def test_imread_flatten():
# a color image is flattened and returned as float32
img = imread(os.path.join(data_dir, 'color.png'), flatten=True)
assert img.dtype == np.float32
img = imread(os.path.join(data_dir, 'camera.png'), flatten=True)
# check that flattening does not occur for an image that is grey already.
assert np.sctype2char(img.dtype) in np.typecodes['AllInteger']
def test_imread_flatten():
# a color image is flattened
img = imread(os.path.join(data_dir, 'color.png'), flatten=True)
assert img.ndim == 2
assert img.dtype == np.float64
img = imread(os.path.join(data_dir, 'camera.png'), flatten=True)
# check that flattening does not occur for an image that is grey already.
assert np.sctype2char(img.dtype) in np.typecodes['AllInteger']
def main():
import scikits.image.io as io
import sys
if len(sys.argv) < 2:
print "Usage: scivi <image-file> [<flip-file>]"
sys.exit(-1)
io.use_plugin('qt2')
im = io.imread(sys.argv[1])
flip = None
if len(sys.argv) > 2:
flip = io.imread(sys.argv[2])
io.imshow(im, flip=flip, fancy=True)
io.show()
def roundtrip(self, dtype, x, scaling=1):
f = NamedTemporaryFile(suffix='.png')
imsave(f.name, x)
f.seek(0)
y = imread(f.name)
assert_array_almost_equal((x * scaling).astype(np.int32), y)
def roundtrip(self, dtype, x, scaling=1):
f = NamedTemporaryFile(suffix='.png')
fname = f.name
f.close()
imsave(fname, x)
y = imread(fname)
assert_array_almost_equal((x * scaling).astype(np.int32), y)
def plot_snake_overlay():
plt.figure()
logo = ScipyLogo((670, 250), 250)
logo.plot_snake_curve()
logo.plot_circle()
img = imgio.imread('data/snake_pixabay.jpg')
#mask = logo.get_mask(img.shape, 'upper left')
#img[mask] = 255
plt.imshow(img)
def main():
import scikits.image.io as io
import sys
if len(sys.argv) != 2:
print "Usage: scivi <image-file>"
sys.exit(-1)
io.use_plugin("qt")
io.imshow(io.imread(sys.argv[1]), fancy=True)
io.show()
def main():
import scikits.image.io as io
import sys
if len(sys.argv) != 2:
print "Usage: scivi <image-file>"
sys.exit(-1)
io.use_plugin('qt')
io.imshow(io.imread(sys.argv[1]), fancy=True)
io.show()
def __init__(self):
self.radius = 250
self.origin = (420, 0)
img = sio.imread('data/snake_pixabay.jpg')
img = self._crop_image(img)
img = img.astype(float) * 1.1
img[img > 255] = 255
self.img = img.astype(np.uint8)
LogoBase.__init__(self)
def load_image(self, filename, var_name, dtype='uint8'):
dt = np.uint8
if dtype == 'uint8':
dt = np.uint8
elif dtype == 'float32':
dt = np.float32
elif dtype == 'float64':
dt = np.float64
elif dtype == 'int8':
dt = np.int8
elif dtype == 'int32':
dt = np.int32
filename = str(filename)
var_name = str(var_name)
arr = imread(os.path.join(self.folder, filename), dtype=dt)
self.vars[var_name] = arr
import os
import scikits.image as si
import scikits.image.io as sio
sio.use_plugin('matplotlib', 'imshow')
sio.use_plugin('freeimage', 'imread')
img = sio.imread(os.path.join(si.data_dir, 'color.png'))
sio.imshow(img)
sio.show()
def test_imread_palette():
img = imread(os.path.join(data_dir, 'palette_gray.png'))
assert img.ndim == 2
img = imread(os.path.join(data_dir, 'palette_color.png'))
assert img.ndim == 3
def test_read(self):
io.imread('test.png', as_grey=True, dtype='i4', plugin='test')
# TODO: simpler imshow, without complete GUI
return _advanced_imshow(im, flip=flip, mgr=mgr)
def _advanced_imshow(im, flip=None, mgr=None):
