if os.path.exists(imgpaths[0]) and os.path.exists(imgpaths[1]):
fm.morpher(imgpaths,
alpha=False,
width=w,
height=h,
num_frames=nframes,
fps=10,
out_frames=outfr,
out_video=outvid)
else:
print('missing %s/%s' % (imgpaths[0], imgpaths[1]))
# Creating an average face
for em in emotions:
imgpaths = glob(os.path.join(imdir, 'stim', '*f_' + em + '_c.png'))
fm.averager(imgpaths,
alpha=True,
blur_edges=True,
out_filename='female_' + em + '_c.png')
import numpy as np
from matplotlib import pyplot as plt
from PIL import Image
import scipy
impath = imgpaths[0]
img = scipy.ndimage.imread(impath)[..., :3]
points = fm.locator.face_points(impath)
plt.imshow(img)
plt.plot(points[:, 0], points[:, 1], '.')
import facemorpher import os # Get a list of image paths in a folder photo_path = os.environ['HACKERBRASILEIRO_PHOTO_PATH'] imgpaths = facemorpher.list_imgpaths(photo_path) # To average, supply an array of face images: result_path = os.environ['HACKERBRASILEIRO_FACEMORPHER_PATH'] + '/result.png' facemorpher.averager(imgpaths, out_filename=result_path)
def average(pictures):
facemorpher.averager(pictures, plot=True)
# grouped_images[idx].append(img)
# #print(f"added to age group{idx}")
number_of_people = [1, 2, 3, 5, 7, 10]
age_average = np.zeros((len(number_of_people), len(age_groups)))
for idx, age_group in zip(range(0, len(age_groups)), age_groups):
print(f"Starting age group {idx}")
result = []
for a in range(age_group[0], age_group[1]):
result.extend(functions.find2(f'{a}*.jpg', '../CACD2000'))
print(f"Added age {a}")
for n in number_of_people:
for i in range(0, 3):
out_filename = f"../averages/average{age_group[0]}_{age_group[1]}_N{n}({i}).png"
if not os.path.exists(out_filename):
facemorpher.averager(random.sample(result, n),
plot=True,
out_filename=out_filename)
age_average[n - 1, idx] = age_average[n - 1, idx] + int(
estimate_age.estimate_age(out_filename))
print(f"Estimated age for average face with {n} images.")
#print("Age: ", age_average)
age_average = age_average / 3 # Get mean age
plt.plot([10 * x + 5 for x in range(1, len(age_groups) + 1)], age_average.T)
plt.legend(number_of_people)
plt.xlabel('Actual age')
plt.ylabel('Detected age')
plt.show()
#pictures = ""
pictures = []
for i in onder_70:
print(i)
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
def upload_file():
# get mom_file and dad_file out of request.files
# create a new project in the database
# when saving the mom and dad files to server (somewhere in static folder),
# add the project id to the end of each file name.
# update the new project's database record to fill in the mom_url and dad_url attributes.
user = User.query.get(session['user_id'])
new_project = Project(user=user)
db.session.add(new_project)
db.session.commit()
project_id = str(new_project.project_id)
project_base_dir = os.path.join(app.config['UPLOAD_FOLDER'],
'project_' + project_id)
os.mkdir(project_base_dir)
mom_file = request.files['mom_file']
if mom_file.filename == '':
flash('No selected file')
return redirect('/new_project')
if mom_file and allowed_file(mom_file.filename):
filename = secure_filename(
mom_file.filename) #make sure file is secure
mom_file.save(os.path.join(project_base_dir,
filename)) #/uploads/name.jpeg
dad_file = request.files['dad_file']
if dad_file.filename == '':
flash('No selected file')
return redirect('/new_project')
if dad_file and allowed_file(dad_file.filename):
filename = secure_filename(
dad_file.filename) #make sure file is secure
dad_file.save(os.path.join(project_base_dir,
filename)) #/uploads/name.jpeg
new_project.mom_url = 'project_' + project_id + '/' + mom_file.filename
new_project.dad_url = 'project_' + project_id + '/' + dad_file.filename
mom = os.path.join(project_base_dir, mom_file.filename)
dad = os.path.join(project_base_dir, dad_file.filename)
facemorpher.averager(imgpaths=[mom, dad],
out_filename=os.path.join(project_base_dir,
'result.png'),
blur_edges=True,
alpha=True)
new_project.baby_url = os.path.join('project_' + project_id + '/',
'result.png')
db.session.commit()
avi_filename = os.path.join(project_base_dir, 'result.avi')
facemorpher.morpher([mom, dad], out_video=avi_filename)
#converts avi to mp4
ff = FFmpeg(inputs={avi_filename: None},
outputs={
os.path.join(project_base_dir, 'result.mp4'):
'-filter:v "setpts=3.0*PTS"'
})
ff.run()
new_project.baby_avi = avi_filename
new_project.baby_mp4 = os.path.join('project_' + project_id + '/',
'result.mp4')
db.session.commit()
return redirect("/results/" + project_id)
[
'../CACD2000/32_Oliver_Hudson_0003.jpg',
'../CACD2000/38_Mireille_Enos_0005.jpg',
'../CACD2000/36_Freddie_Prinze_Jr._0013.jpg'
],
[
'../CACD2000/42_Nikolaj_Coster-Waldau_0010.jpg',
'../CACD2000/47_Mare_Winningham_0015.jpg',
'../CACD2000/42_Paul_Rudd_0002.jpg'
],
[
'../CACD2000/53_Dylan_Baker_0001.jpg',
'../CACD2000/53_Fran_Drescher_0005.jpg',
'../CACD2000/57_David_Hasselhoff_0005.jpg'
],
[
'../CACD2000/61_Mark_Hamill_0001.jpg',
'../CACD2000/61_Mary_McDonnell_0007.jpg',
'../CACD2000/62_David_Patrick_Kelly_0001.jpg'
]]
age_average = np.zeros(len(age_groups))
for idx, age_group in zip(range(0, len(age_groups)), age_groups):
out_filename = f"../averages/average{age_group[0]}_{age_group[1]}_handpickedN2.png"
if not os.path.exists(out_filename):
facemorpher.averager(people[idx][0:3],
plot=True,
out_filename=out_filename)
age_average[idx] = age_average[idx] + int(
functions.age_estimation(out_filename))
import facemorpher
# Get a list of image paths in a folder
imgpaths = facemorpher.list_imgpaths('imagefolder')
# To morph, supply an array of face images:
facemorpher.morpher(imgpaths, plot=True)
# To average, supply an array of face images:
facemorpher.averager(['image1.png', 'image2.png'], plot=True)