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 __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 __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 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 face_grouping(uid, face_image_url):
api = API(constant.FACEPP_API_KEY, constant.FACEPP_API_SECRET)
rst = api.faceset.create()
faceset_id = rst['faceset_id']
for url in face_image_url:
for face in face_image_url[url]['face']:
res = api.faceset.add_face(faceset_id=faceset_id, face_id = face['face_id'])
session_id = api.grouping.grouping(faceset_id = faceset_id)
session_id = session_id['session_id']
rst = api.wait_async(session_id)
api.faceset.delete(faceset_id=faceset_id)
if not rst.has_key('result'):
raise Exception('API return error')
return rst['result']
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 is_person(self, image_file):
path = 'media/image/face.png'
# path = os.path.join('media/image/', image_file.filename)
image_file.save(path)
# import ipdb; ipdb.set_trace()
f = File(path)
api = API(API_KEY, API_SECRET, SERVER)
print("Sending face to api")
response = api.recognition.identify(group_name='Hackathoners', img=f)
print(response)
faces = response['face']
if len(faces) > 0:
face = faces[0]
name = face['candidate'][0]['person_name']
if name in self.people.keys():
print("Found " + name)
self.audio.add_to_playlist(self.people[name])
self.audio.play()
else:
self.audio.add_to_playlist('run.wav')
self.audio.play()
print("Did not match a person.")
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 facepp_detect():
API_KEY = '76f2ed8ab272e8793c990ae6c9e0a5e8'
API_SECRET = 'RdVvpVpLaBYi37eMfGzAa8drJyDtDBpE'
api = API(API_KEY, API_SECRET)
count = 0
for pic in POSITIVE_SAMPLES:
#if pic != "../data/positive_samples/IMG_7207.JPG":
# continue
st = time.time()
res = api.detection.detect(img = File(pic), mode = 'normal')
print pic,":",(time.time()-st)*1000,"ms"
if has_valid_pic(res):
count += 1
print pic,":YES"
else:
print pic,":NO",":",len(res['face'])
print "True Positive:",round(float(count)*100/len(POSITIVE_SAMPLES),2)
print "False Negative:",100 - round(float(count)*100/len(POSITIVE_SAMPLES),2)
count = 0
for pic in NEGTIVE_SAMPLES:
#if pic != "../data/negtive_samples/IMG_7404.JPG":
# continue
res = api.detection.detect(img = File(pic), mode='normal')
if not has_valid_pic(res):
count += 1
print pic,":YES"
else:
print pic,":NO",":",len(res['face'])
print "True Negative:",round(float(count)*100/len(NEGTIVE_SAMPLES),2)
print "False Positive:",100 - round(float(count)*100/len(NEGTIVE_SAMPLES),2)
def analysisPhoto(imgPath):
face1,face2,results,smile = 0, 0, 0, 0
api = API(APIKEY, APISCRETE)
try:
detect_res = api.detection.detect(img=File(imgPath))
except Exception,e:
print e
detect_res = {}
def processing():
api = API(API_KEY, API_SECRET)
#url = "http://blogs.reuters.com/great-debate/files/2013/07/obama-best.jpg"
result = api.detection.detect(img=File(
'C:/Users/Bhawana/Desktop/bhaw.jpg')) #to detect local images
#result = api.detection.detect(url=url) to detect online images
return print_result(result)
def test_facepp(pic):
#pic = '../data/negtive_samples/IMG_7404.JPG'
#pic = '../data/positive_samples/IMG_7116.JPG'
API_KEY = '76f2ed8ab272e8793c990ae6c9e0a5e8'
API_SECRET = 'RdVvpVpLaBYi37eMfGzAa8drJyDtDBpE'
api = API(API_KEY, API_SECRET)
res = api.detection.detect(img = File(pic), mode='normal')
print_result('detect result', res)
def getset():
API_KEY = "-PJkamhZzEUkUgv_wvopwTgVSWBVhblr"
API_SECRET = "1heuneo4ixxDAAAKmHrc_dGIP1NMhxne"