return AdvancedImageViewerApp(im, flip=flip, mgr=mgr)
if __name__ == "__main__":
from scikits.image.filter import tvdenoise
from scikits.image.io import imread, imshow
import numpy.random as npr
import os, os.path
import sys
app = QApplication(sys.argv)
if len(sys.argv) > 1:
image = imread(sys.argv[1])
else:
import scipy
image = scipy.lena()
flip = None
if len(sys.argv) > 2:
flip = imread(sys.argv[2])
viewer = _advanced_imshow(image, flip=flip, mgr=None)
viewer.show()
sys.exit(app.exec_())
# Source coordinates
sc = np.array(plt.ginput(n=4))
screen_coords = [(0, 0),
(1023, 0),
(1023, 767),
(0, 767)]
# Homography: source to camera
H_SC = estimate_homography(screen_coords, sc)
tc = np.array(plt.ginput(n=4))
print tc
tc_in_screen = \
np.dot(np.linalg.inv(H_SC),
np.hstack((tc, np.ones((4,1)))).T).T
tc_in_screen /= tc_in_screen[:, 2, np.newaxis]
# Screen to screen homography
H_SS = estimate_homography(screen_coords,
tc_in_screen)
grid = sio.imread('fatgrid.jpg')
grid_warp = tf.homography(grid, H_SS,
output_shape=grid.shape,
order=2)
np.save('/tmp/H_SS.npy', H_SS)
sio.imsave('/tmp/grid_warp.png', grid_warp)
def test_imread_simple():
io.use_plugin('fits')
testfile = os.path.join(data_dir, 'simple.fits')
img = io.imread(testfile)
assert np.all(img == pyfits.getdata(testfile, 0))
def test_read(self):
io.imread('test.png', as_grey=True, dtype='i4', plugin='test')
self.setTextSizeMultiplier(m)
elif control and c == Qt.Key_0:
self.setTextSizeMultiplier(1.05)
if __name__ == "__main__":
folder = "image_denoising_tutorial"
if len(sys.argv) > 1:
folder = sys.argv[1]
app = QApplication(sys.argv)
if False:
viewer = WebImageViewer()
image = imread(folder+'/data/lena512.tif')
image_noise = image + npr.randn(image.size).reshape(image.shape)*29
viewer.show_image(image, image_noise)
viewer.show()
else:
global_settings = QWebSettings.globalSettings()
global_settings.setAttribute(QWebSettings.PluginsEnabled, True)
view = Browser(folder)
page = view.page()
frame = page.mainFrame()
factory = WebPluginFactory(frame)
page.setPluginFactory(factory)
window = QMainWindow()
def test_imread_simple():
io.use_plugin('fits')
testfile = os.path.join(data_dir, 'simple.fits')
img = io.imread(testfile)
assert np.all(img==pyfits.getdata(testfile, 0))
class TestColorconv(TestCase):
img_rgb = imread(os.path.join(data_dir, 'color.png'))
img_grayscale = imread(os.path.join(data_dir, 'camera.png'))
colbars = np.array([[1, 1, 0, 0, 1, 1, 0, 0], [1, 1, 1, 1, 0, 0, 0, 0],
[1, 0, 1, 0, 1, 0, 1, 0]])
colbars_array = np.swapaxes(colbars.reshape(3, 4, 2), 0, 2)
colbars_point75 = colbars * 0.75
colbars_point75_array = np.swapaxes(colbars_point75.reshape(3, 4, 2), 0, 2)
# RGB to HSV
def test_rgb2hsv_conversion(self):
rgb = self.img_rgb.astype("float32")[::16, ::16]
hsv = rgb2hsv(rgb).reshape(-1, 3)
# ground truth from colorsys
gt = np.array([
colorsys.rgb_to_hsv(pt[0], pt[1], pt[2])
for pt in rgb.reshape(-1, 3)
])
assert_almost_equal(hsv, gt)
def test_rgb2hsv_error_grayscale(self):
self.assertRaises(ValueError, rgb2hsv, self.img_grayscale)
def test_rgb2hsv_error_one_element(self):
self.assertRaises(ValueError, rgb2hsv, self.img_rgb[0, 0])
# HSV to RGB
def test_hsv2rgb_conversion(self):
rgb = self.img_rgb.astype("float32")[::16, ::16]
# create HSV image with colorsys
hsv = np.array([
colorsys.rgb_to_hsv(pt[0], pt[1], pt[2])
for pt in rgb.reshape(-1, 3)
]).reshape(rgb.shape)
