170 lines
7.8 KiB
Python
170 lines
7.8 KiB
Python
#!/usr/bin/env python
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import cv2
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import dlib
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import numpy as np
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from PIL import Image, ImageDraw
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# Read Image
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c = cv2.VideoCapture(0)
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# im = cv2.imread("headPose.jpg");
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predictor_path = "shape_predictor_68_face_landmarks.dat"
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detector = dlib.get_frontal_face_detector()
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predictor = dlib.shape_predictor(predictor_path)
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while True:
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_, im = c.read()
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size = im.shape
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# Docs: Ask the detector to find the bounding boxes of each face. The 1 in the
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# second argument indicates that we should upsample the image 1 time. This
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# will make everything bigger and allow us to detect more faces.
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dets = detector(im, 1)
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print("Number of faces detected: {}".format(len(dets)))
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if len(dets) > 0:
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for d in dets:
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shape = predictor(im, d)
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print(shape.part(30).x, shape.part(54))
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#2D image points. If you change the image, you need to change vector
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image_points = np.array([
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(shape.part(30).x,shape.part(30).y), # Nose tip
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(shape.part(8).x,shape.part(8).y), # Chin
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(shape.part(36).x,shape.part(36).y), # Left eye left corner
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(shape.part(45).x,shape.part(45).y), # Right eye right corne
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(shape.part(48).x,shape.part(48).y), # Left Mouth corner
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(shape.part(54).x,shape.part(54).y) # Right mouth corner
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], dtype="double")
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# 3D model points.
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model_points = np.array([
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(0.0, 0.0, 0.0), # Nose tip
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(0.0, -330.0, -65.0), # Chin
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(-225.0, 170.0, -135.0), # Left eye left corner
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(225.0, 170.0, -135.0), # Right eye right corne
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(-150.0, -150.0, -125.0), # Left Mouth corner
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(150.0, -150.0, -125.0) # Right mouth corner
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])
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# Camera internals
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focal_length = size[1]
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center = (size[1]/2, size[0]/2)
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camera_matrix = np.array(
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[[focal_length, 0, center[0]],
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[0, focal_length, center[1]],
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[0, 0, 1]], dtype = "double"
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)
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# print ("Camera Matrix :\n {0}".format(camera_matrix))
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dist_coeffs = np.zeros((4,1)) # Assuming no lens distortion
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(success, rotation_vector, translation_vector) = cv2.solvePnP(model_points, image_points, camera_matrix, dist_coeffs, flags=cv2.SOLVEPNP_ITERATIVE)
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if not success:
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print("Error determening PnP", success)
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continue
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print ("Rotation Vector:\n {0}".format(rotation_vector))
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print ("Translation Vector:\n {0}".format(translation_vector))
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# Project a 3D point (0, 0, 1000.0) onto the image plane.
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# We use this to draw a line sticking out of the nose
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(nose_end_point2D, jacobian) = cv2.projectPoints(np.array([(0.0, 0.0, 1000.0)]), rotation_vector, translation_vector, camera_matrix, dist_coeffs)
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for p in image_points:
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cv2.circle(im, (int(p[0]), int(p[1])), 3, (0,0,255), -1)
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p1 = ( int(image_points[0][0]), int(image_points[0][1]))
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p2 = ( int(nose_end_point2D[0][0][0]), int(nose_end_point2D[0][0][1]))
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cv2.line(im, p1, p2, (255,0,0), 2)
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rotMatrix = np.zeros([3,3])
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cv2.Rodrigues(rotation_vector, rotMatrix, jacobian=0)
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# Find rotation: https://stackoverflow.com/a/15029416
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rx = np.arctan2(rotMatrix[2,1], rotMatrix[2,2])
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ry = np.arctan2(-rotMatrix[2,0], np.sqrt(np.square(rotMatrix[2,1]) + np.square(rotMatrix[2,2])))
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rz = np.arctan2(rotMatrix[1,0],rotMatrix[0,0])
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print("rotation", rx, ry, rz)
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ry = - np.arcsin(rotMatrix[0,2])
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rx = np.arctan2(rotMatrix[1,2]/np.cos(ry), rotMatrix[2,2]/np.cos(ry))
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rz = np.arctan2(rotMatrix[0,1]/np.cos(ry), rotMatrix[0,0]/np.cos(ry))
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print("rotation ml", rx, ry, rz) # seems better?
