def grasp_ball():
pygame.init()
settings = Settings()
screen = pygame.display.set_mode(
(settings.screen_width, settings.screen_height))
pygame.display.set_caption(settings.screen_caption)
stats = GameStats(settings)
people = People(settings, screen)
balls = Group()
gbf.create_ball(settings, screen, balls)
while True:
gbf.check_events(people)
if stats.game_active:
gbf.update_ball(settings, stats, screen, people, balls)
else:
balls.empty()
settings.people_image = './images/game_over.bmp'
people = People(settings, screen)
people.rect.centerx = screen.get_rect().centerx
people.rect.centery = screen.get_rect().centery
people.draw_people()
gbf.update_screen(settings, screen, people, balls)
def main(student_file, volunteer_file, output_file):
workbook = xlsxwriter.Workbook(
'/Users/Ingrid.Pacheco/Desktop/match-output.xlsx')
worksheet = workbook.add_worksheet()
headers = [
'nome MENTOR', 'email MENTOR', 'numero MENTOR', 'graduacao MENTOR',
'disciplinas MENTOR', 'idade MENTOR', 'estado MENTOR', 'nome ALUNO',
'email ALUNO', 'numero ALUNO', 'graduacao ALUNO', 'disciplinas ALUNO',
'idade ALUNO', 'estado ALUNO', 'dificuldades', 'interesse'
]
worksheet = add_headers(worksheet, headers)
matches = Match(worksheet, len(headers))
students = People()
mentors = People()
with pd.ExcelFile(student_file) as firstxls:
df1 = pd.read_excel(firstxls, 0)
f1 = File(student_file, df1.columns, df1.values.tolist(), df1)
f1.set_properties('student')
with pd.ExcelFile(volunteer_file) as secondxls:
df2 = pd.read_excel(secondxls, 0)
f2 = File(volunteer_file, df2.columns, df2.values.tolist(), df2)
f2.set_properties('mentor')
hours = df2.get(
'Quantas horas por semana você terá para dedicar para a mentoria (não esqueça de levar em consideração o tempo que você já dedica a outras atividades, e eventualmente outros projetos do ExplicaEnem que você é parte). Dessa maneira, de acordo com sua disponibilidade, poderemos te conectar com a quantidade de mentorados.'
).tolist()
for idx_mentor, val_mentor in enumerate(f2.get_values()):
vital_properties = f2.get_properties(idx_mentor, 'mentor')
mentor = Person(
f2.get_name(idx_mentor), f2.get_email(idx_mentor),
f2.get_phone(idx_mentor), vital_properties, val_mentor,
int(hours[idx_mentor].split('(')[1].split(' ')[0]))
mentors.add_person(mentor)
for idx_student, val_student in enumerate(f1.get_values()):
student_vital_properties = f1.get_properties(
idx_student, 'student')
student = Person(f1.get_name(idx_student),
f1.get_email(idx_student),
f1.get_phone(idx_student),
student_vital_properties, val_student, 0,
f1.get_additional_properties(idx_student))
students.add_person(student)
matches.get_match(student, mentor)
find_matches(matches, students, mentors)
workbook.close()
def rungame():
#初始化
pygame.init()
al_setting = Settings()
#创建窗口
screen = pygame.display.set_mode((al_setting.screen_width,
al_setting.screen_height))
pygame.display.set_caption("catch the ball")
stats = Stats(al_setting)
#创建角色
people = People(al_setting,screen)
#创建球组
balls = Group()
#创建角色组
peoples = Group()
peoples.add(people)
while True:
#鼠标键盘相应事件
gf.check_event(people)
if stats.game_active:
#更新角色位置
people.update()
#更新球的位置
gf.ball_update(al_setting,screen,balls,peoples,stats)
#刷新界面
gf.screen_update(al_setting,screen,balls,people)
def run_game():
pygame.init()
ai_settings = Settings()
screen = pygame.display.set_mode(
(ai_settings.screen_width, ai_settings.screen_height))
pygame.display.set_caption("Pick the stars")
people = People(ai_settings, screen)
stars = Stars(ai_settings, screen)
alien = Alien(ai_settings, screen)
bullets = Group()
stats = GameStats(ai_settings)
sb = Scoreboard(ai_settings, screen, stats)
play_button = Button(ai_settings, screen, "Play")
while True:
gf.check_events(ai_settings, stats, sb, people, alien, bullets,
play_button)
