def cv_Identifyfaces(identifyfaces, picture=None):
''' 運用 cv2 技術顯示的 Identifyfaces '''
import cv2
import numpy as np
# print('identifyfaces=',identifyfaces)
if len(identifyfaces) == 0:
cv_ImageText('沒有偵測到任何人！', '請按「ENTER」繼續')
return
for identifyface in identifyfaces:
faceimagepath = ClassUtils.getFaceImagepath(identifyface['faceId'])
if 'person' not in identifyface:
print('identifyface=', identifyface)
cv_ImageText('你哪位？請先訓練。', '按 ENTER 繼續', faceimagepath, picture,
identifyfaces)
else:
text = ClassUtils.textConfidence(identifyface['person']['name'],
identifyface['confidence'])
try:
print(text, identifyface['confidence'])
except UnicodeEncodeError as e:
print("UnicodeEncodeERROR!!", identifyface['confidence'])
#print('cv_Identifyfaces.identifyface=', identifyface)
# text = ClassUtils.textConfidence(identifyface['person']['name'],
# identifyface['confidence'])
cv_ImageText(text, '按 ENTER 繼續', faceimagepath, picture,
identifyfaces)
def cv_Identifyfaces(identifyfaces, picture=None):
''' 運用 cv2 技術顯示的 Identifyfaces '''
import cv2
import numpy as np
# print('identifyfaces=',identifyfaces)
if len(identifyfaces) == 0:
cv_ImageText('No Faces Detected', 'Press [ENTER] to continue ')
return
for identifyface in identifyfaces:
faceimagepath = ClassUtils.getFaceImagepath(identifyface['faceId'])
if 'person' not in identifyface:
print('identifyface=', identifyface)
cv_ImageText('Who is it?? Please train first!',
'Press [ENTER] to continue ', faceimagepath, picture,
identifyfaces)
else:
text = ClassUtils.textConfidence(identifyface['person']['name'],
identifyface['confidence'])
try:
print(text, identifyface['confidence'])
except UnicodeEncodeError as e:
print("UnicodeEncodeERROR!!", identifyface['confidence'])
#print('cv_Identifyfaces.identifyface=', identifyface)
# text = ClassUtils.textConfidence(identifyface['person']['name'],
# identifyface['confidence'])
cv_ImageText(text, '[ENTER] to continue ', faceimagepath, picture,
identifyfaces)
def takePicture_opencv(personGroupId, delay, typee):
if (ClassUtils.isWindows() or ClassUtils.isDarwin()):
picturepath = ClassCV.show_opencv(typee, mirror=True)
return picturepath
else:
print('若系統為樹莓派，則需設定 camera 為 CSIcamera 無法以 webcam 作為影像來源。')
return None
def play_gTTS(name, text):
start = int(round(time.time() * 1000))
print('開始計時 play_gTTS 0 ms: ', name, text)
#text = '_'.join(lazy_pinyin(text))
name = ClassUtils.protectPersonName(name)
mp3path = os.path.join(mp3base, name + text + ".mp3")
#print('gTTS:', str(name + text).encode("utf8"), 'mp3path:', mp3path, os.path.isfile(mp3path))
print('SPEED: play_gTTS mp3path', int(round(time.time() * 1000) - start),
'ms')
if os.path.isfile(mp3path) == False:
tts = gTTS(text=ClassUtils.protectPersonNameForTTS(name) + text,
lang='zh-tw')
tts.save(mp3path)
print('SPEED: play_gTTS savemp3',
int(round(time.time() * 1000) - start), 'ms')
sysstr = platform.system()
#print('system='+sysstr)
# print('SPEED: pygame play 前', int(round(time.time() * 1000) - start), 'ms')
# if (sysstr == "Windows"):
# print("Call Windows tasks")
# pygamee.mixer.init()
# pygamee.mixer.music.load(mp3path)
# pygamee.mixer.music.play()
# while pygamee.mixer.music.get_busy():
# pygamee.time.Clock().tick(10)
# elif (sysstr == "Darwin"):
# print("Call macOS tasks")
# pygamee.mixer.init()
# pygamee.mixer.music.load(mp3path)
# pygamee.mixer.music.play()
# while pygamee.mixer.music.get_busy():
# pygamee.time.Clock().tick(10)
# elif (sysstr == "Linux"):
# #os.system('omxplayer ' + mp3path +" > /dev/null 2>&1")
# pygamee.mixer.init()
# pygamee.mixer.music.load(mp3path)
# pygamee.mixer.music.play()
# while pygamee.mixer.music.get_busy() == True:
# continue
# else:
print("Call Other OS tasks")
pygamee.mixer.init()
