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FIX: handle correctly main axis def

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François Boulogne
2013-08-06 19:38:03 +02:00
parent 7c652c74d0
commit e27b798ffa
2 changed files with 160 additions and 30 deletions
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skimage/transform/_hough_transform.pyx
+6 -7
View File
@@ -123,8 +123,8 @@ def hough_ellipse(cnp.ndarray img, int threshold=4, double accuracy=1,
Returns
-------
res : list of tuples [(accumulator, x0, y0, a, b, angle)]
Where (x0, y0) is the center, (a, b) major and minor axis.
res : list of tuples [(accumulator, y0, x0, ry, rx, angle)]
Where (y0, x0) is the center, (ry, rx) main axis.
The angle value follows `draw.ellipse_perimeter()` convention.
Examples
@@ -135,7 +135,7 @@ def hough_ellipse(cnp.ndarray img, int threshold=4, double accuracy=1,
>>> result = hough_ellipse(img, threshold=4)
>>> # extract the highest accumulator
>>> heapq.nlargest(1, result)
[(10, 10.0, 10.0, 8.0, 6.0, 0.0)]
[(10, 10.0, 10.0, 6.0, 8.0, 0.0)]
>>> # To sort them all
>>> results = [heappop(results) for i in range(len(results))]
@@ -211,6 +211,7 @@ def hough_ellipse(cnp.ndarray img, int threshold=4, double accuracy=1,
hist_max = np.max(hist)
if hist_max > threshold:
angle = np.arctan2(p1x - p2x, p1y - p2y)
b = sqrt(bin_edges[hist.argmax()])
# to keep ellipse_perimeter() convention
if angle != 0:
angle = np.pi - angle
@@ -219,13 +220,11 @@ def hough_ellipse(cnp.ndarray img, int threshold=4, double accuracy=1,
# that a < b. But we keep a > b.
if angle > np.pi:
angle = angle - np.pi / 2.
elif angle < - np.pi:
angle = angle + np.pi / 2.
b = sqrt(bin_edges[hist.argmax()])
a, b = b, a
heapq.heappush(results,
(hist_max, # Accumulator
x0,
y0,
x0,
a,
b,
angle,
skimage/transform/tests/test_hough_transform.py
+154 -23
View File
@@ -150,56 +150,187 @@ def test_hough_circle_extended():
def test_hough_ellipse_zero_angle():
img = np.zeros((25, 25), dtype=int)
a = 6
b = 8
rx = 6
ry = 8
x0 = 12
y0 = 15
angle = 0
rr, cc = ellipse_perimeter(y0, x0, b, a)
rr, cc = ellipse_perimeter(y0, x0, ry, rx)
img[rr, cc] = 1
result = tf.hough_ellipse(img, threshold=9)
best = heapq.nlargest(1, result)[0]
assert_equal(best[1], x0)
assert_equal(best[2], y0)
assert_almost_equal(best[3], b, decimal=1)
assert_almost_equal(best[4], a, decimal=1)
assert_equal(best[1], y0)
assert_equal(best[2], x0)
assert_almost_equal(best[3], ry, decimal=1)
assert_almost_equal(best[4], rx, decimal=1)
assert_equal(best[5], angle)
