def setUp(self): self.lena = scipy.misc.lena().astype(numpy.float32) self.shape = self.lena.shape self.extra = (10, 11) # self.img = scipy.ndimage.shift(self.lena, (7, 5)) # self.img = scipy.ndimage.rotate(self.lena, -20, reshape=False, order=3) # self.img = scipy.ndimage.shift(scipy.ndimage.rotate(self.lena, 20, reshape=False, order=3), (7, 5)) self.img = scipy.ndimage.affine_transform(self.lena, [[1.1, -0.1], [0.05, 0.9]], [7, 5]) self.align = LinearAlign(self.lena, context=ctx)
class test_linalign(unittest.TestCase): def setUp(self): self.lena = scipy.misc.lena().astype(numpy.float32) self.shape = self.lena.shape self.extra = (10, 11) # self.img = scipy.ndimage.shift(self.lena, (7, 5)) # self.img = scipy.ndimage.rotate(self.lena, -20, reshape=False, order=3) # self.img = scipy.ndimage.shift(scipy.ndimage.rotate(self.lena, 20, reshape=False, order=3), (7, 5)) self.img = scipy.ndimage.affine_transform(self.lena, [[1.1, -0.1], [0.05, 0.9]], [7, 5]) self.align = LinearAlign(self.lena, context=ctx) def test_align(self): """ tests the combine (linear combination) kernel """ out = self.align.align(self.img, 0, 1) for i in out: if i in ["offset", "matrix"]: print i print out[i] self.align.log_profile() out = out["result"] if PROFILE and out is not None: fig = pylab.figure() sp0 = fig.add_subplot(221) im0 = sp0.imshow(self.lena) sp1 = fig.add_subplot(222) im1 = sp1.imshow(self.img) sp2 = fig.add_subplot(223) im2 = sp2.imshow(out) sp3 = fig.add_subplot(224) delta = (out - self.lena)[100:400, 100:400] im3 = sp3.imshow(delta) print({ "min": delta.min(), "max:": delta.max(), "mean": delta.mean(), "std:": delta.std() }) pylab.show() raw_input("enter")
class test_linalign(unittest.TestCase): def setUp(self): self.lena = scipy.misc.lena().astype(numpy.float32) self.shape = self.lena.shape self.extra = (10, 11) # self.img = scipy.ndimage.shift(self.lena, (7, 5)) # self.img = scipy.ndimage.rotate(self.lena, -20, reshape=False, order=3) # self.img = scipy.ndimage.shift(scipy.ndimage.rotate(self.lena, 20, reshape=False, order=3), (7, 5)) self.img = scipy.ndimage.affine_transform(self.lena, [[1.1, -0.1], [0.05, 0.9]], [7, 5]) self.align = LinearAlign(self.lena, context=ctx) def test_align(self): """ tests the combine (linear combination) kernel """ out = self.align.align(self.img, 0, 1) for i in out: if i in ["offset","matrix"]: print i print out[i] self.align.log_profile() out = out["result"] if PROFILE and out is not None: fig = pylab.figure() sp0 = fig.add_subplot(221) im0 = sp0.imshow(self.lena) sp1 = fig.add_subplot(222) im1 = sp1.imshow(self.img) sp2 = fig.add_subplot(223) im2 = sp2.imshow(out) sp3 = fig.add_subplot(224) delta = (out - self.lena)[100:400, 100:400] im3 = sp3.imshow(delta) print({"min":delta.min(), "max:":delta.max(), "mean":delta.mean(), "std:":delta.std()}) pylab.show() raw_input("enter")