114 lines
4.3 KiB
Python
114 lines
4.3 KiB
Python
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import cv2
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import numpy as np
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import dlib
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import math
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cap=cv2.VideoCapture(0)
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#cap=cv2.VideoCapture("debat.webm")
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detector=dlib.get_frontal_face_detector()
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predictor=dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")
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def tr(c, o, coeff):
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return(int((c-o)*coeff)+o)
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def cube(image, pt1, pt2, a1, a2, a3):
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color=(0, 255, 0)
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epaisseur=2
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offset=1.6
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offset2=2
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d_eyes=math.sqrt(math.pow(landmarks.part(36).x-landmarks.part(45).x, 2)+math.pow(landmarks.part(36).y-landmarks.part(45).y, 2))
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ox1=int((-(pt2.y-pt1.y)+pt2.x-pt1.x)/2)+pt1.x
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oy1=int(((pt2.x-pt1.x+pt2.y)-pt1.y)/2)+pt1.y
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cv2.line(image,
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(tr(pt1.x, ox1, offset), tr(pt1.y, oy1, offset)),
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(tr(pt2.x, ox1, offset), tr(pt2.y, oy1, offset)),
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color, epaisseur)
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cv2.line(image,
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(tr(pt2.x, ox1, offset), tr(pt2.y, oy1, offset)),
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(tr(-(pt2.y-pt1.y)+pt2.x, ox1, offset), tr(pt2.x-pt1.x+pt2.y, oy1, offset)),
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color, epaisseur)
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cv2.line(image,
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(tr(-(pt2.y-pt1.y)+pt2.x, ox1, offset), tr(pt2.x-pt1.x+pt2.y, oy1, offset)),
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(tr(-(pt2.y-pt1.y)+pt1.x, ox1, offset), tr(pt2.x-pt1.x+pt1.y, oy1, offset)),
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color, epaisseur)
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cv2.line(image,
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(tr(-(pt2.y-pt1.y)+pt1.x, ox1, offset), tr(pt2.x-pt1.x+pt1.y, oy1, offset)),
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(tr(pt1.x, ox1, offset), tr(pt1.y, oy1, offset)),
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color, epaisseur)
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ox2=int((-(pt2.y-pt1.y)+pt2.x-pt1.x)/2)+pt1.x+int(a2)
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oy2=int(((pt2.x-pt1.x+pt2.y)-pt1.y)/2)+pt1.y+int(a3)
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cv2.line(image,
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(tr(pt1.x+a2, ox2, offset2), tr(pt1.y+a3, oy2, offset2)),
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(tr(pt2.x+a2, ox2, offset2), tr(pt2.y+a3, oy2, offset2)),
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color, epaisseur)
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cv2.line(image,
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(tr(pt2.x+a2, ox2, offset2), tr(pt2.y+a3, oy2, offset2)),
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(tr(-(pt2.y-pt1.y)+pt2.x+a2, ox2, offset2), tr(pt2.x-pt1.x+pt2.y+a3, oy2, offset2)),
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color, epaisseur)
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cv2.line(image,
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(tr(-(pt2.y-pt1.y)+pt2.x+a2, ox2, offset2), tr(pt2.x-pt1.x+pt2.y+a3, oy2, offset2)),
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(tr(-(pt2.y-pt1.y)+pt1.x+a2, ox2, offset2), tr(pt2.x-pt1.x+pt1.y+a3, oy2, offset2)),
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color, epaisseur)
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cv2.line(image,
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(tr(-(pt2.y-pt1.y)+pt1.x+a2, ox2, offset2), tr(pt2.x-pt1.x+pt1.y+a3, oy2, offset2)),
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(tr(pt1.x+a2, ox2, offset2), tr(pt1.y+a3, oy2, offset2)),
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color, epaisseur)
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cv2.line(image,
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(tr(pt1.x, ox1, offset), tr(pt1.y, oy1, offset)),
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(tr(pt1.x+a2, ox2, offset2), tr(pt1.y+a3, oy2, offset2)),
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color, epaisseur)
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cv2.line(image,
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(tr(pt2.x, ox1, offset), tr(pt2.y, oy1, offset)),
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(tr(pt2.x+a2, ox2, offset2), tr(pt2.y+a3, oy2, offset2)),
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color, epaisseur)
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cv2.line(image,
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(tr(-(pt2.y-pt1.y)+pt2.x, ox1, offset), tr(pt2.x-pt1.x+pt2.y, oy1, offset)),
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(tr(-(pt2.y-pt1.y)+pt2.x+a2, ox2, offset2), tr(pt2.x-pt1.x+pt2.y+a3, oy2, offset2)),
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color, epaisseur)
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cv2.line(image,
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(tr(-(pt2.y-pt1.y)+pt1.x, ox1, offset), tr(pt2.x-pt1.x+pt1.y, oy1, offset)),
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(tr(-(pt2.y-pt1.y)+pt1.x+a2, ox2, offset2), tr(pt2.x-pt1.x+pt1.y+a3, oy2, offset2)),
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color, epaisseur)
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while True:
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ret, frame=cap.read()
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tickmark=cv2.getTickCount()
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gray=cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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faces=detector(gray)
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for face in faces:
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x1=face.left()
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y1=face.top()
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x2=face.right()
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y2=face.bottom()
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landmarks=predictor(gray, face)
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d_eyes=math.sqrt(math.pow(landmarks.part(36).x-landmarks.part(45).x, 2)+math.pow(landmarks.part(36).y-landmarks.part(45).y, 2))
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d1=math.sqrt(math.pow(landmarks.part(36).x-landmarks.part(30).x, 2)+math.pow(landmarks.part(36).y-landmarks.part(30).y, 2))
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d2=math.sqrt(math.pow(landmarks.part(45).x-landmarks.part(30).x, 2)+math.pow(landmarks.part(45).y-landmarks.part(30).y, 2))
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coeff=d1+d2
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a1=int(250*(landmarks.part(36).y-landmarks.part(45).y)/coeff)
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a2=int(250*(d1-d2)/coeff)
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cosb=min((math.pow(d2, 2)-math.pow(d1, 2)+math.pow(d_eyes, 2))/(2*d2*d_eyes), 1)
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a3=int(250*(d2*math.sin(math.acos(cosb))-coeff/4)/coeff)
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cube(frame, landmarks.part(36), landmarks.part(45), a1, a2, a3)
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cv2.imshow("Frame", frame)
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key=cv2.waitKey(1)&0xFF
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if key==ord('q'):
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break
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cap.release()
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cv2.destroyAllWindows()
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1
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