bullets.update()
for bullet in bullets.copy():
if bullet.rect.bottom >= ai_settings.screen_height:
bullets.remove(bullet)
if stats.game_active:
people.update()
gf.update_alien(alien)
gf.update_stars(ai_settings, stats, sb, people, stars)
if alien.rect.x % 120 == 0:
gf.update_bullet(ai_settings, stats, screen, people, alien,
bullets)
gf.update_screen(ai_settings, stats, sb, screen, people, stars, alien,
bullets, play_button)
def get_faces():
"""
This API searches an image for faces and returns the location of each face
---
tags:
- Image Analyzer
consumes:
- multipart/form-data
produces:
-application/json
parameters:
- in: formData
name: upfile
type: file
required: true
description: Image file to analyse
responses:
500:
description: Error, something went wrong!
200:
description: Detection success!
"""
#logger=logging.getLogger(__name__)
#logger.info("Calling prediction data for /people")
response = None
model = People()
query_class = request.args.get('class')
iFile = request.files.getlist('upfile')[0]
img = load_image(iFile)
img = rotate_image(img, iFile)
img = limit_size_image(img)
response = model.get_tags_coords(img, query_class)
return jsonify(response)
def create_people():
"""
sample request body:{
"First":"Zhe",
"Last":"Chen",
"Age":"31",
"GithubAcct":"zchen1007",
"Date of 3rd Grade Graduation":"3/04/98"
}
not recommending using id as one of the key in the json
:return: json object response
"""
input = request.json
people = People(profile=input)
is_valid, msg = people.is_data_valid()
if not is_valid:
return jsonify({"err": msg}), 400
has_all_req, msg = people.contains_all_keys()
if not has_all_req:
return jsonify({"err": msg}), 400
con_cur = Database.get_connection()
if 'ID' in people.profile:
app.logger.warning(
"manually input ID has the risk of conflicting with existing, if conflicts records will be ignored"
)
people.insert_with_id(con_cur)
else:
people.insert_no_id(con_cur)
con_cur.commit()
con_cur.close()
return getPeople()
def __init__(self, slug, api_key):
super(NationBuilder, self).__init__()
self.people = People(slug, api_key)
self.tags = NBTags(slug, api_key)
self.lists = Lists(slug, api_key)
self.contacts = Contacts(slug, api_key)
def __init__(self, num, city, BROAD_RATE, PROTECTION_RATE, DEATH_RATE, EXPOSED_TIME, IMMUNED_TIME, \
HOSPITAL_RECEIVE_TIME, CURE_TIME, SAFETY_DIST, u, FLUCTUATION, can_exposed_infect, recovered_included):
# self.city = city
self.num = num
self.peoples = np.array([])
self.BROAD_RATE = BROAD_RATE
self.PROTECTION_RATE = PROTECTION_RATE
self.DEATH_RATE = DEATH_RATE
self.EXPOSED_TIME = EXPOSED_TIME
self.HOSPITAL_RECEIVE_TIME = HOSPITAL_RECEIVE_TIME
self.CURE_TIME = CURE_TIME
self.IMMUNED_TIME = IMMUNED_TIME
self.SAFETY_DIST = SAFETY_DIST
self.FLUCTUATION = FLUCTUATION
self.SCALE = 1000
self.u = np.exp(u)
self.can_exposed_infect = can_exposed_infect
self.recovered_included = recovered_included
self.Tg = []
self.Te = []
self.Ti = []
self.in_touch = 0
if can_exposed_infect == True:
self.can_infect_status = [1, 2]
else:
self.can_infect_status = [2]
for i in range(num):
x = self.SCALE * np.random.normal(0, 1) + city.centerX
y = self.SCALE * np.random.normal(0, 1) + city.centerY
self.peoples = np.append(self.peoples, People(x, y))
def __init__(self, size, n_p):
"""
:param size: int, size of the grid
:param n_p: (4,) numpy array, [# of ppl of each status]
"""
self.size = size
self.all_p = []
self.total_p = sum(
n_p) # sum of the n_p list, indicating total number of ppl
self.steps = 1000 # this is the total number of steps you simulate
for status, n in enumerate(n_p):
gc = 0 if status == 0 else n_p[status - 1]
cur_list = [
People(i + gc,
np.random.randint(self.size, size=2),
size,
age=0,
status=status) for i in range(n)
]
self.all_p.extend(cur_list)
self.to_pos_array()
self.stream = self.data_stream()
# Setup the figure and axes...
self.fig, self.ax = plt.subplots()
# Then setup FuncAnimation.
self.ani = anime.FuncAnimation(
self.fig,
self.update,
interval=200,
# interval it is the time between your snapshots in ms
init_func=self.setup_plot,
blit=True)
def getPeople(self):
self.category = 'people'
result_d = json.loads(
SwapiService.getSwapi(self.category, self.getId()))
self.people = People(result_d['name'], result_d['height'])
print("Name: {} Height: {}cm".format(self.people.name,
self.people.height))
def deal_data():
for index, row in df.iterrows():
new_person = People(row['age'], row['sex'], row['bmi'],
row['children'], row['smoker'], row['region'],
row['charges'])
new_person.change_sex()
new_person.change_smoker()
new_person.change_region()
list1.append(new_person)
for index, row in rf.iterrows():
new_person = People(row['age'], row['sex'], row['bmi'],
row['children'], row['smoker'], row['region'],
row['charges'])
new_person.change_sex()
new_person.change_smoker()
new_person.change_region()
list2.append(new_person)
def run():
"""main function
"""
file_data = None
filename = ""
validation_msgs = ValidationMessages()
tags = Tags()
peeps = People(validation_msgs)
fam = Families(peeps, validation_msgs)
peeps.set_families(fam)
if len(sys.argv) < 2:
sys.exit("Usage: " + sys.argv[0] + " path-to-gedom-file")
filename = sys.argv[1]
try:
file_data = open(filename)
except IOError:
sys.exit("ERROR: file " + sys.argv[1] + "was not found!")
for line in file_data:
try:
data = tags.processline(line)
if data["valid"] == "Y":
fam.process_line_data(data)
peeps.process_line_data(data)
except TagsError as err:
sys.exit("ERROR: ", err)
fam.validate()
peeps.validate()
if validation_msgs.get_messages():
print("Validation Messages")
validation_msgs.print_all()
print("")
print("Individuals")
peeps.print_all()
peeps.us29_print_deceased()
peeps.us31_print_single()
peeps.us35_print_recent_births()
peeps.us36_print_recent_deaths()
peeps.us_38_print_upcoming_birthdays()
print("")
print("Families")
fam.print_all()
fam.us30_print_married()
fam.us32_print_multiple_births()
fam.us33_print_orphans()
fam.us34_print_big_age_diff()
fam.us_39_print_upcoming_anniversaries()
print("")
def app():
laoLiu = People("老刘")
laoWan = People("老王")
laoLin = People("老林")
peopleList = [laoLiu, laoWan, laoLin]
nu = 1 # 记录回合数
"""随机获取一名要敌人"""
def get_enemy(gunerName):
while True:
enemy = random.choice(peopleList)
if enemy.name != gunerName:
return enemy
#每个人开一枪,看谁活到最后
while True:
print("=" * 10 + ("第%d回合" % nu) + "=" * 10)
if laoWan.blood > 0:
print("%s:" % laoWan.name)
enemy = get_enemy(laoWan.name)
if laoWan.shoot_enemy(enemy):
peopleList.remove(enemy)
if laoLiu.blood > 0:
print("%s:" % laoLiu.name)
enemy = get_enemy(laoLiu.name)
if laoLiu.shoot_enemy(enemy):
peopleList.remove(enemy)
if laoLin.blood > 0:
print("%s:" % laoLin.name)
enemy = get_enemy(laoLin.name)
if laoLin.shoot_enemy(enemy):
peopleList.remove(enemy)
if len(peopleList) == 1:
print("最终的赢家是:", peopleList[0].name)
break
nu += 1
def write_arch(name, age, weight, height):
last = 0