pygamee.mixer.music.load(mp3path)
pygamee.mixer.music.play()
while pygamee.mixer.music.get_busy():
pygamee.time.Clock().tick(5)
print('SPEED: pygame play 後', int(round(time.time() * 1000) - start), 'ms')
def get_a_person(self, personId, personGroupId):
headers = {
# Request headers
'Ocp-Apim-Subscription-Key': self.api_key,
}
params = urllib.parse.urlencode({})
try:
conn = http.client.HTTPSConnection(self.host)
conn.request(
"GET", "/face/v1.0/persongroups/" + personGroupId +
"/persons/" + personId + "?%s" % params, "{body}", headers)
response = conn.getresponse()
data = response.read()
personjson = json.loads(str(data, 'UTF-8'))
conn.close()
try:
if ClassUtils.isFaceAPIError(personjson):
return None
except MyException.RateLimitExceededError as e:
time.sleep(10)
return self.get_a_person(personId, personGroupId)
except MyException.UnspecifiedError as e:
return
except MyException.PersonGroupNotTrainedError as e:
print('ERROR: get_a_person.PersonGroupNotTrainedError')
return
return personjson
except Exception as e:
print("[Errno {0}]連線失敗！請檢查網路設定。 {1}".format(e.errno, e.strerror))
def personGroup_status(self, personGroupId):
print("personGroup_status: 查看一個 personGroup 的狀態，也就是看看訓練是否成功！")
headers = {
# Request headers
'Ocp-Apim-Subscription-Key': self.api_key,
}
params = urllib.parse.urlencode({'personGroupId': personGroupId})
try:
conn = http.client.HTTPSConnection(self.host)
conn.request(
"GET", "/face/v1.0/persongroups/" + personGroupId +
"/training?%s" % params, "{body}", headers)
response = conn.getresponse()
data = response.read()
status = json.loads(str(data, 'UTF-8'))
conn.close()
except Exception as e:
print("[Errno {0}]連線失敗！請檢查網路設定。 {1}".format(e.errno, e.strerror))
try:
if ClassUtils.isFaceAPIError(status):
return None
return status
except MyException.UnspecifiedError as e:
return
def getPersonGroup(self, personGroupId):
print('搜尋 personGroupid =', personGroupId)
headers = {
# Request headers
'Ocp-Apim-Subscription-Key': self.api_key,
}
params = urllib.parse.urlencode({})
try:
conn = http.client.HTTPSConnection(self.host)
conn.request(
"GET",
"/face/v1.0/persongroups/" + personGroupId + "?%s" % params,
"{body}", headers)
response = conn.getresponse()
data = response.read()
personGroup = json.loads(str(data, 'UTF-8'))
conn.close()
except Exception as e:
print("[Errno {0}]連線失敗！請檢查網路設定。 {1}".format(e.errno, e.strerror))
try:
if ClassUtils.isFaceAPIError(personGroup):
pass
return personGroup
except MyException.UnspecifiedError as e:
return
def __detectFaces_Save(self, detectFaces, imagepath):
for detectface in detectFaces:
print("faceRectangle = ", detectface['faceRectangle'])
print("faceId = ", detectface['faceId'])
left = detectface['faceRectangle']['left']
top = detectface['faceRectangle']['top']
height = detectface['faceRectangle']['height']
width = detectface['faceRectangle']['width']
img = Image.open(imagepath)
draw = ImageDraw.Draw(img)
if config['landmark'] > 0:
print("save facelandmarks=", detectface['faceLandmarks'])
for faceLandmark in detectface['faceLandmarks']:
print('faceLandmark=', faceLandmark)
print('faceLandmark=',
detectface['faceLandmarks'][faceLandmark])
x = int(detectface['faceLandmarks'][faceLandmark]['x'])
y = int(detectface['faceLandmarks'][faceLandmark]['y'])
draw.ellipse(
(x, y, x + config['landmark'], y + config['landmark']),
fill=(255, 0, 0))
#faceRectangle = {'top': 141, 'height': 261, 'width': 261, 'left': 664}
faceonly = img.crop((left, top, left + width, top + height))
saveFaceImagepath = ClassUtils.getFaceImagepath(
detectface['faceId'])
faceonly.save(saveFaceImagepath, 'PNG')
def ListPersonGroups(self):
#print('列出所有的 person Groups')
headers = {
# Request headers
'Ocp-Apim-Subscription-Key': self.api_key,
}
