def staves(self):
"""The staves detected for a single staffline distance.
Returns:
A staves tensor of shape (N, 2, 2).
"""
height = tf.shape(self.image)[0]
width = tf.shape(self.image)[1]
staff_center = staves_filter.staff_center_filter(
self.image, self.estimated_staffline_distance,
self.estimated_staffline_thickness)
all_thetas = tf.linspace(math.pi / 2 - self.max_abs_theta,
math.pi / 2 + self.max_abs_theta,
self.num_theta)
hough_bins = hough.hough_lines(staff_center, all_thetas)
staff_rhos, staff_thetas = hough.hough_peaks(
hough_bins,
all_thetas,
minval=MIN_STAFF_SLICES * tf.cast(width, tf.float32),
invalidate_distance=self.estimated_staffline_distance * 4)
num_staves = tf.shape(staff_rhos)[0]
# Interpolate the start and end points for the staff center line.
x0 = tf.zeros([num_staves], tf.int32)
y0 = tf.cast(
tf.cast(staff_rhos, tf.float32) / tf.sin(staff_thetas), tf.int32)
x1 = tf.fill([num_staves], width - 1)
y1 = tf.cast((tf.cast(staff_rhos, tf.float32) -
tf.cast(width - 1, tf.float32) * tf.cos(staff_thetas)) /
tf.sin(staff_thetas), tf.int32)
# Cut out staves which have a start or end y outside of the image.
is_valid = tf.logical_and(tf.logical_and(0 <= y0, y0 < height),
tf.logical_and(0 <= y1, y1 < height))
staves = tf.reshape(tf.stack([x0, y0, x1, y1], axis=1), [-1, 2, 2])
return tf.boolean_mask(staves, is_valid)
def testHoughPeaks_minvalTooLarge(self):
image = np.asarray(
[[0, 0, 0, 0, 0],
[0, 1, 1, 1, 0],
[0, 0, 0, 0, 0]]) # pyformat: disable
thetas = np.linspace(0, np.pi / 2, 17)
hough_bins = hough.hough_lines(image, thetas)
peak_rho_t, peak_theta_t = hough.hough_peaks(hough_bins, thetas, minval=3.1)
with self.test_session() as sess:
peak_rho, peak_theta = sess.run((peak_rho_t, peak_theta_t))
self.assertEqual(peak_rho.shape, (0,))
self.assertEqual(peak_theta.shape, (0,))
def testHoughPeaks_verticalLines(self):
image = np.asarray(
[[0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 1, 0, 0, 0],
[0, 1, 0, 0, 1, 0, 0, 0],
[0, 1, 0, 0, 0, 1, 0, 0],
[0, 1, 0, 0, 0, 1, 0, 0],
[0, 1, 0, 0, 0, 0, 1, 0],
[0, 1, 0, 0, 0, 0, 1, 0]]) # pyformat: disable
# Test the full range of angles.
thetas = np.linspace(-np.pi, np.pi, 101)
hough_bins = hough.hough_lines(image, thetas)
peak_rho_t, peak_theta_t = hough.hough_peaks(hough_bins, thetas)
with self.test_session() as sess:
peak_rho, peak_theta = sess.run((peak_rho_t, peak_theta_t))
# Vertical line
self.assertEqual(peak_rho[0], 1)
self.assertAlmostEqual(peak_theta[0], 0)
# Rotated line
self.assertEqual(peak_rho[1], 3)
self.assertAlmostEqual(peak_theta[1], -np.pi / 8, places=1)