face-detector 0.2.6

State-of-the-art face detection and landmarks localization

# Face Detector

Python package and Command Line Tool for state-of-the-art face detection and face
landmark points localization. It gathers the techniques implemented in dlib and
mtcnn, which can be easily switched between by setting a parameter in the
FaceDetector class instantiation (dlib\_5 is default if no technique is
specified, use dlib\_5 for dlib with 5 landmarks and dlib\_68 for dlib with 68
landmarks).

## How to Install:

pip install face-detector

## How to Use python package:

from face_detector import FaceDetector

img_addr = "path/to/image.[jpg/png/jpeg ...]"

# First parameter in FaceDetector constructor specifies face detection method (dlib: fl_5 or fl_68, mtcnn is default: mtcnn)
face_detector = FaceDetector()
faces = face_detector.get_faces(img_addr)

# Or to get the most prominent face in photo
main_face = face_detector.get_main_face(img_addr)

# Show image with bounding boxes and landmarks
import cv2
img = cv2.imread(img_addr)

for face in faces:
bb = face.bounding_box
landmarks = face.landmarks
cv2.rectangle(img, (int(bb.x), int(bb.y)), (int(bb.x + bb.w), int(bb.y+bb.h)), (0, 255, 0), 1)
for l in landmarks:
cv2.circle(img, (l.x, l.y), 2, (0,0,255))

cv2.imshow('img', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

## How to use Command Line Tool

```console
foo@bar:~$ facedetector /home/foo/images/Yasser_Arafat.jpg
```
The previous command will display the image passed in arguments with a bounding box wrapping every face in the image. Fig. 1 shows the image displayed.

<div align='left' style="display:inline-block; text-align:center; word-wrap: break-word;">
<img src='samples/Yasser_Arafat_2_faces.jpg' /> <p>Fig. 1 Face detections as outputted by facedetector command line tool</p>
</div>

<!--
<div align='left' style="margin-left:10px; display:inline-block; text-align:center; word-wrap: break-word;">
<img src='samples/Yasser_Arafat_main_face.jpg'/> <p>Fig. 3 Main face in photo, outputted by facedetector using -j option</p>
</div>
-->
<div align='left' style="margin-left:10px; display:inline-block; text-align:center; word-wrap: break-word;">
<img src='samples/Yasser_Arafat_landmarks.jpg'/> <p>Fig. 2 Face detections and landmarks as outputted by facedetector with -l (--landmarks) and -j (--only-main-face) options</p>
</div>


```console
foo@bar:~$ facedetector /home/foo/images/Yasser_Arafat.jpg -j -o /tmp/output.jpg -l
```
The previous command adds -j, -l and -o options, which capture the main
face in the photo, adds landmark points and output the image with bounding boxes to the
specified path, respectivelly. It also display the image in Fig. 2.


<!--
[//]: <> - From Github:
[//]: <> - Clone this repository
[//]: <> - Install dependencies in requirements.txt:
[//]: <> - pip install -r requirements.txt
[//]: <> - You might need to install zlib and link it to /usr/lib/x86_64-linux-gnu/libz.so:
[//]: <> ```console
[//]: <> foo@bar:~/face_detector$ tar xzvf data/zlib-1.2.9.tar.gz
[//]: <> foo@bar:~/face_detector$ cd data/zlib
[//]: <> foo@bar:~/face_detector/data/zlib$ sudo ./configure && make && make install
[//]: <> foo@bar:~/face_detector/data/zlib$ ln -s /lib/x86_64-linux-gnu/libz.so.1.2.8 /usr/lib/x86_64-linux-gnu/libz.so
[//]: <> ```
-->