params = urllib.parse.urlencode({
# Request parameters
#'start': '{string}',
'top': '1000',
})
try:
conn = http.client.HTTPSConnection(self.host)
conn.request("GET", "/face/v1.0/persongroups?%s" % params,
"{body}", headers)
response = conn.getresponse()
data = response.read()
personGroups = json.loads(str(data, 'UTF-8'))
conn.close()
except Exception as e:
print("[Errno {0}]連線失敗！請檢查網路設定。 {1}".format(e.errno, e.strerror))
try:
if ClassUtils.isFaceAPIError(personGroups):
return []
except MyException.RateLimitExceededError as e:
time.sleep(10)
return self.ListPersonGroups()
except MyException.UnspecifiedError as e:
return
return personGroups
def SuccessesGUI(successes):
''' 多位成功者放在同一個視窗 '''
print('STEP 0')
root = tk.Tk()
print('STEP 0.1')
root.geometry('400x400')
print('STEP 1')
scrollbar = tk.Scrollbar(root)
scrollbar.pack(side=tk.RIGHT, fill=tk.Y)
print('STEP 2')
mylist = tk.Listbox(root,
font="Helvetica 18 bold",
yscrollcommand=scrollbar.set)
y = 10
for success in successes:
#imagepath = ClassUtils.getFaceImagepath(success['faceId'])
#imagefile = __saveImg(imagepath)
#canvas = tk.Canvas(root, height=imagefile.height()*len(successes), width=imagefile.width()*5)
#canvas.create_image(10, y, anchor="nw", image=imagefile)
#y += 10
mylist.insert(
tk.END,
ClassUtils.protectPersonName(success['person']['name']) + '簽到成功！！')
print('STEP 3')
#canvas.pack()
mylist.pack(side=tk.LEFT, fill=tk.BOTH)
scrollbar.config(command=mylist.yview)
print('STEP 4')
root.call('wm', 'attributes', '.', '-topmost', '1')
root.mainloop()
def takePicture_CSI(personGroupId, delay, size='small'):
# delay in ms 3000ms = 3s
# jpgimagepath = os.path.join(basepath, 'takepictures', personGroupId + "_" + time.strftime(
# "%Y%m%d_%H%M%S", time.localtime()) + ".jpg")
picturepath = ClassUtils.getTakePicturePath(personGroupId)
if not os.path.exists(os.path.dirname(picturepath)):
os.makedirs(os.path.dirname(picturepath))
try:
# small for 辨識，加快速度。
if size == 'small':
subprocess.call([
'raspistill', '-hf', '-w', '800', '-h', '450', '-t',
str(delay), '-o', picturepath
])
else: # for 訓練。訓練用圖片可以比較大
subprocess.call([
'raspistill', '-hf', '-w', '1600', '-h', '900', '-t',
str(delay), '-o', picturepath
])
except OSError:
# ClassMessageBox.FaceAPIErrorGUI('def takePicture_CSI', 'CSI 攝影機無法啟動！',
# 'OSError: raspistill 無法執行或不存在！！')
print('def takePicture_CSI', 'CSI 攝影機無法啟動！',
'OSError: raspistill 無法執行或不存在！！')
return None
#os.system("raspistill -t " + str(delay) + " -o " + imagepath)
return picturepath
def takePicture(personGroupId, delay, type='Identify', size='small'):
sysstr = platform.system()
print('os=', sysstr, platform.release())
if ClassUtils.isLinux():
return takePicture_CSI(personGroupId, delay, size)
else:
return takePicture_opencv(personGroupId, delay, type)
def Identify(self, pictureurl):
''' 14: 進行「辨識」，使用 image URL or 檔案路徑 '''
start = int(round(time.time() * 1000))
print('開始計時 identify')
faceApi = FaceAPI.Face(api_key, host)
personApi = FaceAPI.Person(api_key, host)
print('載入 class', int(round(time.time() * 1000) - start), 'ms')
#imageurl = input('請輸入準備要辨識的 image URL or 檔案路徑:')
if pictureurl.startswith('http'):
detectfaces = faceApi.detectURLImages(pictureurl)
else:
pictureurl = pictureurl.strip()
statinfo = os.stat(pictureurl)
print('檔案大小：', statinfo.st_size, 'Bytes')
if statinfo.st_size < 1024:
print('圖檔太小 不可小於 1KB')
sys.exit(1)
elif statinfo.st_size > 4 * 1024 * 1024:
print('圖檔太大 不可大於 4MB')
im = Image.open(pictureurl)
out = im.resize((128, 128))
im.save(pictureurl, "JPEG")
print('out=', type(out))
detectfaces = faceApi.detectLocalImage(pictureurl)
# if len(detectfaces) == 0:
# print('相片中找不到人！')
# sys.exit(1)
faceids = []
for detectface in detectfaces:
print('所偵測到的 faceId=', detectface['faceId'])