people = People(name, int(age), float(weight), float(height))
print(last_id())
last += int(last_id())
final_str = get_all()
final_str += f"{(last)+1} - {people.get_name()}#{people.get_age()}#{people.get_weight():.2f}#{people.get_height():.2f}\n"
with open(abs_file_path, 'w') as archive:
archive.write(final_str)
clear()
print("Pessoa adicionada com sucesso")
def test_get_all_people():
response = requests.get("https://swapi.co/api/people/")
next_is_available = True
while (next_is_available):
assert response.status_code == 200
response_json = response.json()
for response_person in response_json["results"]:
person = People()
person.set_fields(response_person)
person.assert_people()
if response_json["next"] is not None:
response = requests.get(response_json["next"])
else:
next_is_available = False
def load_main_file(filename, main_dic):
wb = openpyxl.load_workbook(filename)
sheet = wb.get_sheet_by_name(wb.sheetnames[0])
line_number = len(sheet["A"])
print "Filename: ", filename, "Lines: ", line_number
racker_name_list = []
contractor_name_list = []
for row in range(9, line_number + 1):
combi_name = sheet['A' + str(row)].value.encode(
'ascii', 'ignore').lower().strip()
status = sheet['C' + str(row)].value.encode('ascii',
'ignore').lower().strip()
company = sheet['J' + str(row)].value.encode('ascii',
'ignore').lower().strip()
time = sheet['D' + str(row)].value
active_status = sheet['K' + str(row)].value.encode(
'ascii', 'ignore').lower().strip()
if status != "completed":
status = "incompleted"
if company != "contractor":
company = "rackspace"
if time > datetime.datetime(2017, 1, 1) and active_status == "active":
if combi_name not in main_dic:
people = People(combi_name)
people.status = status
people.company = company
main_dic[combi_name] = people
#name duplicate
else:
if status == "completed":
main_dic[combi_name].status = status
last_name, first_name = combi_name.split(",")
last_name = last_name.strip()
first_name = first_name.strip()
if company == "rackspace" and (first_name,
last_name) not in racker_name_list:
racker_name_list.append((first_name, last_name))
if company != "rackspace" and (
first_name, last_name) not in contractor_name_list:
contractor_name_list.append((first_name, last_name))
print "Active registered in 2017: ", len(main_dic.keys())
def generate_people(age_max, no_of_people, filename):
"""Reads a list of names from a file then selects a random number of them configured
by no_of_people and assigns them ages up to age_max
"""
try:
people = []
with open(filename) as myfile:
for line in myfile:
person = Person(line.rstrip('\n'), randint(1, age_max))
people.append(person)
people = random.sample(people, no_of_people)
return People(people)
except (FileNotFoundError, ValueError):
raise
def __init__(self, num, city, BROAD_RATE, DEATH_RATE, SHADOW_TIME, \ HOSPITAL_RECEIVE_TIME, CURE_TIME, SAFETY_DIST, u, FLUCTUATION): # self.city = city self.peoples = np.array([]) self.BROAD_RATE = BROAD_RATE self.DEATH_RATE = DEATH_RATE self.SHADOW_TIME = SHADOW_TIME self.HOSPITAL_RECEIVE_TIME = HOSPITAL_RECEIVE_TIME self.CURE_TIME = CURE_TIME self.SAFETY_DIST = SAFETY_DIST self.FLUCTUATION = FLUCTUATION self.SCALE = 1000 self.u = u for i in range(num): x = self.SCALE*np.random.normal(0, 1) + city.centerX y = self.SCALE*np.random.normal(0, 1) + city.centerY self.peoples = np.append(self.peoples, People(x, y))
