def query2(querydir, querysift, dbdir, mainOutputDir, nClosestCells, copytopmatch, params, copy_top_n_percell=0):
lat, lon = info.getQuerySIFTCoord(querysift)
closest_cells = util.getclosestcells(lat, lon, dbdir)
assert dict(closest_cells)['37.8732916331,-122.268346029'] < 236 or dict(closest_cells)['37.8714489427,-122.272389514'] < 236 or dict(closest_cells)['37.8696062215,-122.273737308'] < 236
built = [
'37.8732916331,-122.268346029',
'37.8714489427,-122.272389514',
'37.8696062215,-122.273737308',
]
closest_cells = filter(lambda c: c[0] in built, closest_cells)
outputFilePaths = []
cells_in_range = [(cell, dist) for cell, dist in closest_cells[0:nClosestCells] if dist < cellradius + ambiguity+matchdistance]
latquery, lonquery = info.getQuerySIFTCoord(querysift)
if verbosity > 0:
print "checking query: {0} \t against {1} \t cells".format(querysift, len(cells_in_range))
for cell, dist in cells_in_range:
latcell, loncell = cell.split(',')
latcell = float(latcell)
loncell = float(loncell)
actualdist = info.distance(latquery, lonquery, latcell, loncell)
if verbosity > 1:
print "querying cell: {0}, distance: {1} with:{2}".format(cell, actualdist, querysift)
outputFilePath = os.path.join(mainOutputDir, querysift + ',' + cell + ',' + str(actualdist) + ".res")
outputFilePaths.append(outputFilePath)
# start query
query.run_parallel(dbdir, [c for c,d in cells_in_range], querydir, querysift, outputFilePaths, params)
# end query
for cell, dist in cells_in_range:
latcell, loncell = cell.split(',')
latcell = float(latcell)
loncell = float(loncell)
actualdist = info.distance(latquery, lonquery, latcell, loncell)
outputFilePath = os.path.join(mainOutputDir, querysift + ',' + cell + ',' + str(actualdist) + ".res")
if copy_top_n_percell > 0:
outputDir = os.path.join(mainOutputDir, querysift + ',' + cell + ',' + str(actualdist))
copy_topn_results(os.path.join(dbdir, cell), outputDir, outputFilePath, 4)
# combined = combine_until_dup(outputFilePaths, 1000)
combined = combine_topn_votes(outputFilePaths, float('inf'))
# combined = filter_in_range(combined, querysift)
# write_scores(querysift, combined, "/media/data/combined")
[g, y, r, b, o] = check_topn_img(querysift, combined, topnresults)
if copytopmatch:
match = g or y or r or b or o
copy_top_match(querydir, querysift.split('sift.txt')[0], combined, match)
return [g, y, r, b, o]
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 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 filter_in_range(ranked_matches, querysift):
qlat, qlon = info.getQuerySIFTCoord(querysift)
weighted_matches = []
for matchedimg, score in ranked_matches:
clat = float(matchedimg.split(",")[0])
clon = float(matchedimg.split(",")[1][0:-5])
distance = info.distance(qlat, qlon, clat, clon)
if distance < ambiguity+matchdistance:
weighted_matches.append((matchedimg, 2 * score))
weighted_matches.sort(key=lambda x: x[1], reverse=True)
return weighted_matches
def skew_location(querysift, radius):
center = info.getQuerySIFTCoord(querysift)
length = 2*radius
points = []
corner = info.moveLocation(center[0], center[1], (2**.5)*radius, -45)
for i in range(length+1):
row = info.moveLocation(corner[0], corner[1], i, 180)
for j in range(length+1):
point = info.moveLocation(row[0],row[1], j, 90)
if info.distance(center[0],center[1], point[0], point[1]) <= radius:
points.append(point)
return points
def writeQueryCoords(querydir, fname):
"""writes coordinates for all querysift in path into a file fname for use in google earth"""
if not os.path.exists(querydir):
print "invalid path"
return
f = open(fname, "w")
for querysift in getSiftFileNames(querydir):
lat, lon = info.getQuerySIFTCoord(querysift)
lat = str(lat)
lon = str(lon)
f.write(',' + querysift.split(',')[0] + ',' + lon + ',' + lat + '' + '\n')
f.close()
def match(siftfile, lat=None, lon=None):
if lat == None or lon == None:
lat, lon = info.getQuerySIFTCoord(siftfile)
stats, matchedimg, matches, combined = context.match(
siftfile, matchdir, lat, lon)
return matchedimg, matches
def match(siftfile, lat=None, lon=None):
if lat == None or lon == None:
lat, lon = info.getQuerySIFTCoord(siftfile)
stats, matchedimg, matches, combined = context.match(siftfile, matchdir, lat, lon)
return matchedimg, matches