faceids.append(detectface['faceId'])
print('Identify.detectfaces=', detectfaces)
try:
identifiedfaces = faceApi.identify(faceids[:10], personGroupId)
print('在所提供的相片中偵測到 identifyfaces 共 ', len(identifiedfaces), '個')
except MyException.PersonGroupNotTrainedError as e:
print('接到例外！MyException.PersonGroupNotTrainedError as e')
print('Identify.detectedFaces=', detectfaces)
ClassCV.cv_Identifyfaces(detectfaces, pictureurl)
#ClassTK.tk_UnknownPerson('texttest....', pictureurl, pictureurl)
return
print('在所提供的相片中偵測到 identifyfaces 共 ', len(identifiedfaces), '個')
# successes = []
for identifiedface in identifiedfaces:
for candidate in identifiedface['candidates']:
personId = candidate["personId"]
person = personApi.get_a_person(personId, personGroupId)
identifiedface['person'] = person
identifiedface['confidence'] = candidate["confidence"]
identifiedface['personId'] = candidate["personId"]
Utils.SigninIdentifyfaces(identifiedfaces, pictureurl)
def totalDistance(self):
# AIzaSyA7_9tSb7YwCpul5IF_edGnqGUO6Q1Zed8 for Geocoding
backToBacks = self.findBackToBacks()
if len(backToBacks) > 0:
self.distance = 0
for classPair in backToBacks:
distance = ClassUtils.findDistanceBetweenTwoClasses(classPair)
self.distance += distance
return self.distance
def identify(self, faceidkeys, personGroupId):
print("def Face.identify 開始辨識。faceidkeys=", faceidkeys)
if len(faceidkeys) == 0:
return []
start = int(round(time.time() * 1000))
print('開始辨識 identify 0 ms')
headers = {
# Request headers
'Content-Type': 'application/json',
'Ocp-Apim-Subscription-Key': self.api_key,
}
params = urllib.parse.urlencode({})
requestbody = '''{
"personGroupId": "''' + personGroupId + '''",
"faceIds":''' + str(faceidkeys) + ''',
"maxNumOfCandidatesReturned":1,
"confidenceThreshold": ''' + str(config['confidence']) + '''
}'''
#print('requestbody=', requestbody)
try:
conn = http.client.HTTPSConnection(self.host)
conn.request("POST", "/face/v1.0/identify?%s" % params,
requestbody, headers)
response = conn.getresponse()
data = response.read()
identifiedfaces = json.loads(str(data, 'UTF-8'))
print('Face.Identify.identifiedfaces=', identifiedfaces)
conn.close()
# ClassUtils.tryFaceAPIError(identifyfaces)
except Exception as e:
print("[Errno {0}]連線失敗！請檢查網路設定。 {1}".format(e.errno, e.strerror))
sys.exit()
try:
if ClassUtils.isFaceAPIError(identifiedfaces):
return []
except MyException.RateLimitExceededError as e:
time.sleep(10)
return self.identify(faceidkeys, personGroupId)
except MyException.PersonGroupNotFoundError as e:
personGroupAPI = PersonGroup(self.api_key, self.host)
personGroupAPI.createPersonGroup(personGroupId,
config['personGroupName'],
'group userdata')
return self.identify(faceidkeys, personGroupId)
except MyException.UnspecifiedError as e:
return []
except MyException.PersonGroupNotTrainedError as e:
print('丟出 MyException.PersonGroupNotTrainedError 例外')
raise
print('超過 raise')
# if ClassUtils.isFaceAPIError(identifyfaces):
# return []
return identifiedfaces
def detectLocalImage(self, imagepath):
start = int(round(time.time() * 1000))
print('開始計時 detectLocalImage 0 ms')
headers = {
# Request headers
'Content-Type': 'application/octet-stream', # 用本地圖檔辨識
'Ocp-Apim-Subscription-Key': self.api_key,
}
params = urllib.parse.urlencode({
# Request parameters
'returnFaceId':
'true',
'returnFaceLandmarks':
'true',
'returnFaceAttributes':
'age,gender,emotion'
})
#'age,gender,headPose,smile,facialHair,glasses,emotion,hair,makeup,occlusion,accessories,blur,exposure'
print('imagepath=', imagepath)
requestbody = open(imagepath, "rb").read()
try:
conn = http.client.HTTPSConnection(self.host)
conn.request("POST", "/face/v1.0/detect?%s" % params, requestbody,
headers)
response = conn.getresponse()
data = response.read()
