def facedetect(path):
API_KEY = "RuF7pDgXRAl0EfZjZrWIYElt_QoO-XhN"
API_SECRET = "lpUhYiPv8dSdFgMyjkaBKvO2X1nbKzv1"
from facepp import API, File
api = API(API_KEY, API_SECRET)
result = api.detect(image_file=File(path), return_landmark=1)
#we only detect face feature points
landmarks = result['faces'][0]['landmark']
feature_dict = {}
for k, v in landmarks.iteritems():
feature_dict[k] = np.array([v['x'], v['y']])
return feature_dict
def detect(path):
API_KEY = "3o6_lMDRxcpYalXhuXq9cymJeeN7cHCS"
API_SECRET = "6776wZFWYVfYjwDgS8G_0rmWhtXVyUcW"
from facepp import API, File
api = API(API_KEY, API_SECRET)
result = api.detect(image_file=File(path),return_landmark=1)
landmarks = result['faces'][0]['landmark']
new_dict = {}
for k,v in landmarks.iteritems():
new_dict[k] = np.array([v['y'],v['x']])
return new_dict
def createFace ():
# 您需要先注册一个App，并将得到的API key和API secret写在这里。
# You need to register your App first, and enter you API key/secret.
API_KEY = "o_aUYdJlo0Pl1beu0kXiIQShUheA7pe3"
API_SECRET = "Q0DrLrFybJvD7VP_XCKbOEeVeq7mUdLA"
#get the folder list
name_list=os.listdir('/Users/Roy/Documents/masterthesis/image_set')
print (name_list)
face_list=[]
for i in range(len(name_list)):
face_url = '/Users/Roy/Documents/masterthesis/image_set/'+name_list[i]
face_list.append(face_url)
print face_list
api_server_international = 'https://api-us.faceplusplus.com/facepp/v3/'
# First import the API class from the SDK
# 首先，导入SDK中的API类
from facepp import API, File
#创建一个API对象，如果你是国际版用户，代码为：api = API(API_KEY, API_SECRET, srv=api_server_international)
#Create a API object, if you are an international user,code: api = API(API_KEY, API_SECRET, srv=api_server_international)
api = API(API_KEY, API_SECRET)
api.faceset.delete(outer_id='test1', check_empty=0)
print('deleted')
# 创建一个Faceset用来存储FaceToken
# create a Faceset to save FaceToken
ret = api.faceset.create(outer_id='test1')
# print_result("faceset create", ret)
print('faceset create')
# 对图片进行检测
# detect image
Face = {}
Face2 = {}
for i in range(len(face_list)):
res = api.detect(image_file=File(face_list[i]))
# Face['person'+str(i)] = res["faces"][0]["face_token"]
Face[name_list[i]] = res["faces"][0]["face_token"]
print (Face)
# print (Face2)
# 将得到的FaceToken存进Faceset里面
# save FaceToken in Faceset
my_faceset = api.faceset.addface(outer_id='test1', face_tokens=Face.itervalues())
print('finally create')
return Face
def bidui(image_path):
import sys
reload(sys)
sys.setdefaultencoding( "utf-8" )
#将需要识别的图片和集合对比
#------------------------------------------------------------------------------
#准备阶段
API_KEY = "a4OWmRJTir1XGFx6vZtwPvlf6nsYxErQ"
API_SECRET = "Q1bR1pHjv7SGWa3xSN0tNivJ4lK0K8Tu"
#国际版的服务器地址
api_server_international = 'https://api-us.faceplusplus.com/facepp/v3/'
# 导入系统库并定义辅助函数
from pprint import pformat
def print_result(hit, result):
def encode(obj):
if type(obj) is unicode:
return obj.encode('utf-8')
if type(obj) is dict:
return {encode(v): encode(k) for (v, k) in obj.iteritems()}
if type(obj) is list:
return [encode(i) for i in obj]
return obj
print hit
result = encode(result)
print '\n'.join(" " + i for i in pformat(result, width=75).split('\n'))
#导入SDK中的API类
from facepp import API, File
#创建一个API对象
api = API(API_KEY, API_SECRET)
#-----------------------------------------------------------------------------
# 本地图片的地址
face_search = image_path
# 对待比对的图片进行检测
Face = {}
res = api.detect(image_file=File(face_search))
#print_result("face_search", res)
#搜索相似脸
search_result = api.search(face_token=res["faces"][0]["face_token"], outer_id='finally')
# 输出结果
search_confidence = search_result['results'][0]['confidence']
uers=search_result['results'][0]['user_id']
print '置信度:', search_confidence
if search_confidence >=80:
print '你好!',uers.decode('utf-8')
return 1
else:
return 0
def detect(path):
API_KEY = "3o6_lMDRxcpYalXhuXq9cymJeeN7cHCS"
