def test_vlad_distances_order():
im = 'im1'
other_ims = ['im2', 'im3']
histograms = {
'im1': np.array([1, 0, 0]),
'im2': np.array([0, 1, 0]),
'im3': np.array([1, 1, 0]) / np.linalg.norm([1, 1, 0]),
}
im_res, order_res, other_res = vlad.vlad_distances(
im, other_ims, histograms)
assert im_res == im
assert len(order_res) == len(other_ims)
assert other_res == other_ims
assert other_ims[order_res[0]] == 'im3'
assert other_ims[order_res[1]] == 'im2'
def test_vlad_distances_order():
im = "im1"
other_ims = ["im2", "im3"]
histograms = {
"im1": np.array([1, 0, 0]),
"im2": np.array([0, 1, 0]),
"im3": np.array([1, 1, 0]) / np.linalg.norm([1, 1, 0]),
}
im_res, distance_res, other_res = vlad.vlad_distances(
im, other_ims, histograms)
assert im_res == im
assert len(distance_res) == len(other_ims)
assert other_res == other_ims
order_res = np.argsort(distance_res)
assert other_ims[order_res[0]] == "im3"
assert other_ims[order_res[1]] == "im2"
def match_vlad_unwrap_args(args):
""" Wrapper for parralel processing of VLAD """
image, other_images, histograms = args
return vlad.vlad_distances(image, other_images, histograms)
def match_vlad_unwrap_args(
args: Tuple[str, Iterable[str], Dict[str, np.ndarray]]
) -> Tuple[str, List[float], List[str]]:
"""Wrapper for parralel processing of VLAD"""
image, other_images, histograms = args
return vlad.vlad_distances(image, other_images, histograms)