print('detectLocalImage.data=', data)
detectfaces = json.loads(str(data, 'UTF-8'))
print("detectLocalImage.faces=", detectfaces)
#print(parsed[0]['faceId'])
#faceids.append(parsed[0]['faceId'])
conn.close()
try:
if ClassUtils.isFaceAPIError(detectfaces):
return []
except MyException.RateLimitExceededError as e:
time.sleep(10)
return self.detectLocalImage(imagepath)
except MyException.PersonGroupNotTrainedError as e:
print(
'ERROR: detectLocalImage MyException.PersonGroupNotTrainedError'
)
return
except MyException.UnspecifiedError as e:
return
print("detectLocalImage:",
imagepath + "偵測到 {0} 個人".format(len(detectfaces)))
self.__detectFaces_Save(detectfaces, imagepath)
return detectfaces
except Exception as e:
print("[Errno {0}]連線失敗！請檢查網路設定。 {1}".format(e.errno, e.strerror))
def __init__(self, message):
self.message = message
text = 'API KEY 已經失效，請到 config 設定有效的 API KEY。'
print(text)
if ClassUtils.isLinux():
print(text)
else:
# import ClassMessageBox
# ClassMessageBox.MessageGUI(message, text)
print(text)
ClassCV.cv_ImageText('「驗證失敗」', text)
def add_a_person_face(self, imagepath, personId, personGroupId):
print("'add_a_person_face': 用一個圖片放入一個 person 當中 personId=" + personId,
'imagepath=', imagepath)
#display(Image(url=imagepath))
headers = {
# Request headers
# 'Content-Type': 'application/json',
'Content-Type': 'application/octet-stream', #上傳圖檔
'Ocp-Apim-Subscription-Key': self.api_key,
}
params = urllib.parse.urlencode({
# Request parameters
'personGroupId': personGroupId,
#'personId': '03cb1134-ad35-4b80-8bf2-3200f44eef31',
'personId': personId,
#'userData': '{string}',
#'targetFace': '{string}',
})
#"https://lh3.googleusercontent.com/AuJtzSdWCTZ6pWW9pMxec86gVZEjP00O7qvl8RNbzYfmJvsiUfDL-BXfel5Sw2jgPNUy7rcIVQ-HFDxDEFuIZxp56NpKwOjYncgMjL_dt0-FnoBIYyUpplx4LlE5ShN2hJ3-URLwOA4=w597-h796-no"
# requestbody = '{"url": "'+imageurl+'"}'
requestbody = open(imagepath, "rb").read()
try:
conn = http.client.HTTPSConnection(self.host)
conn.request(
"POST", "/face/v1.0/persongroups/" + personGroupId +
"/persons/" + personId + "/persistedFaces?%s" % params,
requestbody, headers)
response = conn.getresponse()
data = response.read()
jsondata = json.loads(str(data, 'UTF-8'))
conn.close()
# if 'error' in jsondata:
# if 'RateLimitExceeded' == jsondata['error']['code']:
# time.sleep(10)
# else:
# print("EXCEPTION: ", jsondata['error']['code'] + ":",
# jsondata['error']['message'])
except Exception as e:
print("[Errno {0}]連線失敗！請檢查網路設定。 {1}".format(e.errno, e.strerror))
try:
if ClassUtils.isFaceAPIError(jsondata):
return []
except MyException.RateLimitExceededError as e:
time.sleep(10)
return self.add_a_person_face(imagepath, personId, personGroupId)
except MyException.UnspecifiedError as e:
return
def traindatas(self, traindatasPath):
''' 請輸入 traindatasPath 的絕對路徑。
請提供資料路徑如： /xxx/xxx/traindatas/
該路徑內的資料夾結構必須為 [userData/姓名/xxxx.jpg]
'''
#traindataPath = basepath + '/traindatas/'
#traindataPath = os.path.join(basepath, 'traindatas')
Utils.makedirsPath(traindatasPath)
train_userDataPaths = os.listdir(traindatasPath)
print('目前 traindatas/ 內的圖檔如下：')
for userDataPath in train_userDataPaths:
userDataPath = os.path.join(traindatasPath, userDataPath)
if os.path.basename(userDataPath).startswith('.') or os.path.isdir(
userDataPath) == False:
print(userDataPath)
print('continue')
continue
for personnamePath in os.listdir(userDataPath):
#print("file="+ os.path.join(traindataPath, trainfile))
personname = os.path.basename(personnamePath)
personpath = os.path.join(traindatasPath, userDataPath,
personname)
if os.path.isdir(personpath):
print("person name=", personname)
personImagePaths = []
for personImagePath in os.listdir(personpath):
personImagePaths.append(