def test_get_person():
response = requests.get("https://swapi.co/api/people/1/")
expected_json = {
"name":
"Luke Skywalker",
"height":
"172",
"mass":
"77",
"hair_color":
"blond",
"skin_color":
"fair",
"eye_color":
"blue",
"birth_year":
"19BBY",
"gender":
"male",
"homeworld":
"https://swapi.co/api/planets/1/",
"films": [
"https://swapi.co/api/films/2/", "https://swapi.co/api/films/6/",
"https://swapi.co/api/films/3/", "https://swapi.co/api/films/1/",
"https://swapi.co/api/films/7/"
],
"species": ["https://swapi.co/api/species/1/"],
"vehicles": [
"https://swapi.co/api/vehicles/14/",
"https://swapi.co/api/vehicles/30/"
],
"starships": [
"https://swapi.co/api/starships/12/",
"https://swapi.co/api/starships/22/"
],
"created":
"2014-12-09T13:50:51.644000Z",
"edited":
"2014-12-20T21:17:56.891000Z",
"url":
"https://swapi.co/api/people/1/"
}
assert response.status_code == 200
person = People()
person.set_fields(response.json())
person.assert_json_equal(expected_json)
def initPeople(self, n):
global MAX_LIKE_LEVEL
#(self,id,egoMax,initMax,sex):
ncore = 10 # n/10
for i in range(0, n):
p = People(i, r.randint(0, self.egoMax),
r.randint(0, self.initMax), r.randint(0, 1))
p.initLike0(n)
if (len(self.people) > 0):
for j in range(0, min(ncore, len(self.people))):
lover = r.randint(0, len(self.people) - 1)
p.like[lover] = r.randint(
MAX_LIKE_LEVEL - MAX_LIKE_LEVEL / 20, MAX_LIKE_LEVEL)
self.people[
lover].nice = self.people[lover].nice + p.like[lover]
p.initUndefinedLike()
self.people.append(p)
def ini():
# create a bunch of particles
num_people = 40
vec_v = np.array([0, 0])
r = 0.25 # in meters
#random initial position and check overlap
overlap= False
p_list=[]
while len(p_list)<num_people:
P=People(np.random.rand(2) * 10, vec_v, r,np.random.rand(2),screen)
for p_j in p_list:
if p_j.overlap(P):
overlap= True
break
overlap= False
if overlap== False:
p_list.append(P)
return p_list
def run_game():
#初始化一个游戏并创建一个屏幕对象
pygame.init()
ai_settings=Settings()
screen=pygame.display.set_mode((ai_settings.screen_width,ai_settings.screen_height))
pygame.display.set_caption("Alien Invasion")
#创建一艘飞船
ship=Ship(screen)
people=People(screen)
#开始游戏的主循环
while True:
#监视屏幕和鼠标和键盘事件
gf.check_events(ship)
ship.update()
#更新屏幕上的图像，并切换到新图像
gf.update_screen(ai_settings,screen,ship,people)
def Cellular_Automata(Total_People):
UI = GUI()
# Total_People = 200
P = People(Total_People, myMap)
UI.Show_People(P.list)
Time_Start = time.time()
Eva_Number = 0
Time_Pass = 0
Time_Step = 1
while Eva_Number < Total_People:
Eva_Number = P.run()
UI.Update_People(P.list)
# time.sleep(random.uniform(0.015, 0.025))
UI.canvas.update()
UI.root.update()
Time_Pass += Time_Step
UI.label_time['text'] = "Time = " + "%.2f" % Time_Pass + "s"
UI.label_evac['text'] = "Evacution People: " + str(Eva_Number)
