def train_person_group(groupId):
# Train PersonGroup
face_api.trainPersonGroup(groupId)
# Get training status
res = face_api.getPersonGroupTrainingStatus(groupId)
res = res.replace('null','None')
res_dict = eval(res)
training_status = res_dict['status']
print training_status
while (training_status=='running'):
time.sleep(0.25)
res = face_api.getPersonGroupTrainingStatus(groupId)
res = res.replace('null','None')
res_dict = eval(res)
training_status = res_dict['status']
print training_status
return training_status
def train_person_group(groupId):
# Train PersonGroup
face_api.trainPersonGroup(groupId)
# Get training status
res = face_api.getPersonGroupTrainingStatus(groupId)
res = res.replace('null','None')
res_dict = eval(res)
training_status = res_dict['status']
print training_status
while (training_status=='running'):
time.sleep(0.25)
res = face_api.getPersonGroupTrainingStatus(groupId)
res = res.replace('null','None')
res_dict = eval(res)
training_status = res_dict['status']
print training_status
return training_status
def retake_validate_photos(clientId, personId, step_time, flag_show_photos, imgPath, name):
global global_vars
global_var = (item for item in global_vars if item["clientId"] == str(clientId)).next()
# Ask users if they want to change photo(s) or validate them
b = validate_photo(clientId)
image_to_paths = [root_path+imgPath+str(name)+"."+str(j)+suffix for j in range(nb_img_max)]
while (b==0):
global_var['text3'] = "Veuillez repondre"
simple_message(clientId, u"Veuillez répondre quelles photos que vous voulez changer ?")
while (global_var['respFromHTML'] == ""):
pass
nb = global_var['respFromHTML']
global_var['respFromHTML'] = ""
if ('-' in nb):
nb2 = ''
for i in range(int(nb[0]), int(nb[2])+1):
nb2 = nb2 + str(i)
nb = nb2
nb = str_replace_chars(nb, [',',';','.',' '], ['','','',''])
if (nb!=""):
str_nb = ""
for j in range(0, len(nb)):
if (j==len(nb)-1):
str_nb = str_nb + "'" + nb[j] + "'"
else:
str_nb = str_nb + "'" + nb[j] + "', "
simple_message(clientId, 'Vous souhaitez changer les photos: ' + str_nb + ' ?')
global_var['text'] = 'Re-prenant photos'
global_var['text2'] = 'Veuillez patienter... '
global_var['text3'] = ''
simple_message(clientId, global_var['text'] + ' ' + global_var['text2'])
time.sleep(0.25)
chrome_server2client(clientId, 'START')
for j in range(0, len(nb)):
global_var['text3'] = str(j) + ' ont ete prises, reste a prendre : ' + str(len(nb)-j)
time.sleep(step_time)
print "Reprendre photo ", nb[j]
#TODO: add a facedetect here to cut the face from image
image_path = image_to_paths[int(nb[j])-1]
os.remove(image_path) # Remove old image
with open(image_path, 'wb') as f:
f.write(global_var['binary_data'])
f.close()
print "Enregistrer photo " + image_path + ", nb de photos prises : " + nb[j]
chrome_server2client(clientId, 'DONE')
time.sleep(0.25)
a = yes_or_no(clientId, u'Reprise de photos finie, souhaitez-vous réviser vos photos ?', 4)
if (a==1):
thread_show_photos2 = Thread(target = show_photos, args = (clientId, imgPath, name), name = 'thread_show_photos2_'+clientId)
thread_show_photos2.start()
b = validate_photo(clientId)
global_var['text'] = ''
global_var['text2'] = ''
global_var['text3'] = ''
if (b==1):
break
# End of While(b==0)
print "Adding faces to person group..."
image_to_paths = [root_path+imgPath+str(name)+"."+str(j)+suffix for j in range(nb_img_max)]
for image_path in image_to_paths:
face_api.addPersonFace(groupId, personId, None, image_path, None)
# Retrain Person Group
resultTrainPersonGroup = face_api.trainPersonGroup(groupId)
print "Re-train Person Group: ", resultTrainPersonGroup
global_var['flag_enable_recog'] = 1 # Re-enable recognition
global_var['flag_ask'] = 1 # Reset asking
def retake_validate_photos(clientId, personId, step_time, flag_show_photos, imgPath, name):
global global_vars
global_var = (item for item in global_vars if item["clientId"] == str(clientId)).next()
# Ask users if they want to change photo(s) or validate them
b = validate_photo(clientId)
image_to_paths = [root_path+imgPath+str(name)+"."+str(j)+suffix for j in range(nb_img_max)]
while (b==0):
global_var['text3'] = "Veuillez repondre"
simple_message(clientId, u"Veuillez répondre quelles photos que vous voulez changer ?")
while (global_var['respFromHTML'] == ""):
pass
nb = global_var['respFromHTML']
global_var['respFromHTML'] = ""
if ('-' in nb):
nb2 = ''
for i in range(int(nb[0]), int(nb[2])+1):
nb2 = nb2 + str(i)
nb = nb2
elif (nb=='*' or nb=='all'):
nb=''
for j in range(0, nb_img_max):
nb = nb+str(j+1)
elif any(nb[idx] in a for idx in range(0, len(nb))): # If there is any number in string
nb2 = ''
for j in range(0, len(nb)):
if (nb[j] in a):
nb2 = nb2 + nb[j]
nb = nb2
else:
print 'Fatal error: invalid response'
nb = ''
nb = str_replace_chars(nb, [',',';','.',' '], ['','','',''])
if (nb!=""):
str_nb = ""
for j in range(0, len(nb)):
if (j==len(nb)-1):
str_nb = str_nb + "'" + nb[j] + "'"
else:
str_nb = str_nb + "'" + nb[j] + "', "
simple_message(clientId, 'Vous souhaitez changer les photos: ' + str_nb + ' ?')
global_var['text'] = 'Re-prenant photos'
global_var['text2'] = 'Veuillez patienter... '
global_var['text3'] = ''
simple_message(clientId, global_var['text'] + ' ' + global_var['text2'])
time.sleep(0.25)
chrome_server2client(clientId, 'START')
for j in range(0, len(nb)):
global_var['text3'] = str(j) + ' ont ete prises, reste a prendre : ' + str(len(nb)-j)
time.sleep(step_time)
print "Reprendre photo ", nb[j]
#TODO: add a facedetect here to cut the face from image
image_path = image_to_paths[int(nb[j])-1]
# os.remove(image_path) # Remove old image
delete_image_on_github(image_path)
# with open(image_path, 'wb') as f:
# f.write(global_var['binary_data'])
# f.close()
put_image_to_github(image_path, global_var['binary_data'])
print "Enregistrer photo " + image_path + ", nb de photos prises : " + nb[j]
chrome_server2client(clientId, 'DONE')
time.sleep(0.25)
a = yes_or_no(clientId, u'Reprise de photos finie, souhaitez-vous réviser vos photos ?', 4)
if (a==1):
thread_show_photos2 = Thread(target = show_photos, args = (clientId, imgPath, name), name = 'thread_show_photos2_'+clientId)
thread_show_photos2.start()
b = validate_photo(clientId)
global_var['text'] = ''
global_var['text2'] = ''
global_var['text3'] = ''
if (b==1):
break
# End of While(b==0)
print "Adding faces to person group..."
image_to_paths = [root_path+imgPath+str(name)+"."+str(j)+suffix for j in range(nb_img_max)]
for image_path in image_to_paths:
image_data = get_image_from_github(image_path)
face_api.addPersonFace(groupId, personId, None, None, image_data)
# Retrain Person Group
resultTrainPersonGroup = face_api.trainPersonGroup(groupId)
print "Re-train Person Group: ", resultTrainPersonGroup
global_var['flag_enable_recog'] = 1 # Re-enable recognition
global_var['flag_ask'] = 1 # Reset asking
if nom not in list_nom:
# Create a Person in a PersonGroup
personName = nom
personId = face_api.createPerson(groupId, personName, "")
list_nom.append(nom)
list_personId.append(personId)
nbr += 1
else:
personId = list_personId[nbr-1]
print "Add image...", nom, '\t', image_path
face_api.addPersonFace(groupId, personId, "", image_path, None)
time.sleep(0.25)
resultTrainPersonGroup = face_api.trainPersonGroup(groupId)
res = face_api.getPersonGroupTrainingStatus(groupId)
res = res.replace('null','None')
res_dict = eval(res)
training_status = res_dict['status']
print training_status
while (training_status=='running'):
time.sleep(0.25)
res = face_api.getPersonGroupTrainingStatus(groupId)
res = res.replace('null','None')
res_dict = eval(res)
training_status = res_dict['status']
print training_status