Good day!My name is Andrey Sobolev and today we will create a simple “bun” for Django, which will check that the person’s face in the photo (which is useful in a bunch of situations).To do this, we need OpenCV and 5 minutes of free time. Go.Installation
First, install the necessary libraries in the docker container:FROM python:3.8.3-buster
RUN apt-get update && \
apt-get upgrade -y && \
apt-get install -y \
gcc && apt-get install -y \
libcurl4-gnutls-dev libexpat1-dev gettext libz-dev libssl-dev libjpeg-dev libfreetype6-dev python-dev libpq-dev python-dev libxml2-dev libxslt-dev postgresql-client git && \
apt-get install -y libxrender1 libxext-dev fontconfig && \
pip3 install -U pip setuptools
COPY ./requirements.txt /home/
* * *
And add the dependencies to requirements.txt:opencv-python
matplotlib
numpy
Face check function detect_face
Create the utils.py file (for example, in the main folder, you can have any other folder) and add the following lines there:import cv2 as cv
import numpy as np
def detect_face(in_memory_photo):
face_cascade = cv.CascadeClassifier(cv.__path__[0] + "/data/haarcascade_frontalface_default.xml")
in_memory_photo = in_memory_photo.read()
nparr = np.fromstring(in_memory_photo, np.uint8)
img = cv.imdecode(nparr, 4)
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
if len(faces) > 0:
return True
else:
return False
Integration into user input form
Import our function:from main.utils import detect_face
And “check the face” when registering a new user.if request.method == "POST":
form = RegistrationForm(request.POST, request.FILES)
if form.is_valid():
try:
in_memory_uploaded_file = request.FILES["photo"]
except:
in_memory_uploaded_file = None
if not in_memory_uploaded_file or not detect_face(in_memory_uploaded_file):
messages.add_message(request, messages.WARNING, _("You can only upload a face photo. Please try to uploading a different photo."))
return HttpResponseRedirect(reverse("main:profile_registration"))
An example without a framework
import os
import cv2 as cv
import numpy as np
def detect_face(in_memory_photo):
face_cascade = cv.CascadeClassifier(cv.__path__[0] + "/data/haarcascade_frontalface_default.xml")
in_memory_photo = in_memory_photo.read()
nparr = np.fromstring(in_memory_photo, np.uint8)
img = cv.imdecode(nparr, 4)
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
if len(faces) > 0:
return True
else:
return False
with open(os.path.dirname(os.path.abspath(__file__)) + '/photo.jpg', 'rb') as in_memory_photo:
is_it_face = detect_face(in_memory_photo)
print(is_it_face)
That's all.As you can see, everything is quite simple (if you need a simple check of course).useful links
towardsdatascience.com/face-detection-in-2-minutes-using-opencv-python-90f89d7c0f81new-friend.org/ru/195/2800/12918/profile-registration (an example of how this solution works).