def get_num_imgs_in_range(range, celldir, querydir='/home/zhangz/.gvfs/data on 128.32.43.40/query3/'):
queries = util.getSiftFileNames(querydir)
total_in_range=0
for querysift in queries:
lat, lon = info.getQuerySIFTCoord(querysift)
cell, dist = util.getclosestcell(lat, lon, celldir)
numinrange = util.getNumJPGInRange(lat, lon, os.path.join(celldir,cell), range)
total_in_range+=numinrange
print "average # of imgs within {0} meters of query: {1}".format(range, float(total_in_range)/len(queries))
def iter1():
for file in util.getSiftFileNames(self.querydir):
image = _Query()
image.siftpath = os.path.join(self.querydir, file)
#TODO: this uses a hard coded dimension
image.pgm_scale = max(Image.open(os.path.join(self.querydir, image.siftname[:-8] + '.pgm')).size) / max(2592.0, 1456.0)
image.jpgpath = os.path.join(self.querydir, image.siftname[:-8] + '.jpg')
image.setSensorCoord(0,0)
image.check()
yield image
def iter2():
for file in util.getSiftFileNames(self.querydir):
image = _Query()
if self.QUERY == 'query2':
image.pgm_scale = 512/2592.0
image.siftpath = os.path.join(self.querydir, file)
image.jpgpath = os.path.join(self.querydir, image.siftname[:-8] + '.JPG')
image.setSensorCoord(*info.add_error(info.getQuerySIFTCoord(file), self.added_error))
if self.QUERY != 'query4-matlab':
image.check()
yield image
def characterizeFuzzy(querydir, dbdir, mainOutputDir, n, copytopmatch):
start = time.time()
if not os.path.exists(mainOutputDir):
os.makedirs(mainOutputDir)
if copytopmatch:
if os.path.exists(resultsdir):
shutil.rmtree(resultsdir)
os.makedirs(resultsdir)
files = util.getSiftFileNames(querydir)
g_count = 0
y_count = 0
r_count = 0
b_count = 0
o_count = 0
count = 0
for queryfile in files:
for newlat, newlon in skew_location(queryfile, ambiguity):
closest_cells = util.getclosestcells(newlat, newlon, dbdir)
count += 1
[g, y, r, b, o] = query2(querydir, queryfile, dbdir, mainOutputDir, n, copytopmatch, closest_cells, copy_top_n_percell=5)
if g:
g_count += 1
if verbosity > 0:
print "G match-g:{0} y:{1} r:{2} b:{3} o:{4} out of {5}".format(g_count, y_count, r_count, b_count, o_count, count)
elif y:
y_count += 1
if verbosity > 0:
print "Y match-g:{0} y:{1} r:{2} b:{3} o:{4} out of {5}".format(g_count, y_count, r_count, b_count, o_count, count)
elif r:
r_count += 1
if verbosity > 0:
print "R match-g:{0} y:{1} r:{2} b:{3} o:{4} out of {5}".format(g_count, y_count, r_count, b_count, o_count, count)
elif b:
b_count += 1
if verbosity > 0:
print "B match-g:{0} y:{1} r:{2} b:{3} o:{4} out of {5}".format(g_count, y_count, r_count, b_count, o_count, count)
elif o:
o_count += 1
if verbosity > 0:
print "O match-g:{0} y:{1} r:{2} b:{3} o:{4} out of {5}".format(g_count, y_count, r_count, b_count, o_count, count)
else:
if verbosity > 0:
print "No match-g:{0} y:{1} r:{2} b:{3} o:{4} out of {5}".format(g_count, y_count, r_count, b_count, o_count, count)
end = time.time()
elapsed = end - start
if verbosity > 0:
print "total time:{0}, avg time:{1}".format(elapsed, elapsed / count)
total_count = g_count + y_count + r_count + b_count + o_count
match_rate = float(total_count) / count
print "g:{0} y:{1} r:{2} b:{3} o:{4} = {5}, out of {6}={7}".format(g_count, y_count, r_count, b_count, o_count, total_count, count, match_rate)