API_SECRET = "6776wZFWYVfYjwDgS8G_0rmWhtXVyUcW"
from facepp import API, File
api = API(API_KEY, API_SECRET)
result = api.detect(image_file=File(path),return_landmark=1)
landmarks = result['faces'][0]['landmark']
#print(landmarks)
keys = [ 'left_eye_right_corner','left_eye_left_corner','right_eye_right_corner','right_eye_left_corner','left_eyebrow_right_corner','right_eyebrow_left_corner',
'mouth_right_corner','mouth_left_corner','mouth_lower_lip_left_contour2','mouth_lower_lip_left_contour3','mouth_lower_lip_bottom','mouth_lower_lip_right_contour2','mouth_lower_lip_right_contour3','nose_left','nose_right']
new_dict = {}
for k,v in landmarks.iteritems():
new_dict[k] = np.array([v['x'],v['y']])
return new_dict
def analyze_user(filepath, id_img):
print filepath
api = API(API_KEY, API_SECRET)
ret = api.faceset.create(outer_id=id_img)
# print_result("faceset create", ret)
Face = {}
res = api.detect(image_file=File(filepath))
if res["faces"]:
Face['person'] = res["faces"][0]["face_token"]
res = api.face.analyze(
image_file=File(filepath),
face_tokens=Face['person'],
return_attributes=
'gender,age,smiling,glass,headpose,facequality,blur')
print_result("person", res)
# res = api.detect(image_file=File(face_two))
# print_result("person_two", res)
# Face['person_two'] = res["faces"][0]["face_token"]
# # 将得到的FaceToken存进Faceset里面
# # save FaceToken in Faceset
# api.faceset.addface(outer_id=id_test, face_tokens=Face.itervalues())
# # 对待比对的图片进行检测，再搜索相似脸
# # detect image and search same face
# ret = api.detect(image_file=File(face_search))
# print_result("detect", ret)
# search_result = api.search(face_token=ret["faces"][0]["face_token"], outer_id=id_test)
# # 输出结果
# # print result
# print_result('search', search_result)
# print '=' * 60
# for k, v in Face.iteritems():
# if v == search_result['results'][0]['face_token']:
# print 'The person with highest confidence:', k
# break
api.faceset.delete(outer_id=id_img, check_empty=0)
return res
def batch_process(src_path,dst_path):
api = API(API_KEY,API_SECRET);
cnt = 0;
for parent,dirnames,filenames in os.walk(src_path):
filenames.sort();
while (not len(filenames)==0):
filename = filenames.pop();
if (os.path.exists(os.path.join(dst_path,os.path.splitext(filename)[0]+'.npy'))):
cnt = cnt+1;
continue;
try:
result = api.detect(image_file = File(os.path.join(parent,filename)),return_landmark=2,
return_attributes="gender,age,headpose,eyestatus,emotion,mouthstatus,eyegaze")
np.save(os.path.join(dst_path,os.path.splitext(filename)[0]+'.npy'),result);
cnt = cnt+1;
print(cnt,filename)
# dictionary = np.load(filename).item()
except APIError, error:
print(error.body);
filenames.append(filename);
def action():
api = API(API_KEY, API_SECRET)
cap = cv2.VideoCapture(0)
while True:
ret, frame = cap.read()
cv2.imwrite('demo.jpeg', frame, [int(cv2.IMWRITE_JPEG_QUALITY), 40])
# detect image
Face = {}
res = api.detect(image_file=File(face_one),
return_landmark=2,
return_attributes='headpose',
calculate_all=1)
try:
#print_result("person_one", res['time_used'])
#print_result("person_one", res['faces'][0]['attributes']['headpose'])
head = res['faces'][0]['attributes']['headpose']
for i in range(3):
if head[headposelist[i]] < (-1) * int(detectrange[i]):
print action[i][0]
if head[headposelist[i]] > detectrange[i]:
print action[i][1]
except:
continue
for item in res['faces'][0]['landmark']:
try:
y = res['faces'][0]['landmark'][item]['x']
x = res['faces'][0]['landmark'][item]['y']
frame[x, y] = [0, 0, 255]
frame[x + 1, y] = [0, 0, 255]
frame[x, y + 1] = [0, 0, 255]
frame[x - 1, y] = [0, 0, 255]
frame[x, y - 1] = [0, 0, 255]
except:
continue
cv2.imshow("capture", frame)
cv2.waitKey(1)
from facepp import API, File
#创建一个API对象，如果你是国际版用户，代码为：api = API(API_KEY, API_SECRET, srv=api_server_international)
#Create a API object, if you are an international user,code: api = API(API_KEY, API_SECRET, srv=api_server_international)