api_server_international = 'https://api-cn.faceplusplus.com/facepp/v3/faceset/getfacesets'
api = API(API_KEY, API_SECRET)
data = {"api_key":API_KEY, "api_secret":API_SECRET}
response = requests.post(api_server_international, data = data)
req_con = response.content.decode('utf-8')
req_dict = JSONDecoder().decode(req_con)
print(req_dict['facesets'])
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 __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 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 Oauth(key_file='', verifier_file='flickr.verifier'):
API_KEY = '0b9ca8fca8041e791d684c0b88fe5708'
API_SECRET = '4WlmUalSo3_SLScJyBaaJvgMCWjK3-WR'
flickr_key = '31573003eefcabb832334323de5027a0'
flickr_secret = 'f66472f76f1992ee'
flickr_api.set_keys(api_key=flickr_key, api_secret=flickr_secret)
a = flickr_api.auth.AuthHandler.load(verifier_file)
flickr_api.set_auth_handler(a)
face_api = API(API_KEY, API_SECRET)
return face_api
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)
class ImageDetector:
''' Image Detector class demo'''
file_path = None
api = None
def __init__(self, file_path):
self.file_path = file_path
self.api = API(API_KEY, API_SECRET)
def detect(self):
file = File(self.file_path)
middle_result = self.api.detection.detect(img=file)
result = self.api.wait_async(middle_result["session_id"])
return len(result['result']['face'])
def processing(name):
api = API(API_KEY, API_SECRET)
#url = "http://blogs.reuters.com/great-debate/files/2013/07/obama-best.jpg"
#result = api.detection.detect(img = File(os.path.join('uploads/',str(name)))) #to detect local images
#result = api.detection.detect(url=url) to detect online images
#return attributeExtractionToCsv(result)
print "going to take video"
vidcap = cv2.VideoCapture(os.path.join("video", name))
print "video captured"
count = 0
while count < 10:
print "image taking"
success, image = vidcap.read()
print 'Read a new frame: ', success
cv2.imwrite(os.path.join("Frames", "frame%d.jpg" % count),
image) # save frame as JPEG file
count += 1
print "image taken"
vidcap.set(cv2.CAP_PROP_POS_MSEC, count * 600)
fields = [
'File Name', 'Face Id', 'Distance b/w left eye and nose',
'Distance b/w right eye and nose',
'Distance b/w nose and left side of mouth',
'Distance b/w nose and right side of mouth'
]
initializeTestCSV(fields)
count = 0
for filename in os.listdir('Frames'):
if filename.endswith(".jpg") or filename.endswith(
".png") or filename.endswith(".jpeg"):
result = api.detection.detect(img=File(
os.path.join('Frames', filename))) #to detect local images
count = count + 1
attributeExtractionToCsv(result, fields, filename)
print "frame " + str(count)
else:
continue
return perplexedFinalResult()
def get_faceplusplus_keypoints(imagepath):
# face++ API access
api = API(apicfg.API_KEY, apicfg.API_SECRET, apicfg.SERVER)
img = cv2.imread(imagepath)
kpts_list = []
try:
faces = api.detection.detect(img=File(imagepath))
for face in faces['face']:
result = api.detection.landmark(face_id=face['face_id'])
keypoints = result['result'][0]['landmark']
for kpt in keypoints:
x = img.shape[1] * keypoints[kpt]['x']/100
y = img.shape[0] * keypoints[kpt]['y']/100
keypoints[kpt] = (x, y)
kpts_list.append(keypoints)
except Exception, e:
print e
def init():
import sys
import os.path
if sys.version_info.major != 2:
sys.exit('Python 2 is required to run this program')
fdir = None
if hasattr(sys, "frozen") and \
sys.frozen in ("windows_exe", "console_exe"):
fdir = os.path.dirname(os.path.abspath(sys.executable))
sys.path.append(fdir)
fdir = os.path.join(fdir, '..')