# convert back to RGB and compare with original.
# relative precision for RGB -> HSV roundtrip is about 1e-6
assert_almost_equal(rgb, hsv2rgb(hsv), decimal=4)
def test_hsv2rgb_error_grayscale(self):
self.assertRaises(ValueError, hsv2rgb, self.img_grayscale)
def test_hsv2rgb_error_one_element(self):
self.assertRaises(ValueError, hsv2rgb, self.img_rgb[0, 0])
# RGB to XYZ
def test_rgb2xyz_conversion(self):
gt = np.array([[[0.950456, 1., 1.088754],
[0.538003, 0.787329, 1.06942],
[0.592876, 0.28484, 0.969561],
[0.180423, 0.072169, 0.950227]],
[[0.770033, 0.927831, 0.138527],
[0.35758, 0.71516, 0.119193],
[0.412453, 0.212671, 0.019334], [0., 0., 0.]]])
assert_almost_equal(rgb2xyz(self.colbars_array), gt)
# stop repeating the "raises" checks for all other functions that are
# implemented with color._convert()
def test_rgb2xyz_error_grayscale(self):
self.assertRaises(ValueError, rgb2xyz, self.img_grayscale)
def test_rgb2xyz_error_one_element(self):
self.assertRaises(ValueError, rgb2xyz, self.img_rgb[0, 0])
# XYZ to RGB
def test_xyz2rgb_conversion(self):
# only roundtrip test, we checked rgb2xyz above already
assert_almost_equal(xyz2rgb(rgb2xyz(self.colbars_array)),
self.colbars_array)
# RGB to RGB CIE
def test_rgb2rgbcie_conversion(self):
gt = np.array([[[0.1488856, 0.18288098, 0.19277574],
[0.01163224, 0.16649536, 0.18948516],
[0.12259182, 0.03308008, 0.17298223],
[-0.01466154, 0.01669446, 0.16969164]],
[[0.16354714, 0.16618652, 0.0230841],
[0.02629378, 0.1498009, 0.01979351],
[0.13725336, 0.01638562, 0.00329059], [0., 0., 0.]]])
assert_almost_equal(rgb2rgbcie(self.colbars_array), gt)
# RGB CIE to RGB
def test_rgbcie2rgb_conversion(self):
# only roundtrip test, we checked rgb2rgbcie above already
assert_almost_equal(rgbcie2rgb(rgb2rgbcie(self.colbars_array)),
self.colbars_array)
def test_convert_colorspace(self):
colspaces = ['HSV', 'RGB CIE', 'XYZ']
colfuncs_from = [hsv2rgb, rgbcie2rgb, xyz2rgb]
colfuncs_to = [rgb2hsv, rgb2rgbcie, rgb2xyz]
assert_almost_equal(
convert_colorspace(self.colbars_array, 'RGB', 'RGB'),
self.colbars_array)
for i, space in enumerate(colspaces):
gt = colfuncs_from[i](self.colbars_array)
assert_almost_equal(
convert_colorspace(self.colbars_array, space, 'RGB'), gt)
gt = colfuncs_to[i](self.colbars_array)
assert_almost_equal(
convert_colorspace(self.colbars_array, 'RGB', space), gt)
self.assertRaises(ValueError, convert_colorspace, self.colbars_array,
'nokey', 'XYZ')
self.assertRaises(ValueError, convert_colorspace, self.colbars_array,
'RGB', 'nokey')
def test_rgb2grey(self):
x = np.array([1, 1, 1]).reshape((1, 1, 3))
g = rgb2grey(x)
assert_array_almost_equal(g, 1)
assert_equal(g.shape, (1, 1))
from scikits.image import io, transform
s = 0.7
img = io.imread('scikits_image_logo.png')
h, w, c = img.shape
print "\nScaling down logo by %.1fx..." % s
img = transform.homography(img, [[s, 0, 0],
[0, s, 0],
[0, 0, 1]],
output_shape=(int(h*s), int(w*s), 4),
order=3)
io.imsave('scikits_image_logo_small.png', img)
