本文整理汇总了Python中menpo.image.Image类的典型用法代码示例。如果您正苦于以下问题:Python Image类的具体用法?Python Image怎么用?Python Image使用的例子?那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
在下文中一共展示了Image类的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_rotate_image_90_180
def test_rotate_image_90_180():
image = Image(np.array([[1., 2., 3., 4.],
[5., 6., 7., 8.],
[9., 10., 11., 12.]]))
image.landmarks['temp'] = PointCloud(np.array([[1., 1.], [1., 2.],
[2., 1.], [2., 2.]]))
# rotate 90 degrees
rotated_img = image.rotate_ccw_about_centre(theta=90, order=0)
rotated_img.landmarks['temp'] = rotated_img.landmarks['temp'].constrain_to_bounds(
rotated_img.bounds())
assert_allclose(rotated_img.pixels, np.array([[[4., 8., 12.],
[3., 7., 11.],
[2., 6., 10.],
[1., 5., 9.]]]))
assert_almost_equal(rotated_img.landmarks['temp'].points,
np.array([[2., 1.], [1., 1.], [2., 2.], [1., 2.]]))
# rotate 180 degrees
rotated_img = image.rotate_ccw_about_centre(theta=180, order=0)
rotated_img.landmarks['temp'] = rotated_img.landmarks['temp'].constrain_to_bounds(
rotated_img.bounds())
assert_allclose(rotated_img.pixels, np.array([[[12., 11., 10., 9.],
[8., 7., 6., 5.],
[4., 3., 2., 1.]]]))
assert_almost_equal(rotated_img.landmarks['temp'].points,
np.array([[1., 2.], [1., 1.], [0., 2.], [0., 1.]]))
示例2: test_image_clip_pixels_cutom_max_uint
def test_image_clip_pixels_cutom_max_uint():
pixels = (np.random.rand(3, 10, 20) * 255).astype(np.uint8)
# add the noise of increased values
pixels[0, 0, 0] = 255
image = Image(pixels, copy=False)
image2 = image.clip_pixels(maximum=200)
assert(image2.pixels.max() <= 200)
示例3: test_image_gradient_sanity
def test_image_gradient_sanity():
# Only a sanity check - does it run and generate sensible output?
image = Image(np.zeros([120, 120, 3]))
new_image = image.gradient()
assert(type(new_image) == Image)
assert(new_image.shape == image.shape)
assert(new_image.n_channels == image.n_channels * 2)
示例4: test_texturedtrimesh_copy
def test_texturedtrimesh_copy():
points = np.ones([10, 3])
tcoords = np.ones([10, 3])
trilist = np.ones([10, 3])
landmarks = PointCloud(np.ones([3, 3]), copy=False)
landmarks_im = PointCloud(np.ones([3, 2]), copy=False)
pixels = np.ones([10, 10, 1])
texture = Image(pixels, copy=False)
texture.landmarks['test_im'] = landmarks_im
ttmesh = TexturedTriMesh(points, tcoords, texture, trilist=trilist,
copy=False)
ttmesh.landmarks['test'] = landmarks
ttmesh_copy = ttmesh.copy()
assert (not is_same_array(ttmesh_copy.points, ttmesh.points))
assert (not is_same_array(ttmesh_copy.trilist, ttmesh.trilist))
assert (not is_same_array(ttmesh_copy.tcoords.points,
ttmesh.tcoords.points))
assert (not is_same_array(ttmesh_copy.texture.pixels,
ttmesh.texture.pixels))
assert (not is_same_array(
ttmesh_copy.texture.landmarks['test_im'].lms.points,
ttmesh.texture.landmarks['test_im'].lms.points))
assert (not is_same_array(ttmesh_copy.landmarks['test'].lms.points,
ttmesh.landmarks['test'].lms.points))
示例5: test_image_from_vector_inplace_no_copy_warning
def test_image_from_vector_inplace_no_copy_warning():
pixels = np.random.rand(10, 20, 2)
pixels2 = np.random.rand(10, 20, 2)
image = Image(pixels)
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
image.from_vector_inplace(pixels2.ravel()[::-1], copy=False)
assert len(w) == 1
示例6: test_as_greyscale_average
def test_as_greyscale_average():
ones = np.ones([3, 120, 120])
