class Agender():
def __init__(self):
self.agender = PyAgender()
def detect(self, img_path):
# img_path = '/Users/woffee/www/language_design/couples-posing-800x450.jpg'
faces = self.agender.detect_genders_ages(cv2.imread(img_path))
return faces
def get_estimate_age(url):
try:
image = url_to_image(url)
except urllib.error.HTTPError:
return False
except urllib.error.URLError:
return False
except:
return False
agender = PyAgender()
faces = agender.detect_genders_ages(image)
if len(faces) > 0:
return round(faces[0]['age'])
else:
return 0
def gender_detect(path):
'''
gender_detect: takes in an image file, uses OpenCV and
PyAgender to detected the gender of the individual in the
live image
Parameters
----------
file: file name + location where file is stored
Returns
-------
Prediction string (i.e. "male")
'''
agender = PyAgender()
face = agender.detect_genders_ages(cv2.imread(path))
gender = face[0]['gender']
if gender >= 0.5:
return 'Female'
else:
return 'Male'
def detect(image):
agenda = PyAgender()
ans = agenda.detect_genders_ages(image)
return ans
def age_estimation(foto):
agender = PyAgender()
faces = agender.detect_genders_ages(cv2.imread(foto))
age = faces[0]['age']
return round(age)
# define store path
store_root_dir = r"D:\Datasets\Korean"
store_image_dir = os.path.join(store_root_dir, dataset_name + postfix)
if os.path.exists(store_image_dir) is False:
os.makedirs(store_image_dir)
if os.path.exists(os.path.join(root_data_dir,
dataset_name + '_F')) is False:
os.makedirs(os.path.join(root_data_dir, dataset_name + '_F'))
if os.path.exists(os.path.join(root_data_dir,
dataset_name + '_E')) is False:
os.makedirs(os.path.join(root_data_dir, dataset_name + '_E'))
for filename in tqdm(os.listdir(image_root_dir)):
filepath = os.path.join(image_root_dir, filename)
if os.path.isdir(filepath):
continue
width = -1
height = -1
with Image.open(filepath) as img:
width, height = img.size
agender = PyAgender()
# see available options in __init__() src
faces = agender.detect_genders_ages(cv2.imread(MY_IMAGE))
# print(width, ", ", height)
# if width <= 128 or height <= 128: #F
# shutil.move(filepath, os.path.join(os.path.join(root_data_dir, dataset_name + '_F'), filename))
# elif width <= 256 or height <= 256: #E
# shutil.move(filepath, os.path.join(os.path.join(root_data_dir, dataset_name + '_E'), filename))
"profile_image_url"].replace("_normal", "")
filename, file_extension = os.path.splitext(
tweet_in["user"]["profile_image_url"])
_my_img_path = path_img_data + tweet_in["user"][
"id_str"] + file_extension
if file_extension in ["", ".gif"]:
