def getMatches(featDir,sfm_file_name,match_file_name):
"""provide a dictionary of matches
featDir is the path of the directory that contains the .feat files
sfm_file_name is the path of sfm_data.json
match_file_name is the path of the match file (matches.f.txt)
returns:
a dictionary
keys: pair of image identifier (im_id0,im_id1)
values: list of match tuples
a match tuple is a 4-uple:
(kp_id0,feat0,kp_id1,feat1)
a feat is a numpy float array representing the keypoint tuple:
x,y,scale,orientation (aka xyso feature)
"""
print "[getMatches(featDir,sfm_file_name,match_file_name)]"
print "featDir ", featDir
print "sfm_file_name " ,sfm_file_name
print "match_file_name", match_file_name
id2name,name2id=parseImages(sfm_file_name)
pair2matches=parseMatches(match_file_name)
#check completeness
for p in pair2matches:
assert p[0] in id2name
assert p[1] in id2name
featname=featNamer(featDir)
matchMap={
pair:[
#let F0 be parseFeat(featname(id2name(pair[0])))
#let F1 be parseFeat(featname(id2name(pair[1])))
(match[0],F0[match[0]],
match[1],F1[match[1]])
for F0 in (parseFeat(featname(id2name[pair[0]])),)
for F1 in (parseFeat(featname(id2name[pair[1]])),)
for match in pair2matches[pair]]
for pair in pair2matches}
return matchMap
def loadImageMap(self):
sfm_file_name =self._ftd+"/sfm_data.json"
self.image_id2name,self.name2image_id = parseImages(sfm_file_name)
return self.image_id2name,self.name2image_id