api = API(API_KEY, API_SECRET)
# 创建一个Faceset用来存储FaceToken
# create a Faceset to save FaceToken
ret = api.faceset.create(outer_id='test')
print_result("faceset create", ret)
# 对图片进行检测
# detect image
Face = {}
res = api.detect(image_url=face_one)
print_result("person_one", res)
Face['person_one'] = res["faces"][0]["face_token"]
res = api.detect(image_file=File(face_two))
print_result("person_two", res)
Face['person_two'] = res["faces"][0]["face_token"]
# 将得到的FaceToken存进Faceset里面
# save FaceToken in Faceset
api.faceset.addface(outer_id='test', face_tokens=Face.itervalues())
# 对待比对的图片进行检测，再搜索相似脸
# detect image and search same face
ret = api.detect(image_file=File(face_search))
print_result("detect", ret)
# 首先，导入SDK中的API类
from facepp import API, File
#创建一个API对象，如果你是国际版用户，代码为：api = API(API_KEY, API_SECRET, srv=api_server_international)
#Create a API object, if you are an international user,code: api = API(API_KEY, API_SECRET, srv=api_server_international)
api = API(API_KEY, API_SECRET)
# 创建一个Faceset用来存储FaceToken
# create a Faceset to save FaceToken
ret = api.faceset.create(outer_id='test')
print_result("faceset create", ret)
# 对图片进行检测
# detect image
Face = {}
res = api.detect(image_url=face_one)
print_result("person_one", res)
Face['person_one'] = res["faces"][0]["face_token"]
res = api.detect(image_file=File(face_two))
print_result("person_two", res)
Face['person_two'] = res["faces"][0]["face_token"]
# 将得到的FaceToken存进Faceset里面
# save FaceToken in Faceset
api.faceset.addface(outer_id='test', face_tokens=Face.itervalues())
# 对待比对的图片进行检测，再搜索相似脸
# detect image and search same face
ret = api.detect(image_file=File(face_search))
print_result("detect", ret)
result = encode(result)
print '\n'.join(" " + i for i in pformat(result, width=75).split('\n'))
from facepp import API, File
api = API(API_KEY, API_SECRET)
# 创建一个Faceset用来存储FaceToken
# create a Faceset to save FaceToken
ret = api.faceset.create(outer_id='facedetect')
print_result("faceset create", ret)
Face = {}
res = api.detect(image_file=File(face_one))
print_result("person_one", res)
Face['person_one'] = res["faces"][0]["face_token"]
res = api.detect(image_file=File(face_two))
print_result("person_two", res)
Face['person_two'] = res["faces"][0]["face_token"]
res = api.detect(image_file=File(face_three))
print_result("person_three", res)
Face['person_three'] = res["faces"][0]["face_token"]
res = api.detect(image_file=File(face_four))
print_result("person_four", res)
Face['person_four'] = res["faces"][0]["face_token"]
from pprint import pformat
import sys
import cv2
files = []
for arg in sys.argv[1:]:
files.append(arg)
api_server_international = 'https://api-us.faceplusplus.com/facepp/v3/'
API_KEY = 'TKc09eEMggaDnrTMaJ4wueum7ljWa5Lf'
API_SECRET = '3gX8LSHV7X1R4ODVxsMO-inu4qZDyOSJ'
api = API(API_KEY, API_SECRET, srv=api_server_international)
# api.faceset.delete(outer_id='test1', check_empty=0)
ret = api.faceset.create(outer_id='test1')
for filename in files:
img = cv2.imread(filename);
size = img.shape
res = api.detect(image_file=File(filename), return_landmark=2)
face = res["faces"][0]["landmark"]
person_file = open(filename+".txt", "w")
for face_area, face_points in face.iteritems():
person_file.write(str(face_points[u'x']) + "\t" + str(face_points[u'y']) + "\n")
api.faceset.delete(outer_id='test1', check_empty=0)
class FaceDectect:
def __init__(self,
id='test',
API_KEY='w1s9SPlbJkhetEnq-BD8puseCT2LDTyj',
API_SECRET='a8uEA_hK6lzuRHAY-LiqhlNcoDmS3I7A'):
self.api = API(API_KEY, API_SECRET)
self.Face = {}
self.id = id
self.search_result = {}
def changeFaceset(self, id):
try:
ret = self.api.faceset.create(outer_id=id)
except Exception as e:
print "id already exists"
self.id = id
def delete_Faceset(self, id):
self.api.faceset.delete(outer_id=id, check_empty=0)
def addFaceToSet(self, image_file, info):
