def extract_register(data_register, lock, average_register, register_feature, count_register):
lock.acquire()
#global extractor
# global register_feature
extractor = pfextractor('PED_EXT_001.pkl')
for i in range(0, len(data_register)):
s = getsize(data_register[i])
# try:
fea = extractor.extract(data_register[i])
one_feature = {}
one_feature['camera_id'] = data_register[i]
one_feature['time_stamp'] = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')
one_feature['feature'] = [fea]
register_feature[i + count_register.value] = one_feature
# register_feature[i] = one_feature
# print(i)
# print i+count_register
print len(register_feature)
count_register.value += average_register.value
print count_register
# except:
# continue
print("finished ext cam2 images features")
# register
lock.release()
def extract_register(data_register, lock, count, length, register_feature,
id): #,average_register,register_feature,count_register):
# lock.acquire()
#global register_feature
#register_feature = {}
print("output card:", id)
# id="cuda:"+str(id)
# print("output card:", id)
CUDA_VISIBLE_DEVICES = id
extractor = pfextractor('PED_EXT_001.pkl', id)
for i in range(0, len(data_register)): #len(data_register)):
# s = getsize(data_register[i])
#try:
fea = extractor.extract(data_register[i])
one_feature = {}
one_feature['camera_id'] = data_register[i]
one_feature['time_stamp'] = datetime.datetime.now().strftime(
'%Y-%m-%d %H:%M:%S')
one_feature['feature'] = [fea]
#lock.acquire()
register_feature[i + length] = one_feature
del one_feature
print("count", count)
#lock.release()
# count_register.value+=average_register.value
#print('-----------count',count, len(register_feature), register_feature[0], register_feature[1])
print("finished ext cam2 images features")
def extract_query(data_match, count, match_feature, id):
print("output card:", id)
#CUDA_VISIBLE_DEVICES = id
extractor = pfextractor('PED_EXT_001.pkl', id)
for i in range(0, len(data_match)):
fea = extractor.extract(data_match[i])
match_feature[data_match[i]] = fea
del fea
print("count", count)
print "finished ext cam1 images features"
def extract_match(
data_match, j, register_out,
id): #,match_feature): #,average_match,count_match,register_out):
tic = timeit.default_timer()
print("output card:", id)
#print("count----------", count)
#CUDA_VISIBLE_DEVICES = id
extractor = pfextractor('PED_EXT_001.pkl', id)
toc = timeit.default_timer()
print('all time: %.2f' % ((toc - tic) * 1000))
print("process are ", j)
match_feature = {}
for i in range(0, len(data_match)): #len(data_match)):
fea = extractor.extract(data_match[i])
one_feature = {}
one_feature['camera_id'] = data_match[i]
one_feature['time_stamp'] = datetime.datetime.now().strftime(
'%Y-%m-%d %H:%M:%S')
one_feature['feature'] = [fea]
match_feature[i] = one_feature
del one_feature
print("------------------", len(match_feature))
dm = DataModule(cache_dir)
mm = MatchingModule(MM_CONFIG, dm)
tic = timeit.default_timer()
matching_out = mm.match(match_feature, register=False, rank=5)
toc = timeit.default_timer()
print('match------- time: %.2f' % ((toc - tic) * 1000))
print("per----------time:%.2f" % ((toc - tic) * 1000 / len(matching_out)))
mm.free()
del match_feature
print('result is----------------', len(matching_out))
#calculate precisoin
candidate_path_ids = []
for i in range(len(cam1_image_list)): #len(cam1_image_list)):
# print(i)
id = cam1_image_list[i].split('/')[-2]
candidate_path_id = candidate_path + id
#print("mkdir is ",candidate_path_id)
if not os.path.exists(str(candidate_path_id)):
os.system('mkdir ' + candidate_path_id)
candidate_path_ids.append(candidate_path_id)
for mkey in matching_out:
mobject_id = matching_out[mkey]['object_id'][0]
mcamera_id = matching_out[mkey]['camera_id']
file_name = mcamera_id.split('/')[2]
allName = candidate_path + str(file_name) + "/"
