A collection of public facial landmark datasets and the Python code to make use of them.
Watch this 1 minute introduction video.
Name | Author | Published | #Marks | #Samples |
---|---|---|---|---|
300-W | Imperial College London | 2013 | 68 | 600 |
300-VW | Imperial College London | 2015 | 68 | 218597 |
AFW | Imperial College London | 2013 | 68 | 337 |
AFLW | Graz University of Technology | 2011 | 21 | |
AFLW2000-3D | Chinese Academy of Sciences | 2015 | 68 | 2000 |
HELEN | Imperial College London | 2013 | 68 | 2330 |
IBUG | Imperial College London | 2013 | 68 | 135 |
LFPW | Imperial College London | 2013 | 68 | 1035 |
WFLW | Tsinghua National Laboratory | 2018 | 98 | 10000 |
Face images and mark coordinates are required. Some dataset used existing images from other dataset, in which case the dataset was named after the image dataset.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
OpenCV 4.x
Just git clone this repo and you are good to go.
# From your favorite development directory
git clone https://github.com/yinguobing/facial-landmark-dataset
First, initialize the dataset. Take 300W as an example.
from fmd.ds300w import DS300W
# Set the path to the dataset directory.
DS300W_DIR = "/home/robin/data/facial-marks/300W"
# Construct a dataset.
ds = DS300W("300w")
# Populate the dataset with essential data
ds.populate_dataset(DS300W_DIR)
# See what we have got.
print(ds)
Possible output:
name: 300w
authors: Imperial College London
year: 2013
num_marks: 68
num_samples: 600
Once the dataset is constructed:
sample = ds.pick_one()
This could be useful when you are trying to transform or export the dataset.
for sample in ds:
# do whatever you want, like
print(sample.marks)
Read in the image file as a numpy array, and show the image.
image = sample.read_image()
import cv2
cv2.imshow("Preview", image)
cv2.waitKey()
facial_marks = sample.marks
The key marks are: left eye left corner, left eye right corner, right eye left corner, right eye right corner, mouse left corner, mouse right corner.
key_marks = sample.get_key_marks()
draw_marks(image, facial_marks)
Yin Guobing (尹国冰) - yinguobing
All the dataset authors who made their data public.