# Check if I re-draw the ellipse, points are the same!
# ie check API compatibility between hough_ellipse and ellipse_perimeter
rr2, cc2 = ellipse_perimeter(y0, x0, int(best[3]), int(best[4]), orientation=best[5])
assert_equal(rr, rr2)
assert_equal(cc, cc2)
def test_hough_ellipse_non_zero_angle():
def test_hough_ellipse_non_zero_posangle1():
# ry > rx, angle in [0:pi/2]
img = np.zeros((30, 24), dtype=int)
a = 6
b = 12
rx = 6
ry = 12
x0 = 10
y0 = 15
angle = np.pi / 1.35
rr, cc = ellipse_perimeter(y0, x0, b, a, orientation=angle)
rr, cc = ellipse_perimeter(y0, x0, ry, rx, orientation=angle)
img[rr, cc] = 1
result = tf.hough_ellipse(img, threshold=15, accuracy=3)
best = heapq.nlargest(1, result)[0]
assert_almost_equal(best[1] / 100., x0 / 100., decimal=1)
assert_almost_equal(best[2] / 100., y0 / 100., decimal=1)
assert_almost_equal(best[3] / 10., b / 10., decimal=1)
assert_almost_equal(best[4] / 100., a / 100., decimal=1)
assert_almost_equal(best[1] / 100., y0 / 100., decimal=1)
assert_almost_equal(best[2] / 100., x0 / 100., decimal=1)
assert_almost_equal(best[3] / 10., ry / 10., decimal=1)
assert_almost_equal(best[4] / 100., rx / 100., decimal=1)
assert_almost_equal(best[5], angle, decimal=1)
# Check if I re-draw the ellipse, points are the same!
# ie check API compatibility between hough_ellipse and ellipse_perimeter
rr2, cc2 = ellipse_perimeter(y0, x0, int(best[3]), int(best[4]), orientation=best[5])
assert_equal(rr, rr2)
assert_equal(cc, cc2)
def test_hough_ellipse_non_zero_angle2():
def test_hough_ellipse_non_zero_posangle2():
# ry < rx, angle in [0:pi/2]
img = np.zeros((30, 24), dtype=int)
b = 6
a = 12
rx = 12
ry = 6
x0 = 10
y0 = 15
angle = np.pi / 1.35
rr, cc = ellipse_perimeter(y0, x0, b, a, orientation=angle)
rr, cc = ellipse_perimeter(y0, x0, ry, rx, orientation=angle)
img[rr, cc] = 1
result = tf.hough_ellipse(img, threshold=15, accuracy=3)
best = heapq.nlargest(1, result)[0]
assert_almost_equal(best[1] / 100., x0 / 100., decimal=1)
assert_almost_equal(best[2] / 100., y0 / 100., decimal=1)
assert_almost_equal(best[3] / 100., a / 100., decimal=1)
assert_almost_equal(best[4] / 100., b / 100., decimal=1)
assert_almost_equal(best[1] / 100., y0 / 100., decimal=1)
assert_almost_equal(best[2] / 100., x0 / 100., decimal=1)
assert_almost_equal(best[3] / 10., ry / 10., decimal=1)
assert_almost_equal(best[4] / 100., rx / 100., decimal=1)
assert_almost_equal(best[5], angle, decimal=1)
# Check if I re-draw the ellipse, points are the same!
# ie check API compatibility between hough_ellipse and ellipse_perimeter
rr2, cc2 = ellipse_perimeter(y0, x0, int(best[3]), int(best[4]), orientation=best[5])
assert_equal(rr, rr2)
assert_equal(cc, cc2)
def test_hough_ellipse_non_zero_posangle3():
# ry < rx, angle in [pi/2:pi]
img = np.zeros((30, 24), dtype=int)
rx = 12
ry = 6
x0 = 10
y0 = 15
angle = np.pi / 1.35 + np.pi / 2.
rr, cc = ellipse_perimeter(y0, x0, ry, rx, orientation=angle)
img[rr, cc] = 1
result = tf.hough_ellipse(img, threshold=15, accuracy=3)
best = heapq.nlargest(1, result)[0]
# Check if I re-draw the ellipse, points are the same!
# ie check API compatibility between hough_ellipse and ellipse_perimeter
rr2, cc2 = ellipse_perimeter(y0, x0, int(best[3]), int(best[4]), orientation=best[5])
assert_equal(rr, rr2)
assert_equal(cc, cc2)
def test_hough_ellipse_non_zero_posangle4():
# ry < rx, angle in [pi:3pi/4]
img = np.zeros((30, 24), dtype=int)
rx = 12
ry = 6
x0 = 10
y0 = 15
angle = np.pi / 1.35 + np.pi
rr, cc = ellipse_perimeter(y0, x0, ry, rx, orientation=angle)
img[rr, cc] = 1
result = tf.hough_ellipse(img, threshold=15, accuracy=3)
best = heapq.nlargest(1, result)[0]