res = self.api.detect(image_file=File(image_file))
self.Face['%s' % info] = res["faces"][0]["face_token"]
print "add to Face sucess"
def addFaceToInternet(self):
print[i for i in self.Face.itervalues()]
self.api.faceset.addface(outer_id=self.id,
face_tokens=self.Face.itervalues())
print "add to internet face sucess"
def getFaceInfo(self, input_file):
ret = self.api.detect(image_file=File(input_file))
self.search_result = self.api.search(
face_token=ret["faces"][0]["face_token"], outer_id=self.id)
for k, v in self.Face.iteritems():
if v == self.search_result['results'][0]['face_token']:
print 'The person with highest confidence:', k
return k
break
def save_Face(self, face_file="default_face.txt"):
face_file = open(face_file, 'wb')
pickle.dump(self.Face, face_file)
face_file.close()
def load_Face(self, face_file="default_face.txt"):
face_file = open(face_file, 'rb')
self.Face = pickle.load(face_file)
face_file.close()
def print_result(hit, result):
def encode(obj):
if type(obj) is unicode:
return obj.encode('utf-8')
if type(obj) is dict:
return {encode(v): encode(k) for (v, k) in obj.iteritems()}
if type(obj) is list:
return [encode(i) for i in obj]
return obj
print hit
result = encode(result)
print '\n'.join(" " + i
for i in pformat(result, width=75).split('\n'))
class Analyze(object):
def __init__(self,
path_to_analyze_config,
output_dir_name="analyzed_result",
wait_time=None):
self.path_to_analyze_config = path_to_analyze_config
with open(self.path_to_analyze_config, "r") as f:
self.config = yaml.load(f, Loader=yaml.SafeLoader)
self.output_dir_name = output_dir_name
self.wait_time = wait_time #自然数で指定する必要がある．
if self.config["output_json_name"] is None:
self.output_json_name = "output"
else:
self.output_json_name = self.config["output_json_name"]
self.api = API(API_KEY=self.config["API_KEY"],
API_SECRET=self.config["API_SECRET"])
del self.config["API_KEY"], self.config["API_SECRET"]
def get_dataset(self,
serch_config_name="config_camera.yaml",
path_to_image=None):
if path_to_image is None:
path_to_image = self.config["target_dir_name"]
if serch_config_name in os.listdir(path_to_image):
self.abs_path = os.path.abspath(path_to_image)
path_to_camera_config = os.path.join(
*[self.abs_path, serch_config_name])
with open(path_to_camera_config, "r") as f:
self.config_camera = yaml.load(f, Loader=yaml.SafeLoader)
self.path_to_image = os.path.join(
*[self.abs_path, self.config_camera["image_dir_name"]])
else:
print("'{}' do not have Image dirctory, ex) {}".format(
path_to_image, os.path.join(*[path_to_image, "Images/"])))
exit()
path_list = glob.glob(
os.path.join(*[
self.path_to_image, "*{}".format(
self.config_camera['image_style'])
]))
path_list = sorted(path_list,
key=lambda x: int(x.split("/")[-1].split(".")[0]))
output_dir_path = os.path.join(*[self.abs_path, self.output_dir_name])
os.makedirs(output_dir_path, exist_ok=True)
with open(
os.path.join(*[
output_dir_path,
self.path_to_analyze_config.split("/")[-1]
]), "w") as f:
yaml.dump(self.config, f)
return path_list
def choise_function(self, encode_image, api_kind):
if api_kind == "Detect":
return self.api.detect(image_base64=encode_image,
return_landmark=1,
return_attributes=",".join(
self.config["Attribute_Detect"]))
elif api_kind == "Dence":
return self.api.face.thousandlandmark(image_base64=encode_image,
return_landmark="all")
def detect(self, path_list, api_kind):
print("-" * 10 + api_kind + "-" * 10)
output_list = []
p_bar = ProgressBar(maxval=len(path_list))
for i, each_file in enumerate(path_list):
p_bar.update(i)
encode_img = self.img_to_bese64(each_file)
output = self.choise_function(encode_image=encode_img,
api_kind=api_kind)
output["image_path"] = each_file
output_list.append(output)
if (api_kind == "Dence") and (self.wait_time is not None):
import time
time.sleep(int(self.wait_time)) #実行制限の関係から，ここの値を調整する必要がある．
