Dlib database face

picture

Box marker

import cv2 as cv
import dlib

#  open 
filename = 'C:/Users/to_bo/Desktop/1.jpg'
img = cv.imread(filename)

#  Return to the detector 
detector = dlib.get_frontal_face_detector()
#  Return to the face box 
faces = detector(img, 1)

#  Suppose multiple face frames are returned , Traverse in turn 
for i, d in enumerate(faces):
    #  Picture frame 
    cv.rectangle(
        img,
        tuple([d.left(), d.top()]),
        tuple([d.right(), d.bottom()]),
        (0, 255, 255),
        2
    )
#  Output 
cv.imshow('img', img)

#  end 
cv.waitKey(0)
cv.destroyAllWindows()

68 punctuation

import cv2 as cv
import dlib

#  open 
path = 'C:/Users/to_bo/Desktop/1.jpg'
img = cv.imread(path)

#  Return to the detector 
detector = dlib.get_frontal_face_detector()
#  Return to the face box 
faces = detector(img, 1)
#  Return to anchor keys 
predictor = dlib.shape_predictor(
    'C:/Users/to_bo/Desktop/1.dat'
)

#  Suppose multiple face frames are returned , Traverse in turn 
for face in faces:
    #  Locate the key points of the face in the frame 
    shape = predictor(img, face)
    #  Traverse all of （68） spot , Print out its coordinates , Tagged 
    for p in shape.parts():
        cv.circle(img, (p.x, p.y), 1, (255, 0, 0), -1)
    #  Output 
    cv.imshow("image", img)

#  end 
cv.waitKey(0)
cv.destroyAllWindows()

predictor = dlib.shape_predictor() Key predictor usage

detector = dlib.get_frontal_face_detector() Get the usage of face box

video

import cv2 as cv
import dlib

detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(
    'C:/Users/to_bo/Desktop/1.dat'
)

cap = cv.VideoCapture(0, cv.CAP_DSHOW)
if not cap.isOpened():
    print("Can not open camera")
    exit(0)
while True:
    ret, frame = cap.read()
    if not ret:
        print("Can not receive frame")
        break
    faces = detector(frame, 1)
    for face in faces:
        shape = predictor(frame, face)
        for p in shape.parts():
            cv.circle(frame, (p.x, p.y), 2, (0, 255, 0), -1)
    cv.imshow('img', frame)
    if cv.waitKey(1) & 0xFF == 27:
        break

cap.release()
cv.destroyAllWindows()

Add

detector.run() The identification of （ Not exactly ）

import cv2 as cv
import dlib

img = cv.imread('C:/Users/to_bo/Desktop/2.jpg')
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)

detector = dlib.get_frontal_face_detector()
# predictor = dlib.shape_predictor('C:/Users/to_bo/Desktop/1.dat')

faces = detector(gray, 1)

# for face in faces:
# points = predictor(gray, face)
# for p in points.parts():
# cv.circle(img, (p.x, p.y), 1, (0, 255, 0), -1)
# cv.namedWindow('img', cv.WINDOW_NORMAL)
# cv.imshow('img', img)
# cv.waitKey(0)
# cv.destroyWindow('img')

dets, scores, idx = detector.run(img, 1, -1)
for i, d in enumerate(dets):
    print("Detection {}, score: {}, face_type:{}".format(
        d, scores[i], idx[i]))
    if scores[i] > 0.8:
        cv.rectangle(img, (d.left(), d.top()), (d.right(), d.bottom()), (0, 255, 255), 2)
        cv.putText(
            img,
            str(scores[i]),
            (d.left(), d.bottom()),
            cv.FONT_HERSHEY_TRIPLEX,
            1,
            (0, 255, 0),
            2,
            cv.LINE_AA
        )
cv.namedWindow('img', cv.WINDOW_NORMAL)
cv.imshow('img', img)
cv.waitKey(0)
cv.destroyAllWindows()

from imutils import face_utils

import cv2 as cv
import dlib
from imutils import face_utils

img = cv.imread('./1.jpg')
gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)

detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor('1.dat')
faces = detector(gray, 1)

for face in faces:
    shapes = predictor(gray, face)

    points = face_utils.shape_to_np(shapes)
    img = face_utils.visualize_facial_landmarks(img, points)
    for point in points:
        cv.circle(img, (point[0], point[1]), 1, (255, 255, 255), -1)
cv.imshow('img', img)
cv.waitKey(0)
cv.destroyAllWindows()

# print(face_utils.FACIAL_LANDMARKS_IDXS)

import cv2 as cv
import dlib
from imutils import face_utils

cap = cv.VideoCapture(0, cv.CAP_DSHOW)
if not cap.isOpened():
    print('Can not open')
    exit(0)

detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor('1.dat')

while True:
    ret, frame = cap.read()
    if not ret:
        print('Can not get frame')
        break
    gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
    faces = detector(gray, 1)

    for face in faces:
        shapes = predictor(gray, face)

        points = face_utils.shape_to_np(shapes)
        frame = face_utils.visualize_facial_landmarks(frame, points)
        for point in points:
            cv.circle(frame, (point[0], point[1]), 1, (255, 255, 255), -1)
    cv.imshow('img', frame)
    if cv.waitKey(1) & 0xff == 27:
        break

cv.destroyAllWindows()