#print('file location is:',allName)
for rkey in register_out.keys():
robject_id = register_out[rkey]['object_id'][0]
rcamera_id = register_out[rkey]['camera_id']
if robject_id == mobject_id:
print("----------------find--------------")
os.system('cp ' + rcamera_id + ' ' + allName)
def extract_register(data_register, count, register_feature,
id): #,average_register,register_feature,count_register):
print("output card:", id)
#CUDA_VISIBLE_DEVICES = id
extractor = pfextractor('PED_EXT_001.pkl', id)
for i in range(0, len(data_register)): #len(data_register)):
fea = extractor.extract(data_register[i])
register_feature[data_register[i]] = fea
del fea
print("count", count)
del extractor
print "finished ext cam2 images features"
def extract_register(data_register,count,register_feature,id): #,average_register,register_feature,count_register):
print("output card:",id)
#CUDA_VISIBLE_DEVICES = id
tic = timeit.default_timer()
extractor = pfextractor('PED_EXT_001.pkl',id)
toc = timeit.default_timer()
print('read weight time: %.2f' % ((toc - tic) * 1000))
for i in range(0,len(data_register)): #len(data_register)):
fea = extractor.extract(data_register[i])
register_feature[data_register[i]] = fea
del fea
print("count",count)
del extractor
gc.collect()
print "finished ext cam2 images features"
def extract_register(data_register, count, length, register_feature,
id): #,average_register,register_feature,count_register):
print("output card:", id)
#CUDA_VISIBLE_DEVICES = id
extractor = pfextractor('PED_EXT_001.pkl', id)
for i in range(0, len(data_register)): #len(data_register)):
fea = extractor.extract(data_register[i])
one_feature = {}
one_feature['camera_id'] = data_register[i]
one_feature['time_stamp'] = datetime.datetime.now().strftime(
'%Y-%m-%d %H:%M:%S')
one_feature['feature'] = [fea]
register_feature[i + length] = one_feature
del one_feature
print("count", count)
print("finished ext cam2 images features")
import pickle
def load_obj(name):
with open('obj/' + name + '.pkl', 'rb') as f:
return pickle.load(f)
def save_obj(obj, name):
with open('../candidate_2018_09_14_1/' + name + '.pkl', 'wb') as f:
pickle.dump(obj, f, pickle.HIGHEST_PROTOCOL)
if __name__ == '__main__':
tic = timeit.default_timer()
extractor = pfextractor('PED_EXT_001.pkl', 0)
cam1_path = '../1_2018-09-15_test/'
cam2_path = '../2_2018-09-15_test/'
#candidate_path = '../candidate_2018-09-14/'
candidate_path = '../candidate_2018_09_15_5/'
cam2_dict = {}
#num=0
cam1_image_list = []
cam2_image_list = []
num = 0
for dirpath, dirnames, filenames in os.walk(cam2_path):
for f in filenames:
# if num==1000:
# break
print f
def extract_match(data_match, lock, average_match, match_feature, count_match, register_out):
# lock.acquire()
# global count_match
#global extractor
extractor = pfextractor('PED_EXT_001.pkl')
for i in range(0, len(data_match)):
s = getsize(data_match[i])
# try:
fea = extractor.extract(data_match[i])
one_feature = {}
one_feature['camera_id'] = data_match[i]
one_feature['time_stamp'] = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')
one_feature['feature'] = [fea]
# match_feature[i+count_match.value] = one_feature
match_feature[i] = one_feature
print(i)
# print(average_match.value)
# print i+count_match.value
# count_match.value +=average_match.value
print("2222222222222222222222222222222222222222222", len(match_feature))
# print count_match.value
# except:
# continue
print("finished ext cam1 images features")
# parse matching feature
# matching
mm = MatchingModule(MM_CONFIG)
matching_out = mm.match(match_feature, register=False, rank=5)
# with open('register_out.json', 'w') as file:
# json.dump(register_out, file, indent=4)
# json.encoder.FLOAT_REPR = lambda x: format(x, '.2f')
# with open('matching_out.json', 'w') as file:
# json.dump(matching_out, file, indent=4)
# calculate precisoin
candidate_path_ids = []
