def test_hprewitt_vertical():
"""Horizontal prewitt on a vertical edge should be zero"""
i, j = np.mgrid[-5:6, -5:6]
image = (j >= 0).astype(float)
result = F.hprewitt(image)
eps = .000001
assert (np.all(np.abs(result) < eps))
def test_hprewitt_mask():
"""Horizontal prewitt on a masked array should be zero"""
np.random.seed(0)
result = F.hprewitt(np.random.uniform(size=(10, 10)),
np.zeros((10, 10), bool))
eps = .000001
assert (np.all(np.abs(result) < eps))
def test_hprewitt_mask():
"""Horizontal prewitt on a masked array should be zero"""
np.random.seed(0)
result = F.hprewitt(np.random.uniform(size=(10, 10)),
np.zeros((10, 10), bool))
eps = .000001
assert (np.all(np.abs(result) < eps))
def test_hprewitt_vertical():
"""Horizontal prewitt on a vertical edge should be zero"""
i, j = np.mgrid[-5:6, -5:6]
image = (j >= 0).astype(float)
result = F.hprewitt(image)
eps = .000001
assert (np.all(np.abs(result) < eps))
def post_process(img):
"""
Post-processes the results using skimage filters
"""
filt_1 = ski_filter.hprewitt(img)
filt_2 = exposure.equalize_hist(filt_1)
return filt_2
def post_process(img):
"""
Post-processes the results using skimage filters
"""
filt_1 = ski_filter.hprewitt(img)
filt_2 = exposure.equalize_hist(filt_1)
return filt_2
def test_hprewitt_horizontal():
"""Horizontal prewitt on an edge should be a horizontal line."""
i, j = np.mgrid[-5:6, -5:6]
image = (i >= 0).astype(float)
result = F.hprewitt(image)
# Fudge the eroded points
i[np.abs(j) == 5] = 10000
assert (np.all(result[i == 0] == 1))
assert_allclose(result[np.abs(i) > 1], 0, atol=1e-10)
def test_hprewitt_horizontal():
"""Horizontal prewitt on an edge should be a horizontal line"""
i, j = np.mgrid[-5:6, -5:6]
image = (i >= 0).astype(float)
result = F.hprewitt(image)
# Fudge the eroded points
i[np.abs(j) == 5] = 10000
eps = .000001
assert (np.all(result[i == 0] == 1))
assert (np.all(np.abs(result[np.abs(i) > 1]) < eps))
def classify(self,sample,fingerName,jointName):
max=sample.max()
sample=sample/max*255
sample=sample.astype('uint8')
cropSamp=sample[self.windowSize[0]:self.windowSize[1],self.windowSize[2]:self.windowSize[3]]
cropSamp=tv_denoise(cropSamp,weight=0.2)
if self.verbose:
plt.imshow(cropSamp,cmap=plt.cm.gray)
plt.show()
cropSamp=filter.hprewitt(cropSamp)
if self.verbose:
plt.imshow(cropSamp,cmap=plt.cm.gray)
plt.show()
#idx=cropSamp<0.08
#cropSamp[idx]=0
if self.verbose:
plt.imshow(cropSamp,cmap=plt.cm.gray)
plt.show()
scores = []
for classImage in self.classImages:
classImage=tv_denoise(classImage,weight=0.2)
classImage=filter.hprewitt(classImage)
#idx=classImage<0.08
#classImage[idx]=0
if False and self.verbose:
plt.imshow(classImage,cmap=plt.cm.gray)
plt.show()
#do template matching
score = match_template(classImage, cropSamp,1)
scores.append(np.max(score))
classification = self.classLabels[np.argmax(scores)]
return classification
def test_hprewitt_horizontal():
"""Horizontal prewitt on an edge should be a horizontal line"""
i, j = np.mgrid[-5:6, -5:6]
image = (i >= 0).astype(float)
result = F.hprewitt(image)
# Fudge the eroded points
i[np.abs(j) == 5] = 10000
eps = .000001
assert (np.all(result[i == 0] == 1))
assert (np.all(np.abs(result[np.abs(i) > 1]) < eps))
def test_hprewitt_mask():
"""Horizontal prewitt on a masked array should be zero."""
np.random.seed(0)
result = F.hprewitt(np.random.uniform(size=(10, 10)),
np.zeros((10, 10), bool))
assert_allclose(result, 0)
def test_hprewitt_zeros():
"""Horizontal prewitt on an array of all zeros."""
result = F.hprewitt(np.zeros((10, 10)), np.ones((10, 10), bool))
assert_allclose(result, 0)
def test_hprewitt_zeros():
"""Horizontal prewitt on an array of all zeros"""
result = F.hprewitt(np.zeros((10, 10)), np.ones((10, 10), bool))
assert (np.all(result == 0))
def vedges(self):
"""x=vedges(): returns a parameterization of the number of vertical edges versus total edges in an RGB image"""
hprew=filter.hprewitt(self.gray)
vprew=filter.vprewitt(self.gray)
vfrac=vprew.sum()/(vprew.sum()+hprew.sum())
return vfrac
def test_hprewitt_zeros():
"""Horizontal prewitt on an array of all zeros"""
result = F.hprewitt(np.zeros((10, 10)), np.ones((10, 10), bool))
assert (np.all(result == 0))
def test_00_00_zeros(self):
"""Horizontal sobel on an array of all zeros"""
result = F.hprewitt(np.zeros((10, 10)), np.ones((10, 10), bool))
assert (np.all(result == 0))
def test_hprewitt_vertical():
"""Horizontal prewitt on a vertical edge should be zero."""
i, j = np.mgrid[-5:6, -5:6]
image = (j >= 0).astype(float)
result = F.hprewitt(image)
assert_allclose(result, 0, atol=1e-10)
def test_00_00_zeros(self):
"""Horizontal sobel on an array of all zeros"""
result = F.hprewitt(np.zeros((10, 10)), np.ones((10, 10), bool))
assert (np.all(result == 0))