json_name, file_name = self.get_json_name(api_kind)
self.save_output(json_name, file_name, output_list)
def compere(self, path_list, target_file=None):
if target_file is None:
print("target_file is None, pleasse give any path to image file")
exit()
print("-" * 10 + "Get Compere" + "-" * 10)
p_bar = ProgressBar(maxval=len(path_list))
output_list = []
if target_file is None:
target_file = self.config["target_file"]
target_img = self.img_to_bese64(target_file)
for i, each_file in enumerate(path_list):
p_bar.update(i)
if each_file != target_file:
each_img = self.img_to_bese64(each_file)
output = self.api.compare(image_base64_1=target_img,
image_base64_2=each_img)
output["image_path"] = each_img
output_list.append(output)
json_name, file_name = self.get_json_name(
"Compere", name=target_file.split("/")[-1].split(".")[0])
self.save_output(json_name, file_name, output_list)
def get_json_name(self, api_kind, name=None, name_concat=False):
if name is None:
if not name_concat:
return os.path.join(
*[self.abs_path, self.output_dir_name, api_kind
]), self.output_json_name + ".json"
else:
return os.path.join(*[
self.abs_path, self.output_dir_name, api_kind,
self.output_json_name + ".json"
])
else:
if not name_concat:
return os.path.join(
*[self.abs_path, self.output_dir_name, api_kind
]), name + ".json"
else:
return os.path.join(*[
self.abs_path, self.output_dir_name, api_kind, name +
".json"
])
def save_output(self, path, file_name, output_list):
os.makedirs(path, exist_ok=True)
with open(os.path.join(*[path, file_name]), "w") as f:
json.dump(output_list, f)
def img_to_bese64(self, target_file):
with open(target_file, 'rb') as f:
data = f.read()
return base64.b64encode(data)
def __call__(self, target_file=None, path_to_image=None):
path_list = self.get_dataset(path_to_image=path_to_image)
if self.config["USE_API_Detect"]:
self.detect(path_list, api_kind="Detect")
Detect_api_json_to_csv(
path_to_json=self.get_json_name("Detect", name_concat=True))()
if self.config["USE_API_Compare"]:
self.compere(path_list, target_file)
if self.config["USE_API_Dense_Facial_Landmarks"]:
self.detect(path_list, "Dence")
Dence_api_json_to_csv(
path_to_json=self.get_json_name("Dence", name_concat=True))()
sys.exit()
from facepp import API, File
#创建一个API对象
api = API(API_KEY, API_SECRET)
#-----------------------------------------------------------------------------
# 本地图片的地址
face_6 = './gtl6.jpg'
face_7 = './gtl7.jpg'
face_8 = './gtl8.jpg'
face_9 = './gtl9.jpg'
face_10 = './gtl10.jpg'
# 对图片进行检测
Face = {}
res = api.detect(image_file=File(face_6))
print_result("person_6", res)
Face['person_6'] = res["faces"][0]["face_token"]
res = api.face.setuserid(face_token=Face['person_6'], user_id="古天乐")
res = api.detect(image_file=File(face_7))
print_result("person_7", res)
Face['person_7'] = res["faces"][0]["face_token"]
res = api.face.setuserid(face_token=Face['person_7'], user_id="古天乐")
res = api.detect(image_file=File(face_8))
print_result("person_8", res)
Face['person_8'] = res["faces"][0]["face_token"]
res = api.face.setuserid(face_token=Face['person_8'], user_id="古天乐")
res = api.detect(image_file=File(face_9))
# 导入系统库并定义辅助函数
from pprint import pformat
def print_result(hit, result):
def encode(obj):
if type(obj) is unicode:
return obj.encode('utf-8')
if type(obj) is dict:
return {encode(v): encode(k) for (v, k) in obj.iteritems()}
if type(obj) is list:
return [encode(i) for i in obj]
return obj
print hit
result = encode(result)
print '\n'.join(" " + i for i in pformat(result, width=75).split('\n'))
# First import the API class from the SDK
# 首先，导入SDK中的API类
from facepp import API, File
api = API(API_KEY, API_SECRET)
#return_attributes=[gender, age, smiling, glass, headpose,facequality,blur]
res = api.detect(image_url=face_one, return_landmark=1)
print res[u'faces']