image = Image(ones, copy=True)
image.pixels[0].fill(0.5)
new_image = image.as_greyscale(mode='average')
assert (new_image.shape == image.shape)
assert (new_image.n_channels == 1)
assert_allclose(new_image.pixels[0], ones[0] * 0.83333333)
示例7: test_normalize_std_image
def test_normalize_std_image():
pixels = np.ones((3, 120, 120))
pixels[0] = 0.5
pixels[1] = 0.2345
image = Image(pixels)
image.normalize_std_inplace()
assert_allclose(np.mean(image.pixels), 0, atol=1e-10)
assert_allclose(np.std(image.pixels), 1)
示例8: test_normalize_norm_image
def test_normalize_norm_image():
pixels = np.ones((3, 120, 120))
pixels[0] = 0.5
pixels[1] = 0.2345
image = Image(pixels)
new_image = image.normalize_norm()
assert_allclose(np.mean(new_image.pixels), 0, atol=1e-10)
assert_allclose(np.linalg.norm(new_image.pixels), 1)
示例9: test_normalize_norm_image
def test_normalize_norm_image():
pixels = np.ones((120, 120, 3))
pixels[..., 0] = 0.5
pixels[..., 1] = 0.2345
image = Image(pixels)
image.normalize_norm_inplace()
assert_allclose(np.mean(image.pixels), 0, atol=1e-10)
assert_allclose(np.linalg.norm(image.pixels), 1)
示例10: test_copy_landmarks_and_path_with_no_lms_path
def test_copy_landmarks_and_path_with_no_lms_path():
img = Image.init_blank((5, 5))
new_img = Image.init_blank((5, 5))
copy_landmarks_and_path(img, new_img)
assert not hasattr(img, "path")
assert not hasattr(new_img, "path")
assert not img.has_landmarks
assert not new_img.has_landmarks
示例11: test_as_greyscale_luminosity
def test_as_greyscale_luminosity():
ones = np.ones([3, 120, 120])
image = Image(ones, copy=True)
image.pixels[0].fill(0.5)
new_image = image.as_greyscale(mode="luminosity")
assert new_image.shape == image.shape
assert new_image.n_channels == 1
assert_allclose(new_image.pixels[0], ones[0] * 0.850532)
示例12: test_image_copy
def test_image_copy():
pixels = np.ones([1, 10, 10])
landmarks = PointCloud(np.ones([3, 2]), copy=False)
im = Image(pixels, copy=False)
im.landmarks['test'] = landmarks
im_copy = im.copy()
assert (not is_same_array(im.pixels, im_copy.pixels))
assert (not is_same_array(im_copy.landmarks['test'].points,
im.landmarks['test'].points))
示例13: test_normalize_norm_image
def test_normalize_norm_image():
pixels = np.ones((3, 120, 120))
pixels[0] = 0.5
pixels[1] = 0.2345
image = Image(pixels)
with warnings.catch_warnings():
warnings.simplefilter("ignore")
new_image = image.normalize_norm()
assert_allclose(np.mean(new_image.pixels), 0, atol=1e-10)
assert_allclose(np.linalg.norm(new_image.pixels), 1)
示例14: test_normalize_std_image_per_channel
def test_normalize_std_image_per_channel():
pixels = np.random.randn(3, 120, 120)
pixels[1] *= 9
pixels[0] += -3
pixels[2] /= 140
image = Image(pixels)
image.normalize_std_inplace(mode='per_channel')
assert_allclose(
np.mean(image.as_vector(keep_channels=True), axis=1), 0, atol=1e-10)
assert_allclose(
np.std(image.as_vector(keep_channels=True), axis=1), 1)
示例15: test_normalize_norm_image_per_channel
def test_normalize_norm_image_per_channel():
pixels = np.random.randn(120, 120, 3)
pixels[..., 1] *= 17
pixels[..., 0] += -114
pixels[..., 2] /= 30
image = Image(pixels)
image.normalize_norm_inplace(mode='per_channel')
assert_allclose(
np.mean(image.as_vector(keep_channels=True), axis=0), 0, atol=1e-10)
assert_allclose(
np.linalg.norm(image.as_vector(keep_channels=True), axis=0), 1)