本文整理汇总了Python中skimage.data.camera方法的典型用法代码示例。如果您正苦于以下问题：Python data.camera方法的具体用法？Python data.camera怎么用？Python data.camera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skimage.data的用法示例。
在下文中一共展示了data.camera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: MR_showsuperpixel
# 需要导入模块: from skimage import data [as 别名]
# 或者: from skimage.data import camera [as 别名]
def MR_showsuperpixel(self,img=None):
if img == None:
img = cv2.cvtColor(camera(),cv2.COLOR_RGB2BGR)
img = self._MR_saliency__MR_readimg(img)
labels = self._MR_saliency__MR_superpixel(img)
plt.axis('off')
plt.imshow(mark_boundaries(img,labels))
plt.show() 示例2: setUpClass
# 需要导入模块: from skimage import data [as 别名]
# 或者: from skimage.data import camera [as 别名]
def setUpClass(cls):
cls._G = graphs.Logo()
cls._G.compute_fourier_basis()
cls._rs = np.random.RandomState(42)
cls._signal = cls._rs.uniform(size=cls._G.N)
cls._img = img_as_float(data.camera()[::16, ::16]) 示例3: setUpClass
# 需要导入模块: from skimage import data [as 别名]
# 或者: from skimage.data import camera [as 别名]
def setUpClass(cls):
cls._img = img_as_float(data.camera()[::16, ::16]) 示例4: run_all_profiles
# 需要导入模块: from skimage import data [as 别名]
# 或者: from skimage.data import camera [as 别名]
def run_all_profiles():
print('running profiler...')
spokelength = 512
nspokes = 405
ncoil = 15
print('problem size (radial trajectory, 2-factor oversampling):')
print('number of coils: {}'.format(ncoil))
print('number of spokes: {}'.format(nspokes))
print('spokelength: {}'.format(spokelength))
# create an example to run on
image = np.array(Image.fromarray(camera()).resize((256, 256)))
image = image.astype(np.complex)
im_size = image.shape
image = np.stack((np.real(image), np.imag(image)))
image = torch.tensor(image).unsqueeze(0).unsqueeze(0)
# create k-space trajectory
ga = np.deg2rad(180 / ((1 + np.sqrt(5)) / 2))
kx = np.zeros(shape=(spokelength, nspokes))
ky = np.zeros(shape=(spokelength, nspokes))
ky[:, 0] = np.linspace(-np.pi, np.pi, spokelength)
for i in range(1, nspokes):
kx[:, i] = np.cos(ga) * kx[:, i - 1] - np.sin(ga) * ky[:, i - 1]
ky[:, i] = np.sin(ga) * kx[:, i - 1] + np.cos(ga) * ky[:, i - 1]
ky = np.transpose(ky)
kx = np.transpose(kx)
ktraj = np.stack((ky.flatten(), kx.flatten()), axis=0)
ktraj = torch.tensor(ktraj).unsqueeze(0)
smap_sz = (1, ncoil, 2) + im_size
smap = torch.ones(*smap_sz)
profile_torchkbnufft(image, ktraj, smap, im_size, device=torch.device(
'cpu'), sparse_mats_flag=False)
profile_torchkbnufft(image, ktraj, smap, im_size, device=torch.device(
'cpu'), sparse_mats_flag=True)
profile_torchkbnufft(image, ktraj, smap, im_size, device=torch.device(
'cpu'), use_toep=True)
profile_torchkbnufft(image, ktraj, smap, im_size, device=torch.device(
'cuda'), sparse_mats_flag=False)
profile_torchkbnufft(image, ktraj, smap, im_size, device=torch.device(
'cuda'), sparse_mats_flag=True)
profile_torchkbnufft(image, ktraj, smap, im_size, device=torch.device(
'cuda'), use_toep=True) 示例5: MR_boundary_saliency
# 需要导入模块: from skimage import data [as 别名]
# 或者: from skimage.data import camera [as 别名]
def MR_boundary_saliency(self,img=None):
if img == None:
img = cv2.cvtColor(camera(),cv2.COLOR_RGB2BGR)
lab_img = self._MR_saliency__MR_readimg(img)
labels = self._MR_saliency__MR_superpixel(lab_img)
up,right,low,left = self._MR_saliency__MR_boundary_indictor(labels)
aff = self._MR_saliency__MR_affinity_matrix(lab_img,labels)
up_sal = 1- self._MR_saliency__MR_saliency(aff,up)
up_img = self._MR_saliency__MR_fill_superpixel_with_saliency(labels,up_sal)
up_img = up_img.astype(np.uint8)
right_sal = 1-self._MR_saliency__MR_saliency(aff,right)
right_img = self._MR_saliency__MR_fill_superpixel_with_saliency(labels,right_sal)
right_img = right_img.astype(np.uint8)
low_sal = 1-self._MR_saliency__MR_saliency(aff,low)
low_img = self._MR_saliency__MR_fill_superpixel_with_saliency(labels,low_sal)
low_img = low_img.astype(np.uint8)
left_sal = 1-self._MR_saliency__MR_saliency(aff,left)
left_img = self._MR_saliency__MR_fill_superpixel_with_saliency(labels,left_sal)
left_img = left_img.astype(np.uint8)
plt.subplot(3,2,1)
plt.title('orginal')
plt.axis('off')
plt.imshow(cv2.cvtColor(img,cv2.COLOR_BGR2RGB))
plt.subplot(3,2,2)
plt.title('up')
plt.axis('off')
plt.imshow(up_img,'gray')
plt.subplot(3,2,3)
plt.title('right')
plt.axis('off')
plt.imshow(right_img,'gray')
plt.subplot(3,2,4)
plt.title('low')
plt.axis('off')
plt.imshow(low_img,'gray')
plt.subplot(3,2,5)
plt.title('left')
plt.axis('off')
plt.imshow(left_img,'gray')
plt.subplot(3,2,6)
plt.title('integrated')
plt.axis('off')
saliency_map = MR_debuger().saliency(img).astype(np.uint8)
plt.imshow( saliency_map,'gray')
plt.show()