res1 = api.detectsceneandobject(image_url=face_one)
line_list = line.split() # 按空格分割会将时间分为两个对象，因此变成13个
face_url = line_list[12].replace("'", "")
strline = line_list[1] + ',' + line_list[2] + ',' + line_list[3] + ' ' + line_list[4] + ',' \
+ line_list[5] + ',' + line_list[6] + ',' + line_list[7] + ',' + line_list[8] + ',' + line_list[
9] + ',' \
+ line_list[10] + ',' + line_list[11] + ',' + line_list[12]
# print face_one
InsertFaceTable(flickrDataName[j], strline)
'''
InsertFaceTable(line_list[0],long(line_list[1]),line_list[2],line_list[3],line_list[4],\
long(line_list[5]),line_list[6],line_list[7],line_list[8],float(line_list[9]),\
float(line_list[10]),int(line_list[11]),line_list[12])
'''
res = api.detect(image_url=face_url, return_attributes=["gender", "age", "smiling", "emotion", "facequality"])
# print res["faces"][0]["attributes"]
i = len(res["faces"])
if i != 0:
fileWriter.write(line)
for i in range(0, i):
image_id = long(line_list[1])
num = i + 1
gender = res["faces"][i]["attributes"]["gender"]["value"]
age = res["faces"][i]["attributes"]["age"]["value"]
smile = res["faces"][i]["attributes"]["smile"]["value"]
anger = res["faces"][i]["attributes"]["emotion"]["anger"]
disgust = res["faces"][i]["attributes"]["emotion"]["disgust"]
fear = res["faces"][i]["attributes"]["emotion"]["fear"]
happiness = res["faces"][i]["attributes"]["emotion"]["happiness"]
neutral = res["faces"][i]["attributes"]["emotion"]["neutral"]
import pickle, json
from facepp import API, File
users = []
for line in open('users_full.json'):
users.append(json.loads(line))
# get API Key and API Secret from faceplusplus.com
API_KEY = ''
API_SECRET = ''
api = API(API_KEY, API_SECRET)
i = 1
for user in users:
print("processing user #" + str(i) + " out of " + str(len(users)))
i = i + 1
try:
res = api.detect(image_url=user['profile_image_twitter'],
return_attributes='age')
faces = res['faces']
if (len(faces) > 0):
user['age_profile_image_twitter'] = faces[0]['attributes']['age'][
'value']
except:
continue
finally:
with open('users_full_age.json', 'a') as f:
json.dump(user, f)
f.write('\n')
# the server of international version
api_server_international = 'https://api-us.faceplusplus.com/facepp/v3/'
# Create a API object, if you are an international user,code: api = API(API_KEY, API_SECRET, srv=api_server_international)
api = API(API_KEY, API_SECRET, srv=api_server_international)
api.faceset.delete(outer_id=FACESET_ID, check_empty=0)
# create a Faceset to save FaceToken
ret = api.faceset.create(outer_id=FACESET_ID)
print_result("faceset create", ret)
# detect image
Face = {}
res = api.detect(image_file=File(target_face))
print_result(target, res)
target_token = res["faces"][0]["face_token"]
# save FaceToken in Faceset
api.faceset.addface(outer_id=FACESET_ID, face_tokens=[target_token])
t = 0
last_found = False
clips = []
t = 0
last_found = False
clips = []
video = VideoFileClip(filename='/Users/zhiminhe/wbq.mp4')
return [encode(i) for i in obj]
return obj
print hit
result = encode(result)
print '\n'.join(" " + i for i in pformat(result, width=75).split('\n'))
#导入SDK中的API类
from facepp import API, File
#创建一个API对象
api = API(API_KEY, API_SECRET)
#-----------------------------------------------------------------------------
# 创建一个Faceset用来存储FaceToken
ret = api.faceset.create(outer_id='face')
# 本地图片的地址
face_one = './gtl2.jpeg'
face_two = './demo.jpeg'
# 对图片进行检测
Face = {}
res = api.detect(image_file=File(face_one))
print_result("person_one", res)
Face['person_one'] = res["faces"][0]["face_token"]
res = api.detect(image_file=File(face_two))
print_result("person_two", res)
Face['person_two'] = res["faces"][0]["face_token"]
# 将得到的FaceToken存进Faceset里面
api.faceset.addface(outer_id='face', face_tokens=Face.itervalues())
class use_facepp:
def __init__(self, path):
self.path = path
self.api = API(API_KEY, API_SECRET, srv=api_server_international)
