Face Library is an open source package for accurate and real-time face detection and recognition

Last update: Nov 09, 2022

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Overview

Face Library

Face Library is an open source package for accurate and real-time face detection and recognition. The package is built over OpenCV and using famous models and algorithms for face detection and recognition tasks. Make face detection and recognition with only one line of code. The Library doesn't use heavy frameworks like TensorFlow, Keras and PyTorch so it makes it perfect for production.

Installation

pip install face-library

Usage

Importing

from face_lib import face_lib
FL = face_lib()

The model is built over OpenCV, so it expects cv2 input (i.e. BGR image), it will support PIL in the next version for RGB inputs. At the end there is a piece of code to make PIL image like cv2 image.

Face detection

import cv2

img = cv2.imread(path_to_image)
faces = FL.get_faces(img) #return list of RGB faces image

If you want to get faces locations (coordinates) instead of the faces from the image you can use

no_of_faces, faces_coors = FL.faces_locations(face_img)

Face verfication

img_to_verfiy = cv2.imread(path_to_image_to_verify) #image that contain face you want verify
gt_img = cv2.imread(path_to_image_to_compare) #image of the face to compare with

face_exist, no_faces_detected = FL.recognition_pipeline(img_to_verfiy, gt_image)

You can change the threshold of verfication with the best for your usage or dataset like this :

face_exist, no_faces_detected = FL.recognition_pipeline(img_to_verfiy, gt_image, threshold = 1.1) #default number is 0.92

also if you know that gt_img has only one face and the image is zoomed to that face like this :

You can save computing time and the make the model more faster by using

face_exist, no_faces_detected = FL.recognition_pipeline(img_to_verfiy, gt_image, only_face_gt = True)

Extracting face embeddings

I you want represent the face with vector from face only image, you can use

face_embeddings = FL.face_embeddings(face_only_image)

For PIL images

import cv2
import numpy
from PIL import Image

PIL_img = Image.open(path_to_image)

cv2_img = cv2.cvtColor(numpy.array(PIL_img), cv2.COLOR_RGB2BGR) #now you can use this to be input for face_lib functions

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Support

There are many ways to support a project - starring ⭐️ the GitHub repo is just one.

Licence

Face library is licensed under the MIT License

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Comments

Face Recognition model corrupted

While running the script it says tat "face rcognition model corrupted" and starts to download the model. But it takes too long to download 90 mb file.
help wanted

opened by qnihat 4
import issue

This might be a noob python question, but:

git clone https://github.com/a-akram-98/face_lib.git cd face_lib/ virtualenv -p /usr/bin/python3 venv source venv/bin/activate pip install face-library ...

(venv) [email protected]:src (master)$ python Python 3.6.9 (default, Jan 26 2021, 15:33:00) [GCC 8.4.0] on linux Type "help", "copyright", "credits" or "license" for more information.

from face_lib import face_lib Traceback (most recent call last): File "", line 1, in File "/home/jim/source/face_lib/src/face_lib/init.py", line 1, in from .face_lib import face_lib File "/home/jim/source/face_lib/src/face_lib/face_lib.py", line 5, in from .BlazeDetector import BlazeFaceDetector File "/home/jim/source/face_lib/src/face_lib/BlazeDetector.py", line 5, in from blazeFaceUtils import gen_anchors, AnchorsOptions ModuleNotFoundError: No module named 'blazeFaceUtils'

How do I find the modules?
bug good first issue

opened by jvanvorst 2
Issue with size of the image

I saw that with big image 958x1280 it gave an opencv error! so 9i made a small function to resize it to 500 on the height:

`from face_lib import face_lib import cv2 import os FL = face_lib()

maxsize = int(500) #maximum height in pixel to get an opencv error file = "./sacha.jpg" filename, file_extension = os.path.splitext(os.path.basename(file))

def checksize(file): print("in") if not os.path.isfile(file): print("error file not found") exit(1) #get the filename and extensionof filepath img = cv2.imread(file) #Get the width and Heigth of filepath height, width, channels = img.shape #Get the correction factor if the image is to big if height > maxsize: factor = float(maxsize/height) print(factor) height = round(int(height) * factor) width = round(int(width) * factor) #Resize the image img = cv2.resize(img,(width, height)) return img

img = checksize(file) no_of_faces, faces_locations = FL.faces_locations(img) x,y,w,h = faces_locations[0] cv2.rectangle(img, (x,y),(x+w,y+h), (255,0,0),2) cv2.imshow(filename, img) cv2.waitKey(0)`

that can help anyone

opened by sachadee 0

Releases(v1.0.5)

v1.0.5(Oct 17, 2021)

This release hold the Face Recognition model
Source code(tar.gz)
Source code(zip)
graph_final.pb(89.67 MB)

Owner

GitHub Repository

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