os.path.join(personpath, personImagePath))
print(personGroupId, personname, personImagePaths)
personAPI = FaceAPI.Person(api_key, host)
personAPI.add_personimages(personGroupId, personname,
os.path.basename(userDataPath),
personImagePaths)
#time.sleep(6)
personGroupapi = FaceAPI.PersonGroup(api_key, host)
personGroupapi.train_personGroup(personGroupId)
def cv_ImageText(title, hint, facepath=None, picture=None, identifyfaces=None):
''' 標準 cv 視窗'''
import cv2
import numpy as np
if facepath == None:
img = np.zeros((400, 400, 3), np.uint8)
img.fill(90)
else:
img = cv2.imread(facepath)
print('__cv_ImageText.imagepath=', facepath)
H, W = img.shape[:2]
img = cv2.resize(img, (400, int(H / W * 400)))
windowname = facepath
H, W = img.shape[:2]
#img = cv2.resize(img, (400,int(H/W*400)))
ttf = ClassUtils.getSystemFont()
cv2_im = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) # cv2和PIL中颜色的hex码的储存顺序不同
pil_im = Image.fromarray(cv2_im)
draw = ImageDraw.Draw(pil_im) # 括号中为需要打印的canvas，这里就是在图片上直接打印
titlefont = ImageFont.truetype(ttf, 24, encoding="utf-8")
hintfont = ImageFont.truetype(ttf, 18, encoding="utf-8")
w, h = draw.textsize(title, font=titlefont)
draw.rectangle(((W / 2 - w / 2 - 5, 0), (W / 2 + w / 2 + 5, h + 20)),
fill="black")
titlelocation = (W / 2 - w / 2, 5)
if identifyfaces != None and len(identifyfaces) == 1:
hint = hint + "or [a] for new ID"
w, h = draw.textsize(hint, font=hintfont)
draw.rectangle(((W / 2 - w / 2 - 5, H - h), (W / 2 + w / 2 + 5, H)),
fill="red")
hintlocation = (W / 2 - w / 2, H - h)
draw.text(titlelocation, title, (0, 255, 255), font=titlefont)
draw.text(hintlocation, hint, (0, 255, 0), font=hintfont)
cv2_text_im = cv2.cvtColor(np.array(pil_im), cv2.COLOR_RGB2BGR)
cv2.imshow(windowname, cv2_text_im)
key = cv2.waitKey(10000)
if key == ord(' ') or key == 3 or key == 13: # space or enter
cv2.destroyWindow(windowname)
elif key == ord('a') and len(identifyfaces) == 1: # 鍵盤 a 代表要新增 oneshot
cv2.destroyWindow(windowname)
ClassTK.tk_UnknownPerson('您哪位？', facepath, picture)
def detectURLImages_NoDownload(self, imageurl):
headers = {
# Request headers
'Content-Type': 'application/json', #
'Ocp-Apim-Subscription-Key': self.api_key,
}
params = urllib.parse.urlencode({
# Request parameters
'returnFaceId':
'true',
'returnFaceLandmarks':
'false',
'returnFaceAttributes':
'age,gender,emotion'
})
#'age,gender,headPose,smile,facialHair,glasses,emotion,hair,makeup,occlusion,accessories,blur,exposure'
print('imageurl=', imageurl)
requestbody = '{"url": "' + imageurl + '"}'
try:
conn = http.client.HTTPSConnection(self.host)
conn.request("POST", "/face/v1.0/detect?%s" % params, requestbody,
headers)
response = conn.getresponse()
data = response.read()
detectfaces = json.loads(str(data, 'UTF-8'))
print("detecURLImage.faces 偵測到 faces 長度=", len(detectfaces))
for index, face in enumerate(detectfaces):
print('face[' + str(index) + ']=', face)
conn.close()
except Exception as e:
print("[Errno {0}]連線失敗！請檢查網路設定。 {1}".format(e.errno, e.strerror))
#return []
try:
if ClassUtils.isFaceAPIError(detectfaces):
return []
except MyException.RateLimitExceededError as e:
time.sleep(10)
return self.detectURLImages(imageurl)
except MyException.UnspecifiedError as e:
return
self.__detectFaces_Save(detectfaces, imageurl)
return detectfaces
def list_persons_in_group(self, personGroupId):
headers = {
# Request headers
'Ocp-Apim-Subscription-Key': self.api_key,
}
params = urllib.parse.urlencode({
# Request parameters
#'start': '{string}',
#'top': '1000',
})
try:
conn = http.client.HTTPSConnection(self.host)
conn.request(
"GET", "/face/v1.0/persongroups/" + personGroupId +
"/persons?%s" % params, "{body}", headers)
response = conn.getresponse()
data = response.read()