self.frame_count = 0
self.per_frame = 1
self.folder_list = []
self.video_list = {}
self.open_folder()
with open("log.txt", "w") as log:
print "reset log"
def open_folder(self):
self.folder_list = os.listdir(self.path)
for folder in self.folder_list:
#各フォルダーにJsonフォルダが無ければ作る
try:
os.mkdir(self.path+'/'+folder+"/Json")
except OSError:
pass
#Videoフォルダ内のファイル一全てをvideo_listに追加
self.video_list[folder] = os.listdir(self.path+'/'+folder+"/Video")
def main(self):
for folder in self.folder_list:
for video in self.video_list[folder]:
#カウントリセット
self.frame_count = 0
#動画名のフォルダを作成
try:
os.mkdir(self.path+'/'+folder+"/Json/"+video.split('.')[0])
except OSError:
pass
#Opencv用意
cap = cv2.VideoCapture(self.path+'/'+folder+"/Video/"+video)
while True:
ret, frame = cap.read()
if ret == False:
break
self.frame_count += 1
if (self.frame_count-1) % self.per_frame == 0:
cv2.imwrite("current.jpg", frame)
#ファイルがあったらパス
if os.path.isfile(self.path+'/'+folder+"/Json/"+video.split('.')[0]+'/'+video.split('.')[0]+'_'+str(self.frame_count)+".json") is True:
continue
res = self.api.detect(image_file=File("current.jpg"))
with open(self.path+'/'+folder+"/Json/"+video.split('.')[0]+'/'+video.split('.')[0]+'_'+str(self.frame_count)+".json", "w") as file:
json.dump(res, file, indent=4)
print "Finish: "+self.path+'/'+folder+'/Video/'+video
with open("log.txt", "a") as log:
log.write("Finish: "+self.path+'/'+folder+'/Video/'+video+'\n')
print "Finish: "+self.path+'/'+folder
with open("log.txt", "a") as log:
log.write("Finish: "+self.path+'/'+folder+'\n')
print "Finish All"
with open("log.txt", "a") as log:
log.write("Finish All")
os.remove("current.jpg")
# 创建一个Faceset用来存储FaceToken
#ret = api.faceset.create(outer_id='gtl')
# 本地图片的地址
face_1 = './gtl.jpeg'
face_2 = './gtl2.jpeg'
face_3 = './gtl3.jpg'
face_4 = './gtl4.jpg'
face_5 = './gtl5.jpg'
# 对图片进行检测
Face = {}
res = api.faceset.getdetail(outer_id='gtl')
print_result("111111", res)
res = api.detect(image_file=File(face_1))
print_result("person_1", res)
Face['person_1'] = res["faces"][0]["face_token"]
res = api.face.setuserid(face_token=Face['person_1'], user_id="古天乐")
api.faceset.addface(outer_id='gtl', face_tokens=Face.itervalues())
res = api.detect(image_file=File(face_2))
print_result("person_2", res)
Face['person_2'] = res["faces"][0]["face_token"]
res = api.face.setuserid(face_token=Face['person_2'], user_id="古天乐")
api.faceset.addface(outer_id='gtl', face_tokens=Face.itervalues())
res = api.detect(image_file=File(face_3))
print_result("person_3", res)
Face['person_3'] = res["faces"][0]["face_token"]
res = api.face.setuserid(face_token=Face['person_3'], user_id="古天乐")
from pprint import pformat
def print_result(hit, result):
def encode(obj):
if type(obj) is unicode:
return obj.encode('utf-8')
if type(obj) is dict:
return {encode(v): encode(k) for (v, k) in obj.iteritems()}
if type(obj) is list:
return [encode(i) for i in obj]
return obj
print hit
result = encode(result)
print '\n'.join(" " + i for i in pformat(result, width=75).split('\n'))
from facepp import API, File
api = API(API_KEY, API_SECRET)
ret = api.detect(image_file=File(face_search))
print_result("detect", ret)
print '=' * 60
search_result = api.search(face_token=ret["faces"][0]["face_token"],
outer_id=outer_id)
print_result('search', search_result)
print '=' * 60
time.sleep(2)
face_cascade = cv2.CascadeClassifier(
"/opt/ros/kinetic/share/OpenCV-3.3.1-dev/haarcascades/haarcascade_frontalface_alt2.xml"
) #导入opencv的参数
img = cv2.imread("/home/wyx/桌面/one_re/photo1.jpg") #读取照片信息
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) #得到灰度图像
faces = face_cascade.detectMultiScale(gray) #使用opencv自带库寻找照片中是否有人脸
if (len(faces) > 0): #返回值大于0 存在人脸
face_re = True
else:
face_re = False
time.sleep(2)
print face_re
if (face_re): #如何人脸存在
res = api.detect(api_key=API_KEY,
api_secret=API_SECRET,
