def test_smart_image_io(plot = False):
image = smart_load('https://raw.githubusercontent.com/petered/data/master/images/artemis.jpeg', use_cache=True)
smart_save(image[:, ::-1, :], 'output/simetra.png')
rev_image = smart_load('output/simetra.png')
assert np.array_equal(rev_image, rev_image)
if plot:
from artemis.plotting.db_plotting import dbplot
dbplot(image, 'Artemis')
dbplot(rev_image, 'Simetra', hang=True)
def test_smart_image_io(plot=False):
image = smart_load(
'https://raw.githubusercontent.com/petered/data/master/images/artemis.jpeg',
use_cache=True)
smart_save(image[:, ::-1, :], 'output/simetra.png')
rev_image = smart_load('output/simetra.png')
assert np.array_equal(rev_image, rev_image)
if plot:
from artemis.plotting.db_plotting import dbplot
dbplot(image, 'Artemis')
dbplot(rev_image, 'Simetra', hang=True)
def get_imagenet_images(indices):
"""
Get imagenet images at the given indices
:param indices:
:return:
"""
highest_index = np.max(indices)
code_url_pairs = get_imagenet_fall11_urls(highest_index+1)
files = [get_file('data/imagenet/%s%s' % (code_url_pairs[index][0], os.path.splitext(code_url_pairs[index][1])[1]), code_url_pairs[index][1]) for index in indices]
return [smart_load(f) for f in files]
def get_imagenet_images(indices):
"""
Get imagenet images at the given indices
:param indices:
:return:
"""
highest_index = np.max(indices)
code_url_pairs = get_imagenet_fall11_urls(highest_index+1)
files = [get_file('data/imagenet/%s%s' % (code_url_pairs[index][0], os.path.splitext(code_url_pairs[index][1])[1]), code_url_pairs[index][1]) for index in indices]
return [smart_load(f) for f in files]
def classify(f, im_path):
im = smart_load(im_path)
print 'Processing image... "%s"' % (im_path, )
inputs = im2vgginput(im)
out = f(inputs)
amax = np.argmax(out[0])
label = get_vgg_label_at(amax)
print 'Done.'
dbplot(np.rollaxis(inputs[0], 0, 3)[..., ::-1],
'Photo',
title="{label}: {pct}%".format(label=label,
pct=out[0, amax, 0, 0] * 100))