persons = json.loads(str(data, 'UTF-8'))
conn.close()
try:
if ClassUtils.isFaceAPIError(persons):
pass
except MyException.RateLimitExceededError as e:
time.sleep(10)
return self.list_persons_in_group(personGroupId)
except MyException.PersonGroupNotFoundError as e:
self.createPersonGroup(config['personGroupId'],
config['personGroupName'],
'group userdata')
return self.list_persons_in_group(config['personGroupId'])
if 'error' in persons:
message = '取得 persons 出錯！\n'
message += '錯誤編號 = ' + persons['error']['code'] + '\n'
message += '錯誤訊息 = ' + persons['error']['message']
raise MyException.responseError(message)
return persons
except Exception as e:
print("[Errno {0}]連線失敗！請檢查網路設定。 {1}".format(e.errno, e.strerror))
def list_persons_in_group(self, personGroupId):
print("'list_persons_in_group'")
headers = {
# Request headers
'Ocp-Apim-Subscription-Key': self.api_key,
}
params = urllib.parse.urlencode({
# Request parameters
#'start': '{string}',
#'top': '1000',
})
try:
conn = http.client.HTTPSConnection(self.host)
conn.request(
"GET", "/face/v1.0/persongroups/" + personGroupId +
"/persons?%s" % params, "{body}", headers)
response = conn.getresponse()
data = response.read()
persons = json.loads(str(data, 'UTF-8'))
#print('def list_persons_in_group:', persons)
conn.close()
except Exception as e:
print("[Errno {0}]連線失敗！請檢查網路設定。 {1}".format(e.errno, e.strerror))
return []
try:
if ClassUtils.isFaceAPIError(persons):
return []
except MyException.RateLimitExceededError as e:
time.sleep(10)
return self.list_persons_in_group(personGroupId)
except MyException.PersonGroupNotFoundError as e:
personGroupAPI = PersonGroup(self.api_key, self.host)
personGroupAPI.createPersonGroup(config['personGroupId'],
config['personGroupName'],
'group userdata')
return self.list_persons_in_group(personGroupId)
except MyException.UnspecifiedError as e:
return
return persons
def create_a_person(self, personGroupId, name, userData):
print("'create_a_person': 在 personGroupid=" + personGroupId +
" 裡 建立一個 person name=" + name)
headers = {
# Request headers
'Content-Type': 'application/json',
'Ocp-Apim-Subscription-Key': self.api_key,
}
params = urllib.parse.urlencode({'personGroupId': personGroupId})
requestbody = '{"name":"' + name + '","userData":"' + userData + '"}'
try:
conn = http.client.HTTPSConnection(self.host)
conn.request(
"POST", "/face/v1.0/persongroups/" + personGroupId +
"/persons?%s" % params, requestbody.encode('UTF-8'), headers)
response = conn.getresponse()
data = response.read()
create_a_person_json = json.loads(str(data, 'UTF-8'))
conn.close()
except Exception as e:
print("[Errno {0}]連線失敗！請檢查網路設定。 {1}".format(e.errno, e.strerror))
try:
if ClassUtils.isFaceAPIError(create_a_person_json):
return []
except MyException.RateLimitExceededError as e:
time.sleep(10)
return self.create_a_person(personGroupId, name, userData)
except MyException.PersonGroupNotFoundError as e:
personGroupApi = PersonGroup(self.api_key, self.host)
personGroupApi.createPersonGroup(config['personGroupId'],
config['personGroupName'],
'group userdata')
return self.create_a_person(personGroupId, name, userData)
except MyException.UnspecifiedError as e:
return
return create_a_person_json['personId']
def show_opencv(typee, mirror=False):
''' 顯示主畫面 '''
import cv2
import numpy as np
config = ClassUtils.loadConfig()
cam = cv2.VideoCapture(config['videoid'])
cam.set(3, 1280) # 修改解析度 寬
cam.set(4, 1280 // 16 * 9) # 修改解析度 高
print('WIDTH', cam.get(3), 'HEIGHT', cam.get(4)) # 顯示預設的解析度
while True:
ret_val, img = cam.read()
# Add for face detection, ottowei , 2019011701
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Load the Haar cascade file
face_cascade = cv2.CascadeClassifier(
'haar_cascade_files/haarcascade_frontalface_default.xml')
