def test_complete_inference2():
dcrf = densecrf.DenseCRF(100, 2)
pcrf = pycrf.DenseCRF(100, 2)
unary = test_utils._get_simple_unary()
img = test_utils._get_simple_img()
dcrf.setUnaryEnergy(-np.log(unary))
pcrf.set_unary_energy(-np.log(unary))
feats = utils.create_pairwise_gaussian(sdims=(1.5, 1.5),
shape=img.shape[:2])
dcrf.addPairwiseEnergy(feats, compat=3)
pcrf.add_pairwise_energy(feats, compat=3)
feats = utils.create_pairwise_bilateral(sdims=(2, 2), schan=2,
img=img, chdim=2)
dcrf.addPairwiseEnergy(feats, compat=3)
pcrf.add_pairwise_energy(feats, compat=3)
# d.addPairwiseBilateral(2, 2, img, 3)
res1 = np.argmax(dcrf.inference(10), axis=0).reshape(10, 10)
res2 = np.argmax(pcrf.inference(10), axis=0).reshape(10, 10)
if False:
# Save the result for visual inspection
import scipy as scp
import scipy.misc
scp.misc.imsave("test.png", res1)
assert(np.all(res1 == res2))
def test_pairwise():
unary = test_utils._get_simple_unary()
img = test_utils._get_simple_img()
feats = utils.create_pairwise_bilateral(sdims=(2, 2),
schan=2,
img=img,
chdim=2)
pairwise = pair.PairwisePotentials(feats, compat=3)
out = pairwise.apply(unary)
return out
def test_call_dcrf2d():
d = dcrf.DenseCRF2D(10, 10, 2)
unary = test_utils._get_simple_unary()
img = test_utils._get_simple_img()
d.setUnaryEnergy(-np.log(unary))
# d.setUnaryEnergy(PyConstUnary(-np.log(Up)))
d.addPairwiseBilateral(sxy=2, srgb=2, rgbim=img, compat=3)
# d.addPairwiseBilateral(2, 2, img, 3)
res = np.argmax(d.inference(10), axis=0).reshape(10, 10)
np.all(res == img[:, :, 0] / 255)
def test_call_dcrf():
d = dcrf.DenseCRF(100, 2)
unary = test_utils._get_simple_unary()
img = test_utils._get_simple_img()
d.setUnaryEnergy(-np.log(unary))
# d.setUnaryEnergy(PyConstUnary(-np.log(Up)))
feats = utils.create_pairwise_bilateral(sdims=(2, 2), schan=2,
img=img, chdim=2)
d.addPairwiseEnergy(feats, compat=3)
# d.addPairwiseBilateral(2, 2, img, 3)
res = np.argmax(d.inference(10), axis=0).reshape(10, 10)
np.all(res == img[:, :, 0] / 255)
def test_complete_inference():
dcrf = densecrf.DenseCRF(100, 2)
pcrf = pycrf.DenseCRF(100, 2)
unary = test_utils._get_simple_unary()
img = test_utils._get_simple_img()
dcrf.setUnaryEnergy(-np.log(unary))
pcrf.set_unary_energy(-np.log(unary))
feats = utils.create_pairwise_bilateral(sdims=(2, 2), schan=2,
img=img, chdim=2)
dcrf.addPairwiseEnergy(feats, compat=3)
pcrf.add_pairwise_energy(feats, compat=3)
# d.addPairwiseBilateral(2, 2, img, 3)
res1 = np.argmax(dcrf.inference(10), axis=0).reshape(10, 10)
res2 = np.argmax(pcrf.inference(10), axis=0).reshape(10, 10)
assert(np.all(res1 == res2))
def test_call_dcrf_eq_dcrf2d():
d = dcrf.DenseCRF(100, 2)
d2 = dcrf.DenseCRF2D(10, 10, 2)
unary = test_utils._get_simple_unary()
img = test_utils._get_simple_img()
d.setUnaryEnergy(-np.log(unary))
d2.setUnaryEnergy(-np.log(unary))
feats = utils.create_pairwise_bilateral(sdims=(2, 2), schan=2,
img=img, chdim=2)
d.addPairwiseEnergy(feats, compat=3)
d2.addPairwiseBilateral(sxy=2, srgb=2, rgbim=img, compat=3)
# d.addPairwiseBilateral(2, 2, img, 3)
res1 = np.argmax(d.inference(10), axis=0).reshape(10, 10)
res2 = np.argmax(d2.inference(10), axis=0).reshape(10, 10)
assert(np.all(res1 == res2))
def test_pairwise_inference():
dcrf = densecrf.DenseCRF(100, 2)
unary = test_utils._get_simple_unary()
img = test_utils._get_simple_img()
dcrf.setUnaryEnergy(-np.log(unary))
lg_unary = -np.log(unary)
feats = utils.create_pairwise_bilateral(sdims=(2, 2),
schan=2,
img=img,
chdim=2)
dcrf.addPairwiseEnergy(feats, compat=3)
pairwise = pair.PairwisePotentials(feats, compat=3)
dres = np.argmax(dcrf.inference(10), axis=0).reshape(10, 10)
out = compute_inference_with_pair([pairwise], lg_unary, 10)
pres = np.argmax(out, axis=0).reshape(10, 10)
assert (np.all(dres == pres))
def test_dkernel_inference():
dcrf = densecrf.DenseCRF(100, 2)
unary = test_utils._get_simple_unary()
img = test_utils._get_simple_img()
dcrf.setUnaryEnergy(-np.log(unary))
lg_unary = -np.log(unary)
feats = utils.create_pairwise_bilateral(sdims=(2, 2),
schan=2,
img=img,
chdim=2)
dcrf.addPairwiseEnergy(feats, compat=3)
klist = [pair.DenseKernel(feats)]
clist = [pair.PottsComp(3)]
dres = np.argmax(dcrf.inference(10), axis=0).reshape(10, 10)
out = compute_inference_with_dkernel(klist, clist, lg_unary, 10)
pres = np.argmax(out, axis=0).reshape(10, 10)
assert (np.all(dres == pres))
