本文整理汇总了Python中menpo.image.Image.as_vector方法的典型用法代码示例。如果您正苦于以下问题：Python Image.as_vector方法的具体用法？Python Image.as_vector怎么用？Python Image.as_vector使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类menpo.image.Image的用法示例。
在下文中一共展示了Image.as_vector方法的5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_normalize_norm_image_per_channel
# 需要导入模块: from menpo.image import Image [as 别名]
# 或者: from menpo.image.Image import as_vector [as 别名]
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)示例2: test_normalize_std_image_per_channel
# 需要导入模块: from menpo.image import Image [as 别名]
# 或者: from menpo.image.Image import as_vector [as 别名]
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3: test_image_as_vector_keep_channels
# 需要导入模块: from menpo.image import Image [as 别名]
# 或者: from menpo.image.Image import as_vector [as 别名]
def test_image_as_vector_keep_channels():
pixels = np.random.rand(10, 20, 2)
image = Image(pixels)
assert(np.all(image.as_vector(keep_channels=True) ==
pixels.reshape([-1, 2])))示例4: test_image_as_vector
# 需要导入模块: from menpo.image import Image [as 别名]
# 或者: from menpo.image.Image import as_vector [as 别名]
def test_image_as_vector():
pixels = np.random.rand(10, 20, 1)
image = Image(pixels)
assert(np.all(image.as_vector() == pixels.ravel()))示例5: test_image_as_vector_keep_channels
# 需要导入模块: from menpo.image import Image [as 别名]
# 或者: from menpo.image.Image import as_vector [as 别名]
def test_image_as_vector_keep_channels():
pixels = np.random.rand(2, 10, 20)
image = Image(pixels)
assert np.all(image.as_vector(keep_channels=True) == pixels.reshape([2, -1]))