def main_show():
"""
Use glumpy to launch a data set viewer.
"""
self = CIFAR10()
Y = [m["label"] for m in self.meta]
glumpy_viewer(img_array=self._pixels, arrays_to_print=[Y], window_shape=(32 * 4, 32 * 4))
def test_imgs():
root = '/home/bergstra/cvs/eccv12/eccv12/tests/data/'
saved_paths = np.load(os.path.join(root, 'fg11_Xraw0-4.npy'))
saved_processed_imgs = np.load(os.path.join(root, 'fg11_X0-4.npy'))
imgs = plugins.get_images('float32', None)
print saved_paths
print saved_processed_imgs.shape
assert saved_processed_imgs[0].shape == imgs[0].shape
# the saved_preprocessed_imgs were designed to include only images
# that appeared in view1, so it is normal that some images are omitted.
assert np.allclose(saved_processed_imgs[0], imgs[0])
assert np.allclose(saved_processed_imgs[1], imgs[1])
assert np.allclose(saved_processed_imgs[2], imgs[3])
if 0:
from skdata.utils.glviewer import glumpy_viewer, command, glumpy
glumpy_viewer(
#img_array=saved_processed_imgs,
img_array=imgs,
arrays_to_print=[saved_paths],
cmap=glumpy.colormap.Grey)
def main_show():
"""
Use glumpy to launch a data set viewer.
"""
self = KaggleFacialExpression()
from skdata.utils.glviewer import glumpy_viewer
glumpy_viewer(img_array=[m["pixels"] for m in self.meta], arrays_to_print=self.meta, window_shape=(48 * 4, 48 * 4))
def show_centroids(D):
D = D.copy()
for di in D:
di -= di.min()
di /= di.max()
glumpy_viewer(
img_array=D.astype('float32'),
arrays_to_print=[],
)
def main_show():
"""
Use glumpy to launch a data set viewer.
"""
self = CIFAR10()
Y = [m['label'] for m in self.meta]
glumpy_viewer(img_array=self._pixels,
arrays_to_print=[Y],
window_shape=(32 * 4, 32 * 4))
def main_show():
"""
Use glumpy to launch a data set viewer.
"""
self = KaggleFacialExpression()
from skdata.utils.glviewer import glumpy_viewer
glumpy_viewer(img_array=[m['pixels'] for m in self.meta],
arrays_to_print=self.meta,
window_shape=(48 * 4, 48 * 4))
def main_show():
"""
Use glumpy to launch a data set viewer.
"""
self = MNIST()
Y = [m['label'] for m in self.meta]
glumpy_viewer(img_array=self.arrays['train_images'],
arrays_to_print=[Y],
cmap=glumpy.colormap.Grey,
window_shape=(28 * 4, 28 * 4))
def main_show():
"""
Use glumpy to launch a data set viewer.
"""
from skdata.utils.glviewer import glumpy_viewer
self = CIFAR10()
Y = [m['label'] for m in self.meta]
glumpy_viewer(
img_array=self._pixels,
arrays_to_print=[Y],
window_shape=(32 * 4, 32 * 4))
def main_show():
"""
Use glumpy to launch a data set viewer.
"""
self = MNIST()
Y = [m['label'] for m in self.meta]
glumpy_viewer(
img_array=self.arrays['train_images'],
arrays_to_print=[Y],
cmap=glumpy.colormap.Grey,
window_shape=(28 * 4, 28 * 4)
)
def show():
from skdata.utils.glviewer import glumpy_viewer
vh = dataset.Calibrated(10)
items = vh.meta[:10]
images = np.asarray(map(vh.read_image, items))
images = images.astype('float32')
images /= images.reshape(10, 1024 * 1536).max(axis=1)[:, None, None]
images = 1.0 - images
glumpy_viewer(img_array=images,
arrays_to_print=[items],
window_shape=vh.meta[0]['image_shape'])
def show():
from skdata.utils.glviewer import glumpy_viewer
vh = dataset.Calibrated(10)
items = vh.meta[:10]
images = np.asarray(map(vh.read_image, items))
images = images.astype('float32')
images /= images.reshape(10, 1024 * 1536).max(axis=1)[:, None, None]
images = 1.0 - images
glumpy_viewer(
img_array=images,
arrays_to_print=[items],
window_shape=vh.meta[0]['image_shape'])
def show_patches():
N = 100
S = 128
from skdata.utils.glviewer import glumpy_viewer
vh = dataset.Calibrated(10)
patches = vh.raw_patches((N, S, S), items=vh.meta[:10])
patches = patches.astype('float32')
patches /= patches.reshape(N, S * S).max(axis=1)[:, None, None]
patches = 1.0 - patches
SS = S
while SS < 256:
SS *= 2
glumpy_viewer(img_array=patches,
arrays_to_print=[vh.meta],
window_shape=(SS, SS))
def show_patches():
N = 100
S = 128
from skdata.utils.glviewer import glumpy_viewer
vh = dataset.Calibrated(10)
patches = vh.raw_patches((N, S, S), items=vh.meta[:10])
patches = patches.astype('float32')
patches /= patches.reshape(N, S * S).max(axis=1)[:, None, None]
patches = 1.0 - patches
SS = S
while SS < 256:
SS *= 2
glumpy_viewer(
img_array=patches,
arrays_to_print=[vh.meta],
window_shape=(SS, SS))
def main_show():
"""
Use glumpy to launch a data set viewer.
"""
variant = sys.argv[2]
if variant == 'original':
obj = view.Original()
cmap=None
elif variant == 'aligned':
obj = view.Aligned()
cmap=glumpy.colormap.Grey
elif variant == 'funneled':
obj = view.Funneled()
cmap=None
else:
raise ValueError(variant)
glumpy_viewer(
img_array=obj.image_pixels,
arrays_to_print=[obj.image_pixels],
cmap=cmap,
window_shape=(250, 250),
)
def main_show():
"""
Use glumpy to launch a data set viewer.
"""
variant = sys.argv[2]
if variant == 'original':
obj = view.Original()
cmap = None
elif variant == 'aligned':
obj = view.Aligned()
cmap = glumpy.colormap.Grey
elif variant == 'funneled':
obj = view.Funneled()
cmap = None
else:
raise ValueError(variant)
glumpy_viewer(
img_array=obj.image_pixels,
arrays_to_print=[obj.image_pixels],
cmap=cmap,
window_shape=(250, 250),
)