Beauty SDK technical principle, technical application, code analysis

With the popularity of social media, people pay more and more attention to their appearance. In order to meet users' needs for beauty, major technology companies have launched beauty SDK technology, allowing users to achieve beauty effects in photos and videos. This article will analyze the beauty SDK technology in detail.

1. The principle of the beauty SDK technology
The beauty SDK technology is a technology based on image processing, which realizes the beauty effect through image processing. The principle of beauty SDK technology mainly includes the following aspects:

1. Face detection
The beautification SDK technology first needs to detect the face in the image for subsequent beautification processing. Face detection usually uses deep learning algorithms that can accurately identify faces in images.

2. Face key point detection
Before the beautification process, it is necessary to detect the key points in the face, so as to facilitate the subsequent beautification process. Face key point detection can identify key points such as eyes, mouth, nose, etc., for subsequent beauty treatment.

3. Beauty treatment
The core of the beauty SDK technology is beauty treatment. Beauty treatments include skin whitening, dermabrasion, freckle removal, retouching and other treatment methods, and different treatments can be carried out according to the needs of users. Beautification processing usually uses an image processing algorithm, which can process the faces in the image to achieve a beautifying effect.

2. Application of Beauty SDK technology
The application of Beauty SDK technology is very extensive and can be applied to various photo and video applications. Beautification SDK technology can improve user experience, enabling users to achieve beautification effects in photos and videos. The application scenarios of the beauty SDK technology include:

1. Camera application
The beauty SDK technology can be applied to the camera application, so that users can achieve beauty effects when taking pictures. Users can choose different beauty treatment methods according to their own needs, so as to achieve different beauty effects.

2. Video applications
The beauty SDK technology can also be applied to video applications, allowing users to achieve beauty effects while recording videos. The beauty SDK technology can process the faces in the video to achieve the beauty effect.

3. Social applications
The beauty SDK technology can also be applied to social applications, enabling users to achieve beauty effects in social applications. Beauty SDK technology can improve the user experience, so that users can show their appearance more confidently.

3. Code Analysis of Beautification Technology

The following is a simple code example of beautification technology, which uses the OpenCV library and Dlib library to achieve simple beautification effects.

python
import cv2
import dlib

Load the face detector and keypoint detector

detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(“shape_predictor_68_face_landmarks.dat”)

load image

img = cv2.imread(“test.jpg”)

Perform face detection on an image

faces = detector(img)

Keypoint detection for each face

for face in faces:
shape = predictor(img, face)

# 对于每个关键点进行美颜处理
for i in range(1, 68):
    x, y = shape.part(i).x, shape.part(i).y
    
    # 磨皮
    img[y, x] = cv2.bilateralFilter(img[y, x], 15, 75, 75)
    
    # 皮肤美白
    img[y, x] = cv2.addWeighted(img[y, x], 1.5, img[y, x], -0.5, 0)
    
    # 祛斑
    img[y, x] = cv2.fastNlMeansDenoisingColored(img[y, x], None, 10, 10, 7, 21)
    
    # 眼袋去除
    if i in [37, 38, 40, 41, 43, 44, 46, 47]:
        img[y, x] = cv2.GaussianBlur(img[y, x], (5, 5), 0)

display image

cv2.imshow(“img”, img)
cv2.waitKey(0)
cv2.destroyAllWindows()
The above codes achieve simple beauty effects, including skin smoothing, skin whitening, freckle removal, and eye bag removal. Of course, the actual beauty SDK technology is much more complicated than the above code, and more factors need to be considered, including the processing effect under different light and the processing effect of different skin colors, etc.