def transcode(filename):
tmpname = test_utils.temporary_filename(suffix=os.path.splitext(filename)[1])
tmpnam_ = test_utils.temporary_filename(suffix=os.path.splitext(filename)[1])
try:
# complete transcoding test
image = load(filename)
# save with the same extension
write(image, tmpname)
# reload the image from the file
image2 = load(tmpname)
assert numpy.array_equal(image, image2)
# test getting part of the image as well
if len(image.shape) == 3:
subsample = image[:,::2,::2]
else:
subsample = image[::2,::2]
assert not subsample.flags.contiguous
write(subsample, tmpnam_)
image3 = load(tmpnam_)
assert numpy.array_equal(subsample, image3)
finally:
if os.path.exists(tmpname):
os.unlink(tmpname)
if os.path.exists(tmpnam_):
os.unlink(tmpnam_)
def transcode(filename):
tmpname = test_utils.temporary_filename(
suffix=os.path.splitext(filename)[1])
tmpnam_ = test_utils.temporary_filename(
suffix=os.path.splitext(filename)[1])
try:
# complete transcoding test
image = load(filename)
# save with the same extension
write(image, tmpname)
# reload the image from the file
image2 = load(tmpname)
assert numpy.array_equal(image, image2)
# test getting part of the image as well
if len(image.shape) == 3:
subsample = image[:, ::2, ::2]
else:
subsample = image[::2, ::2]
assert not subsample.flags.contiguous
write(subsample, tmpnam_)
image3 = load(tmpnam_)
assert numpy.array_equal(subsample, image3)
finally:
if os.path.exists(tmpname):
os.unlink(tmpname)
if os.path.exists(tmpnam_):
os.unlink(tmpnam_)
def test_persistence():
# make shure we can save an load an Machine machine
weights = []
weights.append(numpy.array([[.2, -.1, .2], [.2, .3, .9]]))
weights.append(numpy.array([[.1, .5], [-.1, .2], [-.1, 1.1]]))
biases = []
biases.append(numpy.array([-.1, .3, .1]))
biases.append(numpy.array([.2, -.1]))
m = Machine((2,3,2))
m.weights = weights
m.biases = biases
# creates a file that will be used in the next test!
machine_file = temporary_filename()
m.save(bob.io.base.HDF5File(machine_file, 'w'))
m2 = Machine(bob.io.base.HDF5File(machine_file))
assert m.is_similar_to(m2)
nose.tools.eq_(m, m2)
nose.tools.eq_(m.shape, m2.shape)
assert (m.input_subtract == m2.input_subtract).all()
assert (m.input_divide == m2.input_divide).all()
for i in range(len(m.weights)):
assert (m.weights[i] == m2.weights[i]).all()
assert (m.biases[i] == m2.biases[i]).all()
def test_persistence():
# make shure we can save an load an Machine machine
weights = []
weights.append(numpy.array([[.2, -.1, .2], [.2, .3, .9]]))
weights.append(numpy.array([[.1, .5], [-.1, .2], [-.1, 1.1]]))
biases = []
biases.append(numpy.array([-.1, .3, .1]))
biases.append(numpy.array([.2, -.1]))
m = Machine((2, 3, 2))
m.weights = weights
m.biases = biases
# creates a file that will be used in the next test!
machine_file = temporary_filename()
m.save(bob.io.base.HDF5File(machine_file, 'w'))
m2 = Machine(bob.io.base.HDF5File(machine_file))
assert m.is_similar_to(m2)
nose.tools.eq_(m, m2)
nose.tools.eq_(m.shape, m2.shape)
assert (m.input_subtract == m2.input_subtract).all()
assert (m.input_divide == m2.input_divide).all()
for i in range(len(m.weights)):
assert (m.weights[i] == m2.weights[i]).all()
assert (m.biases[i] == m2.biases[i]).all()
def test_io():
raise SkipTest("TODO: Not fully implemented yet")
# Checks that the IO functionality of LBP works
test_file = datafile("LBP.hdf5", __name__)
temp_file = temporary_filename()
# create file
lbp1 = bob.ip.base.LBP(8, (2, 3),
elbp_type="transitional",
to_average=True,
add_average_bit=True)
lbp2 = bob.ip.base.LBP(16,
4.,
2.,
uniform=True,
rotation_invariant=True,
circular=True)
# re-generate the reference file, if wanted
f = bob.io.base.HDF5File(temp_file, 'w')
f.create_group("LBP1")
f.create_group("LBP2")
f.cd("/LBP1")
lbp1.save(f)
f.cd("/LBP2")
lbp2.save(f)
del f
# load the file again
f = bob.io.base.HDF5File(temp_file)
f.cd("/LBP1")
read1 = bob.ip.base.LBP(f)
f.cd("/LBP2")
read2 = bob.ip.base.LBP(f)
del f
# assert that the created and the read object are identical
assert lbp1 == read1
assert lbp2 == read2
# load the reference file
f = bob.io.base.HDF5File(test_file)
f.cd("/LBP1")
ref1 = bob.ip.base.LBP(f)
f.cd("/LBP2")
ref2 = bob.ip.base.LBP(f)
del f
# assert that the lbp objects and the reference ones are identical
assert lbp1 == ref1
assert lbp2 == ref2
assert read1 == ref1
assert read2 == ref2
def test_io():
raise SkipTest("TODO: Not fully implemented yet")
# Checks that the IO functionality of LBP works
test_file = datafile("LBP.hdf5", __name__)
temp_file = temporary_filename()
# create file
lbp1 = bob.ip.base.LBP(8, (2,3), elbp_type="transitional", to_average=True, add_average_bit=True)
lbp2 = bob.ip.base.LBP(16, 4., 2., uniform=True, rotation_invariant=True, circular=True)
# re-generate the reference file, if wanted
f = bob.io.base.HDF5File(temp_file, 'w')
f.create_group("LBP1")
f.create_group("LBP2")
f.cd("/LBP1")
lbp1.save(f)
f.cd("/LBP2")
lbp2.save(f)
del f
# load the file again
f = bob.io.base.HDF5File(temp_file)
f.cd("/LBP1")
read1 = bob.ip.base.LBP(f)
f.cd("/LBP2")
read2 = bob.ip.base.LBP(f)
del f
# assert that the created and the read object are identical
assert lbp1 == read1
assert lbp2 == read2
# load the reference file
f = bob.io.base.HDF5File(test_file)
f.cd("/LBP1")
ref1 = bob.ip.base.LBP(f)
f.cd("/LBP2")
ref2 = bob.ip.base.LBP(f)
del f
# assert that the lbp objects and the reference ones are identical
assert lbp1 == ref1
assert lbp2 == ref2
assert read1 == ref1
assert read2 == ref2
def transcode(filename):
tmpname = test_utils.temporary_filename(suffix=os.path.splitext(filename)[1])
try:
# complete transcoding test
image = load(filename)
# save with the same extension
write(image, tmpname)
# reload the image from the file
image2 = load(tmpname)
assert numpy.array_equal(image, image2)
finally:
if os.path.exists(tmpname): os.unlink(tmpname)
def transcode(filename):
tmpname = test_utils.temporary_filename(
suffix=os.path.splitext(filename)[1])
try:
# complete transcoding test
image = load(filename)
# save with the same extension
write(image, tmpname)
# reload the image from the file
image2 = load(tmpname)
assert numpy.array_equal(image, image2)
finally:
if os.path.exists(tmpname):
os.unlink(tmpname)
def read_write(stem, fmt1, fmt2, encoding='UNKNOWN', bits_per_sample=16):
f1 = reader(F(stem + fmt1))
data = f1.load()
f2_filename = temporary_filename(suffix=fmt2)
f2 = writer(f2_filename, rate=f1.rate, encoding=encoding,
bits_per_sample=bits_per_sample)
f2.append(data)
f2.close() #forces file closing
f2 = reader(f2_filename)
nose.tools.eq_(f1.rate, f2.rate)
data_f1 = f1.load()
data_f2 = f2.load()
# verify the data is the same
assert numpy.array_equal(data_f1, data_f2), '%r != %r' % (data_f1, data_f2)
def read_write(stem, fmt1, fmt2, encoding='UNKNOWN', bits_per_sample=16):
f1 = reader(F(stem + fmt1))
data = f1.load()
f2_filename = temporary_filename(suffix=fmt2)
f2 = writer(f2_filename,
rate=f1.rate,
encoding=encoding,
bits_per_sample=bits_per_sample)
f2.append(data)
f2.close() #forces file closing
f2 = reader(f2_filename)
nose.tools.eq_(f1.rate, f2.rate)
data_f1 = f1.load()
data_f2 = f2.load()
# verify the data is the same
assert numpy.array_equal(data_f1, data_f2), '%r != %r' % (data_f1, data_f2)