, 17.294,\ + 6.563, 4.939, 5.883, 7.600, 10.175, 13.519, 17.294, 21.156]) + + tl = t * math.pow(b.ravel()[0] / c00, 0.649) + + tl[1:] = numpy.maximum(tl[1:], (numpy.abs(b.ravel()[1:])**0.7) * (tl[1:]**0.3)) + return tl.reshape((8, 8)) +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/pydct/t4x4.py Tue May 06 23:01:28 2008 +0200 @@ -0,0 +1,39 @@ +import numpy + +def fdct4x4(b): + ''' + Compute the approximate 4x4 DCT coefficients of an array + as defined by H.264/AVC. + ''' + c, e = \ + numpy.array( + [[ 1, 1, 1, 1], + [ 2, 1, -1, -2], + [ 1, -1, -1, 1], + [ 1, -2, 2, -1]], numpy.float), \ + numpy.array( + [[0.25, 0.15811388, 0.25, 0.15811388], + [0.15811388, 0.1, 0.15811388, 0.1], + [0.25, 0.15811388, 0.25, 0.15811388], + [0.15811388, 0.1, 0.15811388, 0.1]], numpy.float) + + return numpy.dot(c, numpy.dot(b, numpy.transpose(c))) * e + +def idct4x4(b): + ''' + Compute the inverse 4x4 DCT of the array. + ''' + c, e = \ + numpy.array( + [[1, 1, 1, 0.5], + [1, 0.5, -1, -1], + [1, -0.5, -1, 1], + [1, -1, 1, -0.5]], numpy.float), \ + numpy.array( + [[0.25, 0.31622777, 0.25, 0.31622777], + [0.31622777, 0.4, 0.31622777, 0.4], + [0.25, 0.31622777, 0.25, 0.31622777], + [0.31622777, 0.4, 0.31622777, 0.4]], numpy.float) + + return numpy.dot(c, numpy.dot(b*e, numpy.transpose(c))) +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/pydct/t8x8.py Tue May 06 23:01:28 2008 +0200 @@ -0,0 +1,75 @@ +import tNxN, numpy + +def fdct8x8(b): + ''' + Forward 8x8 DCT. + ''' + return fdctNxN(b) + +def idct8x8(b): + ''' + Inverse 8x8 DCT. + ''' + return idctNxN(b) + +def fdct8x8x8(b): + ''' + Forward 8x8x8 DCT. + ''' + d = numpy.empty((8, 8, 8), numpy.float) + for i in xrange(8): + d[i,:,:] = fdct8x8(b[i,:,:]) + for r in xrange(8): + for c in xrange(8): + d[:,r,c] = fdct(d[:,r,c]) + return d + +def idct8x8x8(b): + ''' + Inverse 8x8x8 DCT. + ''' + d = numpy.empty((8, 8, 8), numpy.float) + for r in xrange(8): + for c in xrange(8): + d[:,r,c] = idct(b[:,r,c]) + for i in xrange(8): + d[i,:,:] = idct8x8(d[i,:,:]) + return d + +def do_f8x8(s): + for r in xrange(0, s.shape[0], 8): + for c in xrange(0, s.shape[1], 8): + s[r:r+8,c:c+8] = fdct8x8(s[r:r+8,c:c+8]) + return s + +def _get_zz(): + zz = [] + for i, j in wm.zigzag(numpy.empty((8,8))): + zz.append(i*8 + j) + return zz + +def build_vector_from_8x8(s): + v = numpy.zeros((64, (s.shape[0]//8)*(s.shape[1]//8)), numpy.float) + i = 0 + zz = _get_zz() + for r in xrange(0, s.shape[0], 8): + for c in xrange(0, s.shape[1], 8): + v[:,i] = s[r:r+8,c:c+8].flat[zz] + i += 1 + return v + +def do_i8x8(s): + for r in xrange(0, s.shape[0], 8): + for c in xrange(0, s.shape[1], 8): + s[r:r+8,c:c+8] = idct8x8(s[r:r+8,c:c+8]) + return