def test_opencl_implementation(self):
scikits.image.color.lazyopts.enable()
colspaces = ['HSV', 'RGB CIE', 'XYZ']
colfuncs_from = [hsv2rgb, rgbcie2rgb, xyz2rgb]
colfuncs_to = [rgb2hsv, rgb2rgbcie, rgb2xyz]
# create an input, and make some promises about it.
img = lazy.lnumpy.NdarraySymbol.new(value=self.colbars_array)
img.value = img.value.astype('float32')
img.contiguous=True
img.shape = (None, None, 3)
img.dtype=np.dtype('float32')
assert_almost_equal(convert_colorspace(self.colbars_array, 'RGB',
'RGB'), self.colbars_array)
for i, space in enumerate(colspaces):
print 'test: colorspace', space
gt = colfuncs_from[i](img)
eval_gt = lazy.function([img], gt)
assert_almost_equal(convert_colorspace(self.colbars_array, space,
'RGB'), eval_gt(img.value))
gt = colfuncs_to[i](img)
eval_gt = lazy.function([img], gt)
#eval_gt.print_eval_order()
assert_almost_equal(convert_colorspace(self.colbars_array, 'RGB',
space), eval_gt(img.value))
def test_opencl_speed(self):
scikits.image.color.lazyopts.enable()
colspaces = ['RGB CIE', 'XYZ']
colfuncs_from = [ rgbcie2rgb, xyz2rgb]
colfuncs_to = [ rgb2rgbcie, rgb2xyz]
imgdata = np.random.RandomState(234).rand(1600,1200,3).astype('float32')
# create an input, and make some promises about it.
img = lazy.lnumpy.NdarraySymbol.new()
img.contiguous=True
img.shape = (None, None, 3)
img.dtype=np.dtype('float32')
for i, space in enumerate(colspaces):
print 'test: colorspace', space
gt = colfuncs_from[i](img)
scikits.image.color.lazyopts.enable()
fn_yes_cl = lazy.function([img], gt)
scikits.image.color.lazyopts.disable()
fn_no_cl = lazy.function([img], gt)
fn_yes_cl.reuse_computed = True # optimization
print 'fn_yes_cl:'
fn_yes_cl.print_eval_order()
def with_cl():
return fn_yes_cl(imgdata)
def without_cl():
return fn_no_cl(imgdata)
def orig_fn():
return convert_colorspace(imgdata, space, 'RGB')
orig_fn_times = timeit.Timer(orig_fn).repeat(3,3)
without_cl_times = timeit.Timer(without_cl).repeat(3,3)
with_cl_times = timeit.Timer(with_cl).repeat(3,3)
print 'without_cl times',without_cl_times
print 'orig_fn times', orig_fn_times
print 'with_cl times', with_cl_times
print 'CL speedup:', np.asarray(without_cl_times) / with_cl_times
def func(*args, **kwargs):
return function(
transform_policy_ctor=lambda :(lambda x:x),
*args,**kwargs)