# print("%.2fs" % (Time_Pass) + " 已疏散人数:" +str(Eva_Number))
# Time_Pass = time.time()-Time_Start
UI.label_time['text'] = "Time = " + "%.2f" % Time_Pass + "s"
UI.label_evac['text'] = "Evacution People: " + str(Eva_Number)
# 热力图
sns.heatmap(P.thmap.T, cmap='Reds')
# for i in range(0, 100):
# for j in range(0, 60):
# if P.thmap[i][j] != 0:
# print(P.thmap[i][j])
plt.axis('equal')
plt.show()
UI.root.mainloop()
def check_map(self):
# 用于把门周围的地面变成人们更趋近的区域
res = np.where(self.map == Block.GATE.value)
gates = list(zip(res[0], res[1])) # y, X
for gate in gates:
self.gate_log.add_gate(gate[0], gate[1])
man_in_gate = People(gate[1], gate[0], 0)
envs = self.get_env(GATE_AREA, man_in_gate)
envs[0][envs[0] == 0] = Block.EMPTY_NEAR_GATE.value
# 找到地图中的传送门
res = np.where(self.map == Block.GATE_MAN_OUT.value)
gates = list(zip(res[0], res[1])) # y, X
for gate in gates:
num = input(str(gate[0]) + " " + str(gate[1]) + ": ")
g_o = Gate_People_Out(gate[0], gate[1], int(num))
env = self.get_env(4, g_o)
g_o.set_env(env[0])
self.gate_man_out.append(g_o)
self.draw_map()
def gen_people(self, num):
self.total_man = num
res = np.where(self.map == Block.GATE.value)
gates = list(zip(res[0], res[1])) # y, X
# 随机放入游客在空白的地图中
while (num != 0):
x = random.randint(1, self.map.shape[1] - 1)
y = random.randint(1, self.map.shape[0] - 1)
if (self.map[y, x] == Block.EMPTY.value
or self.map[y, x] == Block.EMPTY_NEAR_GATE.value):
d = []
# 计算到门的距离
for gate in gates:
d.append(sqrt((gate[0] - y)**2 + (gate[1] - x)**2))
# 计算出最小值
self.mans.append(People(x, y, min(d)))
num = num - 1
self.map[y, x] = Block.MAN.value
# 应该按照距离排序
self.mans.sort(key=lambda x: x.distance_to_gate, reverse=False)
def get_face_id(repo):
"""
This API searches an image for faces and returns the person face grouop the name of a face group in the DB for a repo.
---
paths:
/people/{repo}
tags:
- Image Analyzer
consumes:
- multipart/form-data
produces:
-application/json
parameters:
- in: formData
name: upfile
type: file
required: true
description: Image file to analyse
- in: path
name: repo
schema:
type: integer
required: true
responses:
500:
description: Error, something went wrong!
200:
description: Detection success!
"""
#logger=logging.getLogger(__name__)
#logger.info("Calling prediction data for /faces")
response = None
model = People(repo)
query_class = request.args.get('class')
iFile = request.files.getlist('upfile')[0]
img = load_image(iFile)
img = rotate_image(img, iFile)
img = limit_size_image(img)
response = model.get_tags_face(img, query_class)
return jsonify(response)
def set_person_name(repo, personid, name):
"""
This API allows you to set the name of a person group in the DB for a repo
---
paths:
/people/{repo}/{personid}/{name}
tags:
- Image Analyzer
consumes:
- multipart/form-data
produces:
-application/json
parameters:
- in: path
name: repo
schema:
type: integer
required: true
- in: path
name: personid
schema:
type: integer
required: true
- in: path
name: name
schema:
type: string
required: true
responses:
500:
description: Error, something went wrong!