else:
fdir = os.path.dirname(__file__)
with open(os.path.join(fdir, 'apikey.cfg')) as f:
exec(f.read())
srv = locals().get('SERVER')
from facepp import API
return API(API_KEY, API_SECRET, srv=srv)
def face(img):
from pprint import pformat
from facepp import API
faceppAPI_KEY = 'db212fa5bc488db66c97808b2c9ef665'
faceppAPI_SECRET = 'lcv2MD_fMt2FeCyWrG91mZvDxutlu3OM'
api = API(faceppAPI_KEY, faceppAPI_SECRET)
rst = api.detection.detect(url = img)
gend = {'Male': 0, 'Female': 1}
peopletile = [["花样少年", "风华正茂", "当立男儿", "不惑壮士"],["豆蔻年华","风姿卓越","风韵犹存","徐娘半老"]]
def age_stage(age):
if age <16:
res = 0
elif age <30:
res = 1
elif age <40:
res = 2
else:
res = 3
return res
peopleindex = 1
reply = ''
print len(rst['face'])
if len(rst['face']) > 1:
reply = '别着急，让我喝口水一个一个说\n'
for face in rst['face']:
if len(rst['face']) > 1:
reply += '第'+str(peopleindex)+'位,'
peopleindex += 1
gender = face['attribute']['gender']['value']
age = face['attribute']['age']['value']
reply += '我看您'+ peopletile[gend[gender]][age_stage(age)]+', 心理年龄是'+str(age) +'岁'
reply += '\n'
#print_result("Name",rst)
return reply
img_re = './photo1.jpg'
img2_re = './photo.jpg'
# 此方法专用来打印api返回的信息
def print_result(hit, result):
print(hit)
print('\n'.join(" " + i for i in pformat(result, width=75).split('\n')))
def printFuctionTitle(title):
return "\n" + "-" * 60 + title + "-" * 60
# 初始化对象，进行api的调用工作
api = API()
# -----------------------------------------------------------人脸识别部分-------------------------------------------
# 人脸检测：https://console.faceplusplus.com.cn/documents/4888373
while True:
command = "fswebcam -d /dev/video0 -r 600*600 /home/wyx/桌面/one_re/photo1.jpg" #启动照相机 拍照
os.system(command)
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
import os
import sys
import cv2
import numpy as np
import contour
from facepp import API, File, APIError
API_KEY = 'bf7eae5ed9cf280218450523049d5f94'
API_SECRET = 'o6SeKJTnaoczTb-j6PBEGXvkiVz2hp71'
api = API(API_KEY, API_SECRET)
feature_list = [
'left_eyebrow_left_corner',
'right_eyebrow_right_corner',
'contour_chin',
]
def get_feature_points(face, w, h):
landmark = api.detection.landmark(face_id=face['face_id'], type='83p')
result = []
for v in feature_list:
x = landmark['result'][0]['landmark'][v]['x'] * w / 100
y = landmark['result'][0]['landmark'][v]['y'] * h / 100
result.append([x,y])
return result
if __name__ == '__main__':
if len(sys.argv) <= 1:
print "usage: %s <image src> <image dst>" % sys.argv[0]
exit(1)
# we assume that these a images are in the same pose bin
consumer_secret = auth.getconsumer_secret()
access_token = auth.getaccess_token()
access_token_secret = auth.getaccess_token_secret()
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.secure = True
auth.set_access_token(access_token, access_token_secret)
#Connect Google Maps API
gmaps = googlemaps.Client(key='AIzaSyCGwI22mO3khzq1_cttVxoBTK_auzfWEjI')
#Connect Face++ API
SERVER = 'http://api.us.faceplusplus.com/'
API_KEY = '3a7092b400dc9827359d7093801f057d'
API_SECRET = 'ChXgzhIEau8A1O_aKOanTS7dzY0AgVKQ'
facepp_api = API(API_KEY, API_SECRET, SERVER)
#Connect CouchDB
print 'Connecting CouchDB...'