image_file=File(img_re))
print_result(printFuctionTitle("人脸检测"), res)
# 人脸比对：https://console.faceplusplus.com.cn/documents/4887586
compare_res = api.compare(api_key=API_KEY,
api_secret=API_SECRET,
image_file1=File(img2_re),
image_file2=File(img_re))
#compare_res = api.compare(image_file1=File(face_search_img), image_file2=File(face_search_img))
print_result(printFuctionTitle("compare"), compare_res)
print compare_res.confidence #打印俩张照片的置信度 越高则越相似
# 人脸搜索：https://console.faceplusplus.com.cn/documents/4888381
# 人脸搜索步骤
# 1,创建faceSet:用于存储人脸信息(face_token)
# 2,向faceSet中添加人脸信息(face_token)
# 3，开始搜索
class FaceTask(object):
def __init__(self, dbpath=SHELVE_DB):
self.api = API(API_KEY, API_SECRET)
if RASPBERRYPI:
GPIO.setmode(GPIO.BCM)
GPIO.setup(BCM_PIN4_SHOW_TAKE_PHOTO, GPIO.OUT)
GPIO.output(BCM_PIN4_SHOW_TAKE_PHOTO, True)
try:
self.api.faceset.create(outer_id = 'default')
except APIError as e:
"""如果 'default' 已创建， 忽略改错误。"""
pass
self.camera_lock = threading.Lock()
def delete_faceset(self, outer_id):
try:
return self.api.faceset.delete(outer_id=outer_id, check_empty=0)
except APIError as e:
return str(e)
def add_faceset(self, outer_id):
try:
return self.api.faceset.create(outer_id=outer_id)
except APIError as e:
return str(e)
def get_facesets(self):
"""获取所有的faceset"""
try:
facesets = self.api.faceset.getfacesets()['facesets']
except KeyError:
return None
return [faceset['outer_id'] for faceset in facesets]
def get_faceset(self, outer_id='default'):
"""获取指定faceset中的face."""
faces = []
try:
detail = self.api.faceset.getdetail(outer_id = outer_id)
faces_tokens = detail['face_tokens']
except ValueError:
return None
except APIError:
return None
def get_faces_name(face_token):
face_detail = self.api.face.getdetail(face_token = face_token)
return face_detail.get('user_id', None)
tmp_executor = ThreadPoolExecutor()
return list(tmp_executor.map(get_faces_name, faces_tokens))
def upload_faces(self, outer_id='default', **kwargs):
"""上传face到指定的faceset
keyword args image_file or image_url
"""
name = kwargs.pop('name', None)
if name == None:
name = raw_input('Please enter the picture name:')
try:
face_token = self.api.detect(**kwargs)["faces"][0]["face_token"]
except (KeyError, IndexError):
return None
self.api.faceset.addface(outer_id=outer_id, face_tokens=face_token)
self.api.face.setuserid(face_token=face_token, user_id=name)
img = db.models.Image(name=name, path=kwargs.pop('image_path'), token=face_token)
img.save()
return face_token, name
def search_faces(self, face_token, outer_id='default'):
""" 根据face_token在指定的faceset中进行匹配搜索
"""
try:
results = self.api.search(face_token=face_token, outer_id=outer_id)['results']
except (KeyError):
return None
return [face['user_id'] for face in results if face['confidence'] > CONFIDENCE]
def search_people_from_camera(self, outer_id='default'):
if not RASPBERRYPI:
return None
image_name = '%s.jpg' % time.time()
GPIO.output(BCM_PIN4_SHOW_TAKE_PHOTO, 1)
cmd = 'sudo raspistill -t 2000 -o %s -p 100,100,300,200 -q 5' % image_name
GPIO.output(BCM_PIN4_SHOW_TAKE_PHOTO, 0)
with self.camera_lock:
os.system(cmd)
ret = self.api.detect(image_file=File(image_name))
try:
face_token=ret["faces"][0]["face_token"]
except (IndexError, KeyError):
if isinstance(ret, dict) and ('error_message' in ret.keys()):
return ret['error_message']
return 'The picture is invalid.'
return self.search_faces(face_token, outer_id=outer_id)
def update_faces_from_camera(self, outer_id='default'):
if not RASPBERRYPI:
return None
image_name = '%s.jpg'%time.time()
cmd = 'sudo raspistill -t 2000 -o %s -p 100,100,300,200 -q 5' % image_name
GPIO.output(BCM_PIN4_SHOW_TAKE_PHOTO, True)
with self.camera_lock:
os.system(cmd)
GPIO.output(BCM_PIN4_SHOW_TAKE_PHOTO, False)
return self.upload_faces(outer_id, image_file=File(image_name), image_path=image_name)
def clear(self):
if RASPBERRYPI:
GPIO.cleanup()
