def test_basic():
x = np.random.random((100, 100)) * 255
y = x / 1.8
a, b = photometric_adjust(y, x)
assert_almost_equal(a, 1.8)
assert_almost_equal(b, 0)
parser.print_help()
sys.exit(0)
ic = load_vgg(vgg_dir)
# Perform crude photometric registration
ref = ic[0].copy()
images = []
scale_offset = []
for i in range(len(ic)):
scale = 1
offset = 0
if options.photo_adjust:
img_warp = homography(ic[i], ic[i].info['H'])
scale, offset = photometric_adjust(img_warp, ref)
scale_offset.append((scale, offset))
images.append(ic[i] * scale + offset)
print "Images adjusted by: %s" % str(['%.2f, %.2f' % (a,b)
for (a,b) in scale_offset])
images = [img for i,img in enumerate(images) if not i in options.ignore]
HH = [i.info['H'] for i in images]
oshape = np.floor(np.array(images[0].shape) * options.scale)
avg = initial_guess_avg(images, HH, options.scale, oshape)
#
# Update solution one frame at a time
parser.print_help()
sys.exit(0)
ic = load_vgg(vgg_dir)
# Perform crude photometric registration
ref = ic[0].copy()
images = []
scale_offset = []
for i in range(len(ic)):
scale = 1
offset = 0
if options.photo_adjust:
img_warp = homography(ic[i], ic[i].info['H'])
scale, offset = photometric_adjust(img_warp, ref)
scale_offset.append((scale, offset))
images.append(ic[i] * scale + offset)
print "Images adjusted by: %s" % str(
['%.2f, %.2f' % (a, b) for (a, b) in scale_offset])
images = [img for i, img in enumerate(images) if not i in options.ignore]
HH = [i.info['H'] for i in images]
oshape = np.floor(np.array(images[0].shape) * options.scale)
avg = initial_guess_avg(images, HH, options.scale, oshape)
#
# Update solution one frame at a time