for i in range(0, len(cam1_image_list)):
print(i)
id = cam1_image_list[i].split('/')[-2]
candidate_path_id = candidate_path + id
if not os.path.exists(str(candidate_path_id)):
os.system('mkdir ' + candidate_path_id)
candidate_path_ids.append(candidate_path_id)
# precision = 0
# feature_num = 0
print("------------------------------------------")
print(candidate_path_ids)
for mkey in matching_out:
try:
mobject_id = matching_out[mkey]['object_id'][0]
mcamera_id = matching_out[mkey]['camera_id']
print(mobject_id)
print(mcamera_id)
print(len(register_out))
for rkey in register_out.keys():
robject_id = register_out[rkey]['object_id'][0]
rcamera_id = register_out[rkey]['camera_id']
print("111111111111111111111111111111111")
print(robject_id)
print(rcamera_id)
if robject_id == mobject_id:
print("find-------------")
os.system('cp ' + rcamera_id + ' ' + candidate_path_ids[mobject_id - 1] + '/')
break
except:
continue
# print 'rank=', len(matching_out[mkey]['object_id']), len(matching_out[mkey]['score'])
# print 'matched_id=', mobject_id, ', register_id=', robject_id, ',score=', matching_out[mkey]['score'][0]
# precision += 1 if mobject_id == robject_id else 0
# feature_num += 1
# print 'precision =', precision * 100.0 / feature_num, '%'
mm.free()
def extract_match(
data_match, lock, j, length, register_out,
id): #,match_feature): #,average_match,count_match,register_out):
#lock.acquire()
#global count_match
#lock.acquire()
tic = timeit.default_timer()
print("output card:", id)
#print(torch.cuda.current_device())
CUDA_VISIBLE_DEVICES = id
#torch.cuda.set_device(id)
extractor = pfextractor('PED_EXT_001.pkl', id)
toc = timeit.default_timer()
print('all time: %.2f' % ((toc - tic) * 1000))
print("process are ", j)
#lock.release()
match_feature = {}
for i in range(0, len(data_match)): #len(data_match)):
# s = getsize(data_match[i])
#try:
fea = extractor.extract(data_match[i])
one_feature = {}
one_feature['camera_id'] = data_match[i]
one_feature['time_stamp'] = datetime.datetime.now().strftime(
'%Y-%m-%d %H:%M:%S')
one_feature['feature'] = [fea]
#match_feature[i+count_match.value] = one_feature
match_feature[i] = one_feature
del one_feature
#print("process is ",j)
# print("finished ext cam1 images features")
# print("finished ext cam1 images features")
# for ii in range(len(match_feature)):
# print(j,len(match_feature), match_feature[ii])
# matching
print("------------------", len(match_feature))
dm = DataModule(cache_dir)
mm = MatchingModule(MM_CONFIG, dm)
matching_out = mm.match(match_feature, register=False, rank=5)
mm.free()
del match_feature
print('result is----------------', len(matching_out))
#calculate precisoin
candidate_path_ids = []
for i in range(len(cam1_image_list)): #len(cam1_image_list)):
# print(i)
id = cam1_image_list[i].split('/')[-2]
candidate_path_id = candidate_path + id
print("mkdir is ", candidate_path_id)
if not os.path.exists(str(candidate_path_id)):
os.system('mkdir ' + candidate_path_id)
candidate_path_ids.append(candidate_path_id)
# print candidate_path_ids
# print("wenjian list is",len(candidate_path_ids))
# print( "------------------------------------------")
for mkey in matching_out:
# try:
mobject_id = matching_out[mkey]['object_id'][0]
mcamera_id = matching_out[mkey]['camera_id']
file_name = mcamera_id.split('/')[2]
allName = ''
allName = candidate_path + str(file_name) + "/"
print('file location is:', allName)
# print(len(register_out))
for rkey in register_out.keys():
robject_id = register_out[rkey]['object_id'][0]
rcamera_id = register_out[rkey]['camera_id']
print(robject_id)
print(rcamera_id)
if robject_id == mobject_id:
print("find-------------")
print mobject_id
print
#print('cp ' + rcamera_id + ' ' + allName)
os.system('cp ' + rcamera_id + ' ' + allName)