200:
description: Detection success!
"""
logger = logging.getLogger(__name__)
logger.info("Calling prediction data for /people/<repo>/<personid>/<name>")
model = People(repo)
query_class = request.args.get('class')
response = model.set_name(repo, personid, name)
return jsonify(response)
def convert(file_path_read, file_path_write):
gorbFile = open(file_path + file_path_read, 'r', encoding='utf-8')
resultFile = open(file_path + 'result.txt', 'r', encoding='utf-8')
gorbPlusResult = open(file_path + file_path_write, 'a+', encoding='utf-8')
resList = []
listOfResult = []
print('Start writting {}'.format(file_path_read))
next(resultFile) #пропускаю первую строку
for line in resultFile: #сплит резалта
resList = line.split() #загоняю резалт в лис
People(resList[0] + ' ' + resList[1] + ' ' + resList[2], resList[3],
resList[12])
gorbPlusResult.writelines(
'file;N;-2;-1;0;1;2;p-2;p-1;p0;p1;p2;TypeExperiment;Target;N_Type_Target;N_Type;Type_Target;N_Target;Hit;'
+ '\n')
next(gorbFile) #пропускаю первую строку
for line in gorbFile: #сплит горба
resList = line.split(';')
gorbList = re.search('[а-яА-ЯёЁ]+\s+[а-яА-ЯёЁ]+\s+[а-яА-ЯёЁ]+',
resList[0])
name = gorbList[0]
gorbList = re.search('[-+]?\d+', resList[0])
id = gorbList[0]
for obj in People.nameList:
if name == obj.getFIO() and id == obj.getNumOfExperiment():
gorbPlusResult.write(line.replace('\n', ''))
gorbPlusResult.write(obj.getResult() + '\n')
break
print('Writting completed {}'.format(file_path_write))
gorbFile.close()
resultFile.close()
gorbPlusResult.close()
def run(self):
import dlib
from people import People
from gender_recognizer_tf import GenderRecognizer
from face_recognizer import FaceRecognizer
self.gender_recognizer = GenderRecognizer()
self.p = People("./known_people")
self.face_recognizer = FaceRecognizer(
self.p.people
) #this is not ok , we should pass onlu self.p as object
self.predictor = dlib.shape_predictor(
"shape_predictor_68_face_landmarks.dat")
self.fa = FaceAligner(self.predictor, desiredFaceWidth=160)
self.state = IdleState()
while True:
label, data = self.recv()
if label == 'video_feed':
frame = data[0]
face = None
aligned_image, face, rect_nums, XY = self.face_extractor(frame)
if face is None:
continue
face_locations, face_names, percent = self.face_recognizer.recognize(
face)
in_the_frame = self.__update_state(self.p.people, percent)
if (self.state.__class__ == MatchState):
path, gender, age = self.gender_recognizer.recognize(
aligned_image, face, rect_nums, XY)
self.broadcast(["Match", face, in_the_frame, gender, age])
else:
path, gender, age = self.gender_recognizer.recognize(
aligned_image, face, rect_nums, XY)
if path is None:
continue
print("FaceFinder path = " + path)
self.broadcast(["NoMatch", path])
def search_archive(self):
root.filename = filedialog.askopenfilename(
initialdir="/",
title="Select file",
filetypes=(("csv files", "*.csv"), ("all files", "*.*")))
people_file = open(root.filename, 'r')
self.t_birth = Tree("birth")
self.t_name = Tree("name")
self.t_cpf = Tree("cpf")
b_date = []
for line in people_file:
columns = line.split(";")
b_date = columns[3].split("/")
columns[3] = b_date[2] + b_date[1] + b_date[0]
people = People(columns[0], columns[1], columns[2], columns[3],
columns[4])
self.t_birth.insert_node(people)
self.t_name.insert_node(people)
self.t_cpf.insert_node(people)