Created
October 7, 2019 10:06
-
-
Save peterjpxie/2b0befb3b6696cf82fb891b871436380 to your computer and use it in GitHub Desktop.
find_facial_features_in_picture.py
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
from PIL import Image, ImageDraw | |
import face_recognition | |
image_file = 'obama.jpg' | |
# Load the jpg file into a numpy array | |
image = face_recognition.load_image_file(image_file) | |
# Find all facial features in all the faces in the image | |
face_landmarks_list = face_recognition.face_landmarks(image) | |
print("I found {} face(s) in this photograph.".format(len(face_landmarks_list))) | |
pil_image = Image.fromarray(image) | |
d = ImageDraw.Draw(pil_image) | |
for face_landmarks in face_landmarks_list: | |
# Print the location of each facial feature in this image | |
facial_features = [ | |
'chin', | |
'left_eyebrow', | |
'right_eyebrow', | |
'nose_bridge', | |
'nose_tip', | |
'left_eye', | |
'right_eye', | |
'top_lip', | |
'bottom_lip' | |
] | |
for facial_feature in facial_features: | |
print("The {} in this face has the following points: {}".format(facial_feature, face_landmarks[facial_feature])) | |
# Let's trace out each facial feature in the image with a line! | |
for facial_feature in facial_features: | |
d.line(face_landmarks[facial_feature], width=5) | |
# Display drawed image | |
pil_image.show() | |
# pil_image.save('test.png') |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment