def __init__(nn_index, hs, cx_list):
import algos
cx2_desc = hs.feats.cx2_desc
# Make unique id for indexed descriptors
feat_uid = hs.prefs.feat_cfg.get_uid()
sample_uid = helpers.hashstr_arr(cx_list, "dcxs")
uid = "_" + sample_uid + feat_uid
# Number of features per sample chip
sx2_nFeat = [len(cx2_desc[cx]) for cx in iter(cx_list)]
# Inverted index from indexed descriptor to chipx and featx
_ax2_cx = [[cx] * nFeat for (cx, nFeat) in izip(cx_list, sx2_nFeat)]
_ax2_fx = [range(nFeat) for nFeat in iter(sx2_nFeat)]
ax2_cx = np.array(list(chain.from_iterable(_ax2_cx)))
ax2_fx = np.array(list(chain.from_iterable(_ax2_fx)))
# Aggregate indexed descriptors into continuous structure
ax2_desc = np.vstack([cx2_desc[cx] for cx in cx_list if len(cx2_desc[cx]) > 0])
# Build/Load the flann index
flann_params = {"algorithm": "kdtree", "trees": 4}
precomp_kwargs = {
"cache_dir": hs.dirs.cache_dir,
"uid": uid,
"flann_params": flann_params,
"force_recompute": hs.args.nocache_flann,
}
flann = algos.precompute_flann(ax2_desc, **precomp_kwargs)
# ----
# Agg Data
nn_index.ax2_cx = ax2_cx
nn_index.ax2_fx = ax2_fx
nn_index.ax2_data = ax2_desc
nn_index.flann = flann
def __init__(nn_index, hs, cx_list):
import algos
cx2_desc = hs.feats.cx2_desc
# Make unique id for indexed descriptors
feat_uid = hs.prefs.feat_cfg.get_uid()
sample_uid = helpers.hashstr_arr(cx_list, 'dcxs')
uid = '_' + sample_uid + feat_uid
# Number of features per sample chip
sx2_nFeat = [len(cx2_desc[cx]) for cx in iter(cx_list)]
# Inverted index from indexed descriptor to chipx and featx
_ax2_cx = [[cx] * nFeat for (cx, nFeat) in izip(cx_list, sx2_nFeat)]
_ax2_fx = [range(nFeat) for nFeat in iter(sx2_nFeat)]
ax2_cx = np.array(list(chain.from_iterable(_ax2_cx)))
ax2_fx = np.array(list(chain.from_iterable(_ax2_fx)))
# Aggregate indexed descriptors into continuous structure
ax2_desc = np.vstack(
[cx2_desc[cx] for cx in cx_list if len(cx2_desc[cx]) > 0])
# Build/Load the flann index
flann_params = {'algorithm': 'kdtree', 'trees': 4}
precomp_kwargs = {
'cache_dir': hs.dirs.cache_dir,
'uid': uid,
'flann_params': flann_params,
'force_recompute': hs.args.nocache_flann
}
flann = algos.precompute_flann(ax2_desc, **precomp_kwargs)
#----
# Agg Data
nn_index.ax2_cx = ax2_cx
nn_index.ax2_fx = ax2_fx
nn_index.ax2_data = ax2_desc
nn_index.flann = flann
def precompute_index_vsmany(hs):
print(textwrap.dedent('''
=============================
[mc2] Building one-vs-many index
============================='''))
# Build (or reload) one vs many flann index
cache_dir = hs.dirs.cache_dir
ax2_cx, ax2_fx, ax2_desc = aggregate_descriptors_vsmany(hs)
# Precompute flann index
matcher_uid = params.get_matcher_uid()
#checks = params.VSMANY_FLANN_PARAMS['checks']
vsmany_flann_params = params.VSMANY_FLANN_PARAMS
vsmany_flann = algos.precompute_flann(ax2_desc,
cache_dir=cache_dir,
uid=matcher_uid,
flann_params=vsmany_flann_params)
# Return a one-vs-many structure
vsmany_args = VsManyArgs(vsmany_flann, ax2_desc, ax2_cx, ax2_fx)
return vsmany_args
