def GetPointData(info):
reconstruction = Info.ReadReconstructionData(info)['shots']
reconstruction_data = []
latlon_data = []
frame_lst = []
f = open(Info.GetMatchLstFileName(info), 'r')
for line in f:
line = line[0:-1].split('\t')
frame_name = line[0]
pano_name = line[1]
try:
[x, y, z] = optical_center(reconstruction[frame_name])
except:
continue
lat = float(line[2])
lon = float(line[3])
frame_lst.append(line[0])
reconstruction_data.append([x, y])
latlon_data.append([lat, lon])
f.close()
reconstruction_data = np.array(reconstruction_data, dtype=np.float32)
latlon_data = np.array(latlon_data, dtype=np.float32)
#plt.figure()
#plt.subplot('111')
#plt.plot(reconstruction_data[:,0], reconstruction_data[:,1], 'o')
#plt.show()
return [frame_lst, reconstruction_data, latlon_data]
def Label(ID):
info = Info.GetVideoInfo(ID)
frame_lst = [
x for x in sorted(os.listdir(info['frame_path'])) if x.endswith
]
i = 0
f = open(Info.GetMatchLstFileName(info), 'w')
while True:
f_name = info['frame_path'] + '/' + frame_lst[i]
command = 'eog %s' % f_name
subprocess.call(command, shell=True)
panoid = raw_input('Pano ID : ')
loc = GSV.getLocationbyID(panoid)
print loc
s = '%s\t%s\t%s\t%s\n' % (frame_lst[i], panoid, loc[0], loc[1])
f.write(s)
i += 10
if i >= 125:
f.close()
return
f.close()
def GetResultLst(ID):
print ID
info = Info.GetVideoInfo(ID)
frame_sift_lst = [
x for x in sorted(os.listdir(info['frame_sift_path']))
if x.endswith('.sift')
]
pano_sift_lst = [
x for x in sorted(os.listdir(info['pano_sift_path']))
if x.endswith('.sift')
]
fisher_result = np.load(Info.GetFisherResultFileName(info))
match_score = np.load(Info.GetMatchFunMFileName(info))
#print match_score
f = open(Info.GetMatchLstFileName(info), 'w')
for frame_index, frame_sift_name in enumerate(frame_sift_lst):
arg_sort_index = np.argsort(match_score[frame_index, :])
highest_index = arg_sort_index[-1]
highest_score = match_score[frame_index, highest_index]
second_index = arg_sort_index[-2]
second_score = match_score[frame_index, second_index]
ratio = float(highest_score) / float(second_score)
if highest_score >= THRESHOLD:
frame_name = frame_sift_name.split('.')[0] + '.jpg'
pano_sift_name = pano_sift_lst[fisher_result[frame_index,
highest_index]]
pano_name = pano_sift_name.split('.')[0] + '.jpg'
pano_id = pano_name[5:27]
print pano_id
loc = GoogleSV.getLocationbyID(pano_id)
if loc is None:
continue
s = '%s\t%s\t%s\t%s\t%d\n' % (frame_name, pano_name, loc[0],
loc[1], highest_score)
f.write(s)
f.close()