# The face predict tool doesn't work with some type of imgs.
face_predict = []
else:
# Predict age and gender
try:
urllib.request.urlretrieve(
tweet_in["user"]["profile_image_url"],
_my_img_path)
face_predict = agender.detect_genders_ages(
cv2.imread(_my_img_path))
except:
face_predict = []
#print(f"EXCEPT: {_my_img_path} {tweet_in['user']['profile_image_url']}")
for f in face_predict:
f["gender"] = float(round(f["gender"], 2))
f["age"] = float(round(f["age"], 2))
tweet["faces_predict"] = face_predict
else:
tweet["faces_predicted"] = "False"
tweet["faces_predict"] = []
#json.dump(tweet, outfile)
tweets.append(tweet)
json.dump(tweets, outfile)
#raw_data.append(tweet)
def img_clss():
new_file_id=uuid.uuid1()
try:
data_file = request.files['img']
file_name = data_file.name
data_file.save(f'{os.getcwd()}/images/{data_file.filename}')
data_file.close()
img_file = os.listdir(f'{os.getcwd()}/images/')
print('Image ',img_file[0])
agender = PyAgender()
path = os.path.join(f'{os.getcwd()}/images/', img_file[0])
print('Path ', path)
faces = agender.detect_genders_ages(cv2.imread(path))
print('Faces ',faces)
if faces[0]['gender'] < 0.5:
faces[0]['gender'] = 'male'
else:
faces[0]['gender'] = 'female'
faces[0]['age'] = str(faces[0]['age'] ).split('.')[0]
print(faces[0])
resp = make_response(faces[0])
resp.headers.set('Content-Type','multipart/form-data')
print('Response ', resp)
return resp
except Exception as e:
print(e)
try:
# Camera capture
path1 = f'{os.getcwd()}/images/'
image_string = str(request.form.get('file_string'))
image_newstring = image_string.replace("data:image/jpeg;base64,", "")
imgdata = base64.b64decode(image_newstring)
filename = os.path.join(path1 , new_file_id.hex+'.jpg')
with open(filename, 'wb') as f:
f.write(imgdata)
f.close()
img_file = os.listdir(f'{os.getcwd()}/images/')
print('Image ',img_file[0])
agender = PyAgender()
path = os.path.join(f'{os.getcwd()}/images/', img_file[0])
print('Path ',path)
faces = agender.detect_genders_ages(cv2.imread(path))
print('Faces ' ,faces)
if faces[0]['gender'] < 0.5:
faces[0]['gender'] = 'male'
else:
faces[0]['gender'] = 'female'
faces[0]['age'] = str(faces[0]['age'] ).split('.')[0]
print(faces[0])
resp = make_response(faces[0])
resp.headers.set('Content-Type','multipart/form-data')
target_dir=f'{os.getcwd()}/images/'
with os.scandir(target_dir) as entries:
for entry in entries:
time.sleep(1)
if entry.is_file() or entry.is_symlink():
os.remove(entry)
print('Response ', resp)
return resp
except Exception as e:
print(e)
print("Something went wrong with your image. Kindly try with different image")
finally:
target_dir=f'{os.getcwd()}/images/'
with os.scandir(target_dir) as entries:
for entry in entries:
time.sleep(1)
print(entry)
if entry.is_file() or entry.is_symlink():
os.remove(entry)
print("Image Deleted")
for img in list(row['urls']):
# Evade HTTP 404 Error
try:
req = urlopen(img)
arr = np.asarray(bytearray(req.read()), dtype=np.uint8)
image = cv2.imdecode(arr, -1)
if np.all(image == no_profile):
tcnt += 1
ncnt += 1
continue
face = agender.detect_genders_ages(image)
# Face Recognition Failed
if len(face) == 0:
continue
# Male
elif face[0]['gender'] <= 0.5:
mcnt += 1
tcnt += 1
# Female
elif face[0]['gender'] > 0.5:
are_matches = [closest_distances[0][i][0] <= distance_threshold for i in range(len(X_face_locations))]
# Predict classes and remove classifications that aren't within the threshold
return [(pred, loc) if rec else ("unknown", loc) for pred, loc, rec in zip(knn_clf.predict(faces_encodings), X_face_locations, are_matches)]
cap = cv2.VideoCapture(0)
cap.set(3, 640)
cap.set(4, 480)
nameold=[]
while 1:
ret,img = cap.read()
if ret:
faces = agender.detect_genders_ages(img)
for face in faces:
size=[face['width'],face['height'],face['top'],face['left']]
#print(faces)
gender=round(face['gender'])
age=face['age']
#print(gender)
if gender>0:
gender='female'
else:
gender='male'
full_file_path=(size[3],size[2]),(size[3]+size[1],size[2]+size[0])
