def get_orgres_match_distances(allres, orgtype_='false'):
import algos
qcxs = allres[orgtype_].qcxs
cxs = allres[orgtype_].cxs
match_list = zip(qcxs, cxs)
print('[rr2] getting orgtype_=%r distances between sifts' % orgtype_)
adesc1, adesc2 = get_matching_descriptors(allres, match_list)
print('[rr2] * adesc1.shape = %r' % (adesc1.shape,))
print('[rr2] * adesc2.shape = %r' % (adesc2.shape,))
#dist_list = ['L1', 'L2', 'hist_isect', 'emd']
#dist_list = ['L1', 'L2']
dist_list = ['L1', 'L2', 'hist_isect']
distances = algos.compute_distances(adesc1, adesc2, dist_list)
return distances
def get_orgres_match_distances(allres, orgtype_='false'):
import algos
qcxs = allres[orgtype_].qcxs
cxs = allres[orgtype_].cxs
match_list = zip(qcxs, cxs)
print('[rr2] getting orgtype_=%r distances between sifts' % orgtype_)
adesc1, adesc2 = get_matching_descriptors(allres, match_list)
print('[rr2] * adesc1.shape = %r' % (adesc1.shape, ))
print('[rr2] * adesc2.shape = %r' % (adesc2.shape, ))
#dist_list = ['L1', 'L2', 'hist_isect', 'emd']
#dist_list = ['L1', 'L2']
dist_list = ['L1', 'L2', 'hist_isect']
distances = algos.compute_distances(adesc1, adesc2, dist_list)
return distances
def get_orgres_match_distances(allres, orgtype_='false'):
import algos
qrids = allres[orgtype_].qrids
rids = allres[orgtype_].rids
match_list = zip(qrids, rids)
printDBG('[rr2] getting orgtype_=%r distances between sifts' % orgtype_)
adesc1, adesc2 = get_matching_descriptors(allres, match_list)
printDBG('[rr2] * adesc1.shape = %r' % (adesc1.shape, ))
printDBG('[rr2] * adesc2.shape = %r' % (adesc2.shape, ))
#dist_list = ['L1', 'L2', 'hist_isect', 'emd']
#dist_list = ['L1', 'L2', 'hist_isect']
dist_list = ['L2', 'hist_isect']
hist1 = np.array(adesc1, dtype=np.float64)
hist2 = np.array(adesc2, dtype=np.float64)
distances = algos.compute_distances(hist1, hist2, dist_list)
return distances
def get_orgres_match_distances(allres, orgtype_='false'):
import algos
qrids = allres[orgtype_].qrids
rids = allres[orgtype_].rids
match_list = zip(qrids, rids)
printDBG('[rr2] getting orgtype_=%r distances between sifts' % orgtype_)
adesc1, adesc2 = get_matching_descriptors(allres, match_list)
printDBG('[rr2] * adesc1.shape = %r' % (adesc1.shape,))
printDBG('[rr2] * adesc2.shape = %r' % (adesc2.shape,))
#dist_list = ['L1', 'L2', 'hist_isect', 'emd']
#dist_list = ['L1', 'L2', 'hist_isect']
dist_list = ['L2', 'hist_isect']
hist1 = np.array(adesc1, dtype=np.float64)
hist2 = np.array(adesc2, dtype=np.float64)
distances = algos.compute_distances(hist1, hist2, dist_list)
return distances