# Run the face detector on the grayscale image
face_rects = face_cascade.detectMultiScale(gray, 1.3, 5)
# Draw a rectangle around the face
for (x, y, w, h) in face_rects:
cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 3)
if mirror:
img = cv2.flip(img, 1)
H, W = img.shape[:2]
#imS = cv2.resize(img, (W, H))
cv2_im = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) # cv2和PIL中颜色的hex码的储存顺序不同
pil_im = Image.fromarray(cv2_im)
draw = ImageDraw.Draw(pil_im) # 括号中为需要打印的canvas，这里就是在图片上直接打印
ttf = ClassUtils.getSystemFont()
font = ImageFont.truetype(ttf, 40, encoding="utf-8")
hintfont = ImageFont.truetype(ttf, 24, encoding="utf-8")
title = config['title'] + ""
w, h = draw.textsize(title, font=font)
draw.rectangle(((W / 2 - w / 2 - 5, 0), (W / 2 + w / 2 + 5, h + 20)),
fill="black")
titlelocation = (W / 2 - w / 2, 5)
#textlocation = (0,0)
draw.text(titlelocation, title, (0, 255, 255),
font=font) # 第一个参数为打印的坐标，第二个为打印的文本，第三个为字体颜色，第四个为字体
# FreeAPIKEY: b9160fbd882f47bd821205a4bce64354
if config['api_key'] == 'b9160fbd882f47bd821205a4bce64354':
warningfont = ImageFont.truetype(ttf, 24, encoding="utf-8")
warning = "請注意，您目前是用的是共用的測試 API_KEY 請儘速自行申請一個自用的 KEY"
w, h = draw.textsize(warning, font=warningfont)
draw.rectangle(
((W / 2 - w / 2 - 5, H - h * 2), (W / 2 + w / 2 + 5, H - h)),
fill="yellow")
warninglocation = (W / 2 - w / 2, H - h * 2)
draw.text(
warninglocation, warning, (0, 0, 255),
font=warningfont) # 第一个参数为打印的坐标，第二个为打印的文本，第三个为字体颜色，第四个为字体
if typee == 'Identify':
hint = "Please Press [ENTER] to Identify"
elif typee == 'Train':
hint = "Please Press [ENTER] to take triple photos"
else:
hint = "Please Press [ENTER] to continue"
w, h = draw.textsize(hint, font=hintfont)
draw.rectangle(((W / 2 - w / 2 - 5, H - h), (W / 2 + w / 2 + 5, H)),
fill="red")
hintlocation = (W / 2 - w / 2, H - h)
#textlocation = (0,0)
draw.text(hintlocation, hint, (0, 255, 255),
font=hintfont) # 第一个参数为打印的坐标，第二个为打印的文本，第三个为字体颜色，第四个为字体
cv2_text_im = cv2.cvtColor(np.array(pil_im), cv2.COLOR_RGB2BGR)
if ClassUtils.isWindows():
cv2.namedWindow("window", cv2.WND_PROP_FULLSCREEN)
cv2.setWindowProperty("window", cv2.WND_PROP_FULLSCREEN,
cv2.WINDOW_FULLSCREEN)
cv2.imshow("window", cv2_text_im)
#cv2.imshow("window", img)
key = cv2.waitKey(1)
if key == ord(' ') or key == 3 or key == 13: # space or enter
picturepath = ClassUtils.getTakePicturePath(
config['personGroupId'])
cv2.imwrite(picturepath, img)
cv2.destroyAllWindows()
cv2.VideoCapture(config['videoid']).release()
return picturepath
elif key == 27: # esc to quit
cv2.destroyAllWindows()
cv2.VideoCapture(config['videoid']).release()
raise MyException.esc_opencv("偵測到 esc 結束鏡頭")
else:
if key != -1:
print('key=', key)
def detectURLImages(self, imageurl):
''' 下載後，用 detectLocalImage 上傳辨識 '''
jpgimagepath = ClassUtils.getTakePicturePath(config['personGroupId'])
print('jpgimagepath:', jpgimagepath)
request.urlretrieve(imageurl, jpgimagepath)
return self.detectLocalImage(jpgimagepath)
#!/usr/bin/env python
import sys, os, json, time, fire
from PIL import Image
import ClassFaceAPI as FaceAPI
import ClassCamera as Camera
import ClassUtils as Utils
from pypinyin import lazy_pinyin
import MyException, ClassTK, ClassCV
basepath = os.path.dirname(os.path.realpath(__file__))
config = Utils.loadConfig()
personGroupId = config['personGroupId']
api_key = config['api_key']
host = config['host']
class FacePI:
''' FacePI 文字介面
搭配參數如下：
createGroup: 建立一個 PersonGroup
deleteGroup: 刪除一個 PersonGroup
deletePerson: 刪除 PersonGroup 裡的一個 Person
listGroups: 列出所有的 PersonGroups
listPersons: 列出「人群」裡有哪些 Person
relay: 設定繼電器僅適用樹莓派,
status: 觀察 PersonGroup status
search: 搜尋一個personName,
traindatas: '訓練 /traindatas 裡的圖檔，同時訓練一群事先準備好的人與照片',
Config: 列出 Config.json 設定。
