def Merge(ID):
print ID
info = Info.GetVideoInfo(ID)
f_name = info['match_path'] + '/' + name
f = open(f_name, 'r')
data = json.load(f)
f.close()
key_lst = sorted(data.keys())
pano_lst = []
for key in key_lst:
loc = data[key]
print key
try:
panoid = GSV.getIDbyloc(lat=loc[0], lon=loc[1])
except:
data.pop(key)
continue
#print panoid
if panoid is None:
data.pop(key)
continue
elif not panoid in pano_lst:
pano_lst.append(panoid)
try:
loc = GSV.getLocationbyID(panoid)
data[key] = [float(loc[0]), float(loc[1])]
except:
data.pop(key)
continue
else:
data.pop(key)
f = open(info['match_path'] + '/google_info.json', 'w')
f.write(json.dumps(data, indent=4))
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()
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 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()
