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BUG: fix test images (float images between 0 and 1).

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Tony S Yu
2012-05-09 18:35:38 -04:00
parent d19d45850f
commit 7326b1949f
1 changed files with 21 additions and 15 deletions
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skimage/feature/tests/test_template.py
+21 -15
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@@ -7,15 +7,14 @@ from skimage.feature import match_template, peak_local_max
def test_template():
size = 100
# Type conversion of image and target not required but prevents warnings.
image = np.zeros((400, 400), dtype=np.float32)
target = np.tri(size) + np.tri(size)[::-1]
target = target.astype(np.float32)
# Float prefactors ensure that image range is between 0 and 1
image = 0.5 * np.ones((400, 400))
target = 0.1 * (np.tri(size) + np.tri(size)[::-1])
target_positions = [(50, 50), (200, 200)]
for x, y in target_positions:
image[x:x + size, y:y + size] = target
np.random.seed(1)
image += np.random.randn(400, 400) * 2
image += 0.1 * np.random.uniform(size=(400, 400))
result = match_template(image, target)
delta = 5
@@ -46,9 +45,9 @@ def test_normalization():
N = 20
ipos, jpos = (2, 3)
ineg, jneg = (12, 11)
image = np.zeros((N, N))
image[ipos:ipos + n, jpos:jpos + n] = 10
image[ineg:ineg + n, jneg:jneg + n] = -10
image = 0.5 * np.ones((N, N))
image[ipos:ipos + n, jpos:jpos + n] = 1
image[ineg:ineg + n, jneg:jneg + n] = 0
# white square with a black border
template = np.zeros((n+2, n+2))
@@ -79,7 +78,7 @@ def test_no_nans():
explicit check that was added to `match_template`).
"""
np.random.seed(1)
image = 10000 + np.random.normal(size=(20, 20))
image = 0.5 + 1e-9 * np.random.normal(size=(20, 20))
template = np.ones((6, 6))
template[:3, :] = 0
result = match_template(image, template)
@@ -93,14 +92,21 @@ def test_switched_arguments():
def test_pad_input():
template = 10.0 * diamond(2)
"""Test `match_template` when `pad_input=True`.
image = np.zeros((9, 19))
This test places two full templates (one with values lower than the image
mean, the other higher) and two half templates, which are on the edges of
the image. The two full templates should score the top (positive and
negative) matches and the centers of the half templates should score 2nd.
"""
# Float prefactors ensure that image range is between 0 and 1
template = 0.5 * diamond(2)
image = 0.5 * np.ones((9, 19))
mid = slice(2, 7)
image[mid, :3] = -template[:, -3:] # half min template centered at 0
image[mid, 4:9] = template # full max template centered at 6
image[mid, -9:-4] = -template # full min template centered at 12
image[mid, -3:] = template[:, :3] # half max template centered at 18
image[mid, :3] -= template[:, -3:] # half min template centered at 0
image[mid, 4:9] += template # full max template centered at 6
image[mid, -9:-4] -= template # full min template centered at 12
image[mid, -3:] += template[:, :3] # half max template centered at 18
result = match_template(image, template, pad_input=True)