predictions = predict(img,full_file_path, model_path="trained_knn_model.clf")
# Print results on the console
for name, (top, right, bottom, left) in predictions:
# -*- coding: utf-8 -*-
"""Untitled0.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1yA-cb7JozrTN3GaMLwhWENbCnqeB2YC_
"""
from fer import FER
import cv2
img = cv2.imread("/content/pic22.jpg")
detector = FER()
detector.detect_emotions(img)
emotion, score = detector.top_emotion(img)
score
emotion
from pyagender import PyAgender
agender = PyAgender()
faces = agender.detect_genders_ages(cv2.imread("/content/pic22.jpg"))
faces
path = find(i,x)
print(path)
if str(path) != "None":
z = find2('*.jpg', path)
#pictures = pictures + " " + '"' + str(z[0]) + '"'
#print(z)
pictures.append(str(z[0]))
print(pictures)
#facemorpher.morpher(pictures, plot=True)
facemorpher.averager(pictures, plot=True)
agender = PyAgender()
# see available options in __init__() src
faces = agender.detect_genders_ages(cv2.imread("/Users/ellen/Documents/Twente/Q2/Introduction to biometrics/Final/result.png"))
print(faces)
# In[3]:
# Vergelijk de gemiddelde leeftijd met de detected leeftijd van de morph van deze leeftijd groep
from pyagender import PyAgender
import cv2
import matplotlib.pyplot as plt
agender = PyAgender()
# see available options in __init__() src
faces_onder_10 = agender.detect_genders_ages(cv2.imread("Onder_10.png"))
agender = PyAgender()
for i in get_all_images(url):
response = urllib.request.Request(i, headers=headers)
try:
with urllib.request.urlopen(response) as url:
with open('temp.jpg', 'wb') as f:
f.write(url.read())
except:
print("Error: image not read")
pass
try:
faces = agender.detect_genders_ages(cv2.imread("temp.jpg"))
except:
b = get_all_images(i)
print("no face detected")
try:
for data in faces:
for key in data:
if (key == 'gender' or key == 'age'):
if key == 'gender':
gen = data[key]
if key == 'age':
age = data[key]
gnum.append(gen)
ages.append(age)
print("Male" if gen < 0.5 else "Female", '%.4s' % age, i)
def GetPhoto():
url = 'https://www.thispersondoesnotexist.com/image'
user_agent = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_3) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/35.0.1916.47 Safari/537.36'
request = urllib.request.Request(url, headers={'User-Agent': user_agent})
response = urllib.request.urlopen(request)
html = response.read()
f = open('img.jpg', 'wb')
f.write(html)
f.close()
GetPhoto()
agender = PyAgender()
faces = agender.detect_genders_ages(cv2.imread('img.jpg'))
age = int(faces[0]['age'])
print("age: ", age)
print("date of birth: " + str(int(str(datetime.now())[:4]) - age) + '.' +
str(random.randint(1, 12)) + '.' + str(random.randint(1, 31)))
if faces[0]['gender'] < 0.5:
print('gender: male')
gender = 'male'
elif faces[0]['gender'] > 0.5:
print('gender: female')
gender = 'female'
else:
print('gender: idk')
if random.randint(0, 1):
gender = 'male'
else:
capture = cv2.VideoCapture(0)
config = {
"apiKey": "AIzaSyDT8zvCg7Ax3h_IYtpwaawKe_80LmoN0aY",
"authDomain": "craeye-fa4f0.firebaseapp.com",
"databaseURL": "https://craeye-fa4f0.firebaseio.com",
"storageBucket": "craeye-fa4f0.appspot.com"
}
firebase = pyrebase.initialize_app(config)
fb_database = firebase.database()
while (True):
ret, frame = capture.read()
faces = agender.detect_genders_ages(frame)
age_values = []
gender_values = []
input_data = {}
if faces:
for int_index in range(0, len(faces)):
for value in faces[int_index]:
if value == "age":
if faces[int_index][value] <= 25:
age_values.append("Cat-01")
elif faces[int_index][value] <= 50:
age_values.append("Cat-02")
else:
age_values.append("Cat-03")
# -*- coding: utf-8 -*-
"""
Created on Tue Dec 1 11:36:51 2020
@author: murie
"""
#import os, fnmatch, facemorpher
from pyagender import PyAgender
import cv2
agender = PyAgender() # see available options in __init__() src
faces = agender.detect_genders_ages(
cv2.imread(
"C:/Users/murie/Documents/school/master/1B/Introduction2Biometrics/project_git/datasets/test"
))
image = agender.detect_genders_ages(cv2.imread("acaro.png"))
