import amitgroup as ag
import gv
import numpy as np

originals, bbs = gv.voc.load_object_images_of_size('bicycle', (64, 64),
                                                   dataset='train')
#originals, bbs = gv.voc.load_negative_images_of_size('bicycle', (64, 64), dataset='train', count=1)

#print map(lambda x: x.shape, images)

#ag.plot.images(images[:9])

for i in xrange(4):
    import pylab as plt
    plt.imshow(originals[i], interpolation='nearest')

    from plotting import plot_box
    plot_box(bbs[i])
    plt.show()
Exemple #2
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img_padded = ag.util.zeropad(img_resized, (sh[0], sh[1], 0))

print img.shape
print img_resized.shape
print img_padded.shape

small_padded = ag.util.zeropad(small, (sh[0], sh[1], 0))

window = small_padded[sh[0] + offset[0]:sh[0] + offset[0] + sh[0],
                      sh[1] + offset[1]:sh[1] + offset[1] + sh[1]]

print window.shape

plt.subplot(231)
plt.imshow(img)
plot_box(box)

plt.subplot(232)
l1 = plt.imshow(np.ones((1, 1)),
                vmin=0,
                vmax=1,
                cmap=plt.cm.gray,
                interpolation='nearest')
plt.title("Window")

plt.subplot(233)
l4 = plt.imshow(np.ones((1, 1)),
                vmin=0,
                vmax=1,
                cmap=plt.cm.gray,
                interpolation='nearest')
img_padded = ag.util.zeropad(img_resized, (sh[0], sh[1], 0))

print img.shape
print img_resized.shape
print img_padded.shape

small_padded = ag.util.zeropad(small, (sh[0], sh[1], 0))

window = small_padded[sh[0] + offset[0] : sh[0] + offset[0] + sh[0], sh[1] + offset[1] : sh[1] + offset[1] + sh[1]]

print window.shape

plt.subplot(231)
plt.imshow(img)
plot_box(box)

plt.subplot(232)
l1 = plt.imshow(np.ones((1, 1)), vmin=0, vmax=1, cmap=plt.cm.gray, interpolation='nearest')
plt.title("Window")

plt.subplot(233)
l4 = plt.imshow(np.ones((1, 1)), vmin=0, vmax=1, cmap=plt.cm.gray, interpolation='nearest')
plt.title("Edge visualization")

plt.subplot(234)
l2 = plt.imshow(np.ones((1, 1)), vmin=0, vmax=1, cmap=plt.cm.RdBu, interpolation='nearest')
plt.colorbar()
plt.title("Kernel")

plt.subplot(235)
import amitgroup as ag
import gv
import numpy as np

originals, bbs = gv.voc.load_object_images_of_size('bicycle', (64, 64), dataset='train')
#originals, bbs = gv.voc.load_negative_images_of_size('bicycle', (64, 64), dataset='train', count=1)

#print map(lambda x: x.shape, images)

#ag.plot.images(images[:9])

for i in xrange(4):
    import pylab as plt
    plt.imshow(originals[i], interpolation='nearest')

    from plotting import plot_box
    plot_box(bbs[i])
    plt.show()