s + +def set_8x8_from_vector(s, v): + i = 0 + zz = _get_zz() + for r in xrange(0, s.shape[0], 8): + for c in xrange(0, s.shape[1], 8): + s[r:r+8,c:c+8].flat[zz] = v[:,i] + i += 1 + return s +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/pydct/tNxM.py Tue May 06 23:01:28 2008 +0200 @@ -0,0 +1,56 @@ +import numpy, math + +__dctNxM = {} + +def __init_dctNxM(b): + global __dctNxM + if not __dctNxM.has_key(b.shape): + c = numpy.sqrt([2.0 / b.shape[0], 2.0 / b.shape[1]]) + __cosf0 = lambda j, i: numpy.cos((math.pi * (2*i + 1) * j) / (2.0 * b.shape[0])) + y = c[0] * numpy.fromfunction(__cosf0, (b.shape[0], b.shape[0])) + __cosf1 = lambda j, i: numpy.cos((math.pi * (2*i + 1) * j) / (2.0 * b.shape[1])) + x = c[1] * numpy.fromfunction(__cosf1, (b.shape[1], b.shape[1])) + __dctNxM[b.shape] = (y, x), c / math.sqrt(2.0) + return __dctNxM[b.shape] + +def fdct2d(b): + ''' + Compute forward 2D DCT on the array of arbitrary size. + Note: slow. + ''' + global __dctNxM + ct, c = __init_dctNxM(b) + + d = numpy.empty(b.shape, numpy.float) + d[0][0] = c[0] * c[1] * numpy.sum(numpy.sum(b)) + + for i in xrange(1, b.shape[1]): + d[0][i] = c[0] * numpy.sum(ct[1][i] * numpy.sum(b, 0)) + + for j in xrange(1, b.shape[0]): + d[j][0] = c[1] * numpy.sum(ct[0][j] * numpy.sum(b, 1)) + + bt = numpy.transpose(b) + for j in xrange(1, b.shape[0]): + d[j,1:] = numpy.sum(ct[1][1:] * numpy.sum(bt * ct[0][j], 1), 1) + + return d + +def idct2d(b): + ''' + Compute inverse 2D DCT on array of arbitrary size. + ''' + global __dctNxM + ct, c = __init_dctNxM(b) + + p0 = c[0] * c[1] * b[0][0] + bt = numpy.transpose(b[1:,1:]) + ctt = ct[1][1:,:].transpose() + d = numpy.empty(b.shape, numpy.float) + for y in xrange(b.shape[0]): + d[y,:] = p0 + \ + c[0] * numpy.sum(b[0,1:] * ctt, 1) + \ + c[1] * numpy.sum(b[1:,0] * ct[0][1:,y]) + \ + numpy.sum(numpy.sum(bt * ct[0][1:,y],1) * ctt,1) + return d +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/pydct/tNxN.py Tue May 06 23:01:28 2008 +0200 @@ -0,0 +1,15 @@ +import dct, numpy + +def fdctNxN(b): + ''' + Forward 2D DCT on NxN array. + ''' + c = __init_dctN(b.shape[0]) + return numpy.dot(c, numpy.dot(b, numpy.transpose(c))) + +def idctNxN(b): + ''' + Inverse 2D DCT on NxN array. + ''' + c = __init_dctN(b.shape[0]) + return numpy.dot(numpy.transpose(c), numpy.dot(b, c))
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/setup.py Tue May 06 23:01:28 2008 +0200 @@ -0,0 +1,10 @@ +from distutils.core import setup + +setup (name = 'pydct', + version = '1.0', + author = 'Peter Meerwald', + author_email = 'pmeerw@pmeerw.net', + description = 'pydct: Discrete Cosine Transform routines for Python', + packages=['pydct'], + license = 'BSD' +)