def __init__(self):
self.radius = 250
self.origin = (420, 0)
img = imgio.imread('data/snake_pixabay.jpg')
self.img = self._crop_image(img)
LogoBase.__init__(self)
def plot_image(self, **kwargs):
ax = kwargs.pop('ax', plt.gca())
img = imgio.imread('data/scipy.png')
ax.imshow(img, **kwargs)
def test_read(self):
io.imread("test.png", as_grey=True, dtype="i4", plugin="test")
indxs = shift.astype(np.int);
bincount = np.bincount(indxs);
map[:len(bincount),i] = bincount
return map,theta,bins;
if __name__ == '__main__':
if len(sys.argv)==1:
print "\nUsage: %s <binary_image> [back_image] ";
sys.exit(1);
img_bin = io.imread(sys.argv[1]);
try:
img = io.imread(sys.argv[2]);
except:
img = None;
theta = np.linspace(-np.pi,np.pi,90);
coeffs,theta,bins = hough(img_edge,theta);
rav_indxs = coeffs.argsort(axis=None)[-15:];
bin_theta_indxs = [ np.unravel_index(i,coeffs.shape) for i in rav_indxs ];
pts = [];
for bin_idx,theta_idx in bin_theta_indxs:
def test_imread_palette():
img = imread(os.path.join(data_dir, 'palette_gray.png'))
assert img.ndim == 2
img = imread(os.path.join(data_dir, 'palette_color.png'))
assert img.ndim == 3
def test_imread_MEF():
io.use_plugin('fits')
testfile = os.path.join(data_dir, 'multi.fits')
img = io.imread(testfile)
assert np.all(img == pyfits.getdata(testfile, 1))
self.axes = axes
axes.add_patch(self.patch)
def paint(self):
self.patch.set_x(self.x)
self.patch.set_y(self.y)
# This is probably not the right call. Should call redraw on canvas?
plt.draw()
print self.name
for fn in args:
try:
img = sio.imread(fn, as_grey=True)/255.
except IOError:
print "Could not open file '%s'." % fn
continue
plt.imshow(img, cmap=plt.cm.gray)
c = Canvas(name=('.'.join(fn.split('.')[:-1]).split('/')[-1]),
img=img,
patch_size=SIZE,
axes=plt.gca())
plt.title('Click anywhere to move the region of interest. Press any "c" '
'to crop.')
plt.connect('key_press_event', crop_factory(c))
plt.connect('button_press_event', set_roi_factory(c))
plt.show()
def test_imread_dtype():
img = imread(os.path.join(data_dir, 'camera.png'), dtype=np.float64)
assert img.dtype == np.float64
self.axes = axes
axes.add_patch(self.patch)
def paint(self):
self.patch.set_x(self.x)
self.patch.set_y(self.y)
# This is probably not the right call. Should call redraw on canvas?
plt.draw()
print self.name
for fn in args:
try:
img = sio.imread(fn, as_grey=True) / 255.
except IOError:
print "Could not open file '%s'." % fn
continue
plt.imshow(img, cmap=plt.cm.gray)
c = Canvas(name=('.'.join(fn.split('.')[:-1]).split('/')[-1]),
img=img,
patch_size=SIZE,
axes=plt.gca())
plt.title('Click anywhere to move the region of interest. Press any "c" '
'to crop.')
plt.connect('key_press_event', crop_factory(c))
plt.connect('button_press_event', set_roi_factory(c))
plt.show()
def test_imread_MEF():
io.use_plugin('fits')
testfile = os.path.join(data_dir, 'multi.fits')
img = io.imread(testfile)
assert np.all(img==pyfits.getdata(testfile, 1))
