Python skimage.data.camera() Examples

The following are 5 code examples of skimage.data.camera(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module skimage.data , or try the search function .
Example #1
Source File: MR.py    From mr_saliency with GNU General Public License v2.0 5 votes vote down vote up 
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()
Example #2
Source File: test_graphs.py    From pygsp with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
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])
Example #3
Source File: test_plotting.py    From pygsp with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def setUpClass(cls):
        cls._img = img_as_float(data.camera()[::16, ::16])
Example #4
Source File: profile_torchkbnufft.py    From torchkbnufft with MIT License 4 votes vote down vote up 
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)
Example #5
Source File: MR.py    From mr_saliency with GNU General Public License v2.0 4 votes vote down vote up 
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()