# Check if I re-draw the ellipse, points are the same!
# ie check API compatibility between hough_ellipse and ellipse_perimeter
rr2, cc2 = ellipse_perimeter(y0, x0, int(best[3]), int(best[4]), orientation=best[5])
assert_equal(rr, rr2)
assert_equal(cc, cc2)
def test_hough_ellipse_non_zero_negangle1():
# ry > rx, angle in [0:-pi/2]
img = np.zeros((30, 24), dtype=int)
rx = 6
ry = 12
x0 = 10
y0 = 15
angle = - np.pi / 1.35
rr, cc = ellipse_perimeter(y0, x0, ry, rx, orientation=angle)
img[rr, cc] = 1
result = tf.hough_ellipse(img, threshold=15, accuracy=3)
best = heapq.nlargest(1, result)[0]
# Check if I re-draw the ellipse, points are the same!
# ie check API compatibility between hough_ellipse and ellipse_perimeter
rr2, cc2 = ellipse_perimeter(y0, x0, int(best[3]), int(best[4]), orientation=best[5])
assert_equal(rr, rr2)
assert_equal(cc, cc2)
def test_hough_ellipse_non_zero_negangle2():
# ry < rx, angle in [0:-pi/2]
img = np.zeros((30, 24), dtype=int)
rx = 12
ry = 6
x0 = 10
y0 = 15
angle = - np.pi / 1.35
rr, cc = ellipse_perimeter(y0, x0, ry, rx, orientation=angle)
img[rr, cc] = 1
result = tf.hough_ellipse(img, threshold=15, accuracy=3)
best = heapq.nlargest(1, result)[0]
# Check if I re-draw the ellipse, points are the same!
# ie check API compatibility between hough_ellipse and ellipse_perimeter
rr2, cc2 = ellipse_perimeter(y0, x0, int(best[3]), int(best[4]), orientation=best[5])
assert_equal(rr, rr2)
assert_equal(cc, cc2)
def test_hough_ellipse_non_zero_negangle3():
# ry < rx, angle in [-pi/2:-pi]
img = np.zeros((30, 24), dtype=int)
rx = 12
ry = 6
x0 = 10
y0 = 15
angle = - np.pi / 1.35 - np.pi / 2.
rr, cc = ellipse_perimeter(y0, x0, ry, rx, orientation=angle)
img[rr, cc] = 1
result = tf.hough_ellipse(img, threshold=15, accuracy=3)
best = heapq.nlargest(1, result)[0]
# Check if I re-draw the ellipse, points are the same!
# ie check API compatibility between hough_ellipse and ellipse_perimeter
rr2, cc2 = ellipse_perimeter(y0, x0, int(best[3]), int(best[4]), orientation=best[5])
assert_equal(rr, rr2)
assert_equal(cc, cc2)
def test_hough_ellipse_non_zero_negangle4():
# ry < rx, angle in [-pi:-3pi/4]
img = np.zeros((30, 24), dtype=int)
rx = 12
ry = 6
x0 = 10
y0 = 15
angle = - np.pi / 1.35 - np.pi
rr, cc = ellipse_perimeter(y0, x0, ry, rx, orientation=angle)
img[rr, cc] = 1
result = tf.hough_ellipse(img, threshold=15, accuracy=3)
best = heapq.nlargest(1, result)[0]
# Check if I re-draw the ellipse, points are the same!
# ie check API compatibility between hough_ellipse and ellipse_perimeter
rr2, cc2 = ellipse_perimeter(y0, x0, int(best[3]), int(best[4]), orientation=best[5])
assert_equal(rr, rr2)
assert_equal(cc, cc2)
if __name__ == "__main__":