data_base = connect_couchdb('http://115.146.89.191:5984/',
'melbourne_tweets_new')
#Prepare for ML Models
lemmatizer = nltk.stem.wordnet.WordNetLemmatizer()
wordSet = set(nltk.corpus.words.words())
stopwords = set(nltk.corpus.stopwords.words('english'))
hashtagwords_temp = []
text_training_set = "training_text_final.txt"
description_training_set = "training_description_final.txt"
prob_training_set = "training_prob_final.txt"
test_set = "test.txt"
def get_facepp_api():
from facepp import API
from djv.utils import get_api_secrets
return API(get_api_secrets()['facepp']['deja vu']['key'],
get_api_secrets()['facepp']['deja vu']['secret'])
if type(obj) is dict:
return {encode(k): encode(v) for (k, v) in obj.iteritems()}
if type(obj) is list:
return [encode(i) for i in obj]
return obj
print hint
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
api = API(API_KEY, API_SECRET)
# Here are the person names and their face images
# 人名及其脸部图片
IMAGE_DIR = 'http://cn.faceplusplus.com/static/resources/python_demo/'
PERSONS = [('Jim Parsons', IMAGE_DIR + '1.jpg'),
('Leonardo DiCaprio', IMAGE_DIR + '2.jpg'),
('Andy Liu', IMAGE_DIR + '3.jpg')]
TARGET_IMAGE = IMAGE_DIR + '4.jpg'
# Step 1: Detect faces in the 3 pictures and find out their positions and
# attributes
# 步骤1：检测出三张输入图片中的Face，找出图片中Face的位置及属性
FACES = {name: api.detection.detect(url=url) for name, url in PERSONS}
def InsertFaceTable(site, iline_list):
sql_command_insertface = "INSERT INTO FaceTable_{0} VALUES({1})".format(site, iline_list)
cur.execute(sql_command_insertface)
connection.commit()
# import csv
from facepp import API
import os
# csv数据name photoId userid photoTakeTime photoUploadTime photoTitle photoDescription photoGeotag longitude latitude accuracy url
API_KEY = "oSzQJ7Owxqk2T5yZuIHKoJ3s_n11BDQP"
API_SECRET = "6wv-sD-NgKWm0kRK757UxUDsbuzj0TYs"
api_server_international = 'https://api-us.faceplusplus.com/facepp/v3/'
api = API(API_KEY, API_SECRET, srv=api_server_international)
path = "C:\\Users\\HCHO\\Desktop\\data"
flickrDataFileUrl = []
flickrDataName = []
# 将os.walk在元素中提取的值，分别放到root（根目录），dirs（目录名），files（文件名）中。
# 将csv文件路径储存倒flickrDataFile数组中
for root, dirs, files in os.walk(path):
for file in files:
if ".csv" in file:
flickrDataFileUrl.append(os.path.join(root, file))
flickrDataName.append(file.replace('.csv', ''))
for j in range(0, 2):
CreateDetectTable(flickrDataName[j])
CreateFaceTable(flickrDataName[j])
if type(obj) is dict:
return {encode(k): encode(v) for (k, v) in obj.iteritems()}
if type(obj) is list:
return [encode(i) for i in obj]
return obj
print hint
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
from facepp import File
import os
api = API(API_KEY, API_SECRET)
#api.group.delete(group_name = 'test')
# Here are the person names and their face images
# 人名及其脸部图片
PERSONS = [
#(u'欧列川', '/Users/O/Downloads/TJ_Faces/788'),
(u'刘潇', '/Users/O/Downloads/TJ_Faces/787'),
(u'龚思宏', '/Users/O/Downloads/TJ_Faces/487'),
(u'邵玄', '/Users/O/Downloads/TJ_Faces/492'),
(u'王甜虾', '/Users/O/Downloads/TJ_Faces/786')
]
# IMAGES: PERSONS_NAME -> list of all person pictures
IMAGES = {}
for name, directory in PERSONS:
IMAGES[name] = []
for file in os.listdir(directory):
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
#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)
if type(obj) is dict:
return {encode(k): encode(v) for (k, v) in obj.iteritems()}
if type(obj) is list:
return [encode(i) for i in obj]
return obj
print hint
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
api = API(API_KEY, API_SECRET)
# Here are the person names and their face images
# 人名及其脸部图片
IMAGE_DIR = "http://cn.faceplusplus.com/static/resources/python_demo/"
PERSONS = [
("Jim Parsons", IMAGE_DIR + "1.jpg"),
("Leonardo DiCaprio", IMAGE_DIR + "2.jpg"),
("Andy Liu", IMAGE_DIR + "3.jpg"),
]
TARGET_IMAGE = IMAGE_DIR + "4.jpg"
# Step 1: Detect faces in the 3 pictures and find out their positions and
# attributes
# 步骤1：检测出三张输入图片中的Face，找出图片中Face的位置及属性