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# rotatedVector = np.dot(rotMatrix, translation_vector)
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# print("rvec", rotatedVector)
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# draw little floorplan for x: 10 -> 50 maps to z: 0 -> 10000, x: -2000 -> 2000
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mapPosX = int((translation_vector[0] + 500) / 1000 * 40)
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mapPosY = int((translation_vector[1] + 500) / 1000 * 40)
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mapPosZ = int((translation_vector[2] + 0 ) / 10000 * 40)
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cv2.circle(im, (mapPosZ + 10, mapPosX + 10), 2, (0,0,255), -1)
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cv2.circle(im, (mapPosZ + 60, mapPosY + 10), 2, (0,0,255), -1)
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# make it an _amazing_ stick figurine for the side view
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cv2.line(im, (mapPosZ + 60, mapPosY + 10), (mapPosZ + 60, mapPosY + 20), (0,0,255), 1)
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cv2.line(im, (mapPosZ + 60, mapPosY + 20), (mapPosZ + 55, mapPosY + 25), (0,0,255), 1)
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cv2.line(im, (mapPosZ + 60, mapPosY + 20), (mapPosZ + 65, mapPosY + 25), (0,0,255), 1)
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cv2.line(im, (mapPosZ + 60, mapPosY + 15), (mapPosZ + 55, mapPosY + 10), (0,0,255), 1)
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cv2.line(im, (mapPosZ + 60, mapPosY + 15), (mapPosZ + 65, mapPosY + 10), (0,0,255), 1)
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# draw rotation vector
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cv2.circle(im, (mapPosZ + 60, mapPosY + 10), 2, (0,0,255), -1)
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# cv2.line(im, (mapPosZ + 10, mapPosX + 10), (mapPosZ + 10 + int(rotation_vector[2]*5), mapPosX + 10 + int(rotation_vector[0]*5)), (255,255,0), 1)
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# cv2.line(im, (mapPosZ + 60, mapPosY + 10), (mapPosZ + 60 + int(rotation_vector[2]*5), mapPosY + 10 + int(rotation_vector[1]*200)), (255,255,0), 1)
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# print(rotMatrix)
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viewDirectionVector = np.dot(np.array([0.0, 0.0, 1000.0]), rotMatrix)
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cv2.line(im, (mapPosZ + 10, mapPosX + 10), (mapPosZ + 10 + int(viewDirectionVector[2] * 100), mapPosX + 10 + int(viewDirectionVector[0] * 100)), (255,255,0), 1)
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cv2.line(im, (mapPosZ + 60, mapPosY + 10), (mapPosZ + 60 + int(viewDirectionVector[2] * 100), mapPosY + 10 - int(viewDirectionVector[1] * 100)), (255,0,255), 1)
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# Translation vector gives position in space:
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# x, y z: 0,0,0 is center of camera
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# line: (x,y,z) = f(a) = (t1 + r1*a, t2+r2*a, t3 + r3*a)
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# Screen: (x,y,z) = (x,y,0)
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# Interesection:
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# x = t1 + r1 * a
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# y = t2 + r2 * a
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# z = t3 * r3 * a = 0
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# => a = -t3 / r3
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# substitute found a in x,y
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a = - translation_vector[2] / rotation_vector[2]
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x = translation_vector[0] + rotation_vector[0] * a
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y = translation_vector[1] + rotation_vector[1] * a
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a = - translation_vector[2] / viewDirectionVector[2]
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x = translation_vector[0] + viewDirectionVector[0] * a
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y = translation_vector[1] + viewDirectionVector[1] * a
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print (a, x, y)
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# draw little floorplan for 10 -> 50, sideplan 60 -> 100 (40x40 px)
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cv2.rectangle(im, (9, 9), (51, 51), (255,255,255), 1)
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cv2.rectangle(im, (59, 9), (101, 51), (255,255,255), 1)
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cv2.line(im, (10,10), (10,50), (200,200,200), 2)
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cv2.line(im, (60,10), (60,50), (200,200,200), 2)
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# Display image
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cv2.imshow("Output", im)
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keyPress = cv2.waitKey(5)
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if keyPress==27:
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break
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cv2.destroyAllWindows()
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