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
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)
search_result = api.search(face_token=ret["faces"][0]["face_token"], outer_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
# 删除无用的人脸库
# delect faceset because it is no longer needed
api.faceset.delete(outer_id='test', check_empty=0)
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)
search_result = api.search(face_token=ret["faces"][0]["face_token"],
outer_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
# 删除无用的人脸库
# delect faceset because it is no longer needed
api.faceset.delete(outer_id='test', check_empty=0)
# 恭喜！您已经完成了本教程，可以继续阅读我们的API文档并利用Face++ API开始写您自
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'))
print_result("person_two", res)
Face['person_two'] = res["faces"][0]["face_token"]
"""
# save FaceToken in Faceset
api.faceset.addface(outer_id=FACESET_ID, face_tokens=[target_token])
for i in range(1, 500):
face_search = '/Users/zhiminhe/wbq/out' + str(i) + '.png'
print face_search,
found = False
# detect image and search same face
ret = api.detect(image_file=File(face_search))
# print_result("detect", ret)
for face in ret["faces"]:
search_result = api.search(face_token=face["face_token"],
outer_id=FACESET_ID)
# print result
# print_result('search', search_result)
# print '=' * 60
for result in search_result['results']:
if target_token == result[
'face_token'] and result['confidence'] > threshold:
found = True
break
if found:
break
if found:
print 'found'
else:
print 'not found'
# with open(face_two, 'rb') as f:
# content = f.read()
# ret = api.detect(image_file=File(content=content))
# print_result("detect", ret)
again = True
while (again):
again = False
try:
ret = api.detect(image_file=File(face_search))
print_result("detect", ret)
# time.sleep(5)
# search_result = api.search(face_token=ret["faces"][0]["face_token"], faceset_token='468d4f8ba70bddbf41aa9b3d2deeb04a')
search_result = api.search(
image_url=face_one,
faceset_token='468d4f8ba70bddbf41aa9b3d2deeb04a')
except APIError as e:
print "error happen:", str(e.body)
again = True
time.sleep(2)
# 输出结果
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
# 删除无用的人脸库
# delect faceset because it is no longer needed
'''
res = api.detect(image_file=File(face_four))
print_result("person_four", res)
Face['person_four'] = res["faces"][0]["face_token"]
# 将得到的FaceToken存进Faceset里面
# save FaceToken in Faceset
api.faceset.update(outer_id='mingxing', face_tokens=Face.itervalues())
print(" Faceset is already prepared!! ")
# 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='mingxing')
# 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
# 删除无用的人脸库
# delect faceset because it is no longer needed
###api.faceset.delete(outer_id='mingxing', check_empty=0)
#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 = './foo.jpg'
# 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='gtl')
# 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')
text = '你好! %s!%s'% \
(uers.decode('utf-8'),get_weather())
print(text)
#text2voice(text)
#mp3path1 = os.path.join(os.path.dirname(__file__), '1.mp3')
#os.system('mplayer %s' % mp3path1)
#os.remove(mp3path1)
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()
