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camera_calibration.py
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camera_calibration.py
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__author__ = 'Douglas and Iacopo'
import numpy as np
import cv2
import math
def estimate_camera(model3D, fidu_XY):
rmat, tvec = calib_camera(model3D, fidu_XY)
RT = np.hstack((rmat, tvec))
projection_matrix = model3D.out_A * RT
return projection_matrix, model3D.out_A, rmat, tvec
def calib_camera(model3D, fidu_XY):
#compute pose using refrence 3D points + query 2D point
## np.arange(68)+1 since matlab starts from 1
goodind = np.setdiff1d(np.arange(68)+1, model3D.indbad)
goodind=goodind-1
fidu_XY = fidu_XY[goodind,:]
ret, rvecs, tvec = cv2.solvePnP(model3D.model_TD, fidu_XY, model3D.out_A, None, None, None, False)
rmat, jacobian = cv2.Rodrigues(rvecs, None)
inside = calc_inside(model3D.out_A, rmat, tvec, model3D.size_U[1], model3D.size_U[0], model3D.model_TD)
if(inside == 0):
tvec = -tvec
t = np.pi
RRz180 = np.asmatrix([np.cos(t), -np.sin(t), 0, np.sin(t), np.cos(t), 0, 0, 0, 1]).reshape((3, 3))
rmat = RRz180*rmat
return rmat, tvec
def get_yaw(rmat):
modelview = rmat
modelview = np.zeros( (3,4 ))
modelview[0:3,0:3] = rmat.transpose()
modelview = modelview.reshape(12)
# Code converted from function: getEulerFromRot()
angle_y = -math.asin( modelview[2] ) # Calculate Y-axis angle
C = math.cos( angle_y)
angle_y = math.degrees(angle_y)
if np.absolute(C) > 0.005: # Gimball lock?
trX = modelview[10] / C # No, so get X-axis angle
trY = -modelview[6] / C
angle_x = math.degrees( math.atan2( trY, trX ) )
trX = modelview[0] / C # Get z-axis angle
trY = - modelview[1] / C
angle_z = math.degrees( math.atan2( trY, trX) )
else:
# Gimball lock has occured
angle_x = 0
trX = modelview[5]
trY = modelview[4]
angle_z = math.degrees( math.atan2( trY, trX) )
# Adjust to current mesh setting
angle_x = 180 - angle_x
angle_y = angle_y
angle_z = -angle_z
out_pitch = angle_x
out_yaw = angle_y
out_roll = angle_z
return out_yaw
def get_opengl_matrices(camera_matrix, rmat, tvec, width, height):
projection_matrix = np.asmatrix(np.zeros((4,4)))
near_plane = 0.0001
far_plane = 10000
fx = camera_matrix[0,0]
fy = camera_matrix[1,1]
px = camera_matrix[0,2]
py = camera_matrix[1,2]
projection_matrix[0, 0] = 2.0 * fx / width
projection_matrix[1, 1] = 2.0 * fy / height
projection_matrix[0, 2] = 2.0 * (px / width) - 1.0
projection_matrix[1, 2] = 2.0 * (py / height) - 1.0
projection_matrix[2, 2] = -(far_plane + near_plane) / (far_plane - near_plane)
projection_matrix[3, 2] = -1
projection_matrix[2, 3] = -2.0 * far_plane * near_plane / (far_plane - near_plane)
deg = 180
t = deg*np.pi/180.
RRz=np.asmatrix([np.cos(t), -np.sin(t), 0, np.sin(t), np.cos(t), 0, 0, 0, 1]).reshape((3, 3))
RRy=np.asmatrix([np.cos(t), 0, np.sin(t), 0, 1, 0, -np.sin(t), 0, np.cos(t)]).reshape((3, 3))
rmat=RRz*RRy*rmat
mv = np.asmatrix(np.zeros((4, 4)))
mv[0:3, 0:3] = rmat
mv[0, 3] = tvec[0]
mv[1, 3] = -tvec[1]
mv[2, 3] = -tvec[2]
mv[3, 3] = 1.
return mv, projection_matrix
def extract_frustum(camera_matrix, rmat, tvec, width, height):
mv, proj = get_opengl_matrices(camera_matrix, rmat, tvec, width, height)
clip = proj * mv
frustum = np.asmatrix(np.zeros((6 ,4)))
#/* Extract the numbers for the RIGHT plane */
frustum[0, :] = clip[3, :] - clip[0, :]
#/* Normalize the result */
v = frustum[0, :3]
t = np.sqrt(np.sum(np.multiply(v, v)))
frustum[0, :] = frustum[0, :]/t
#/* Extract the numbers for the LEFT plane */
frustum[1, :] = clip[3, :] + clip[0, :]
#/* Normalize the result */
v = frustum[1, :3]
t = np.sqrt(np.sum(np.multiply(v, v)))
frustum[1, :] = frustum[1, :]/t
#/* Extract the BOTTOM plane */
frustum[2, :] = clip[3, :] + clip[1, :]
#/* Normalize the result */
v = frustum[2, :3]
t = np.sqrt(np.sum(np.multiply(v, v)))
frustum[2, :] = frustum[2, :]/t
#/* Extract the TOP plane */
frustum[3, :] = clip[3, :] - clip[1, :]
#/* Normalize the result */
v = frustum[3, :3]
t = np.sqrt(np.sum(np.multiply(v, v)))
frustum[3, :] = frustum[3, :]/t
#/* Extract the FAR plane */
frustum[4, :] = clip[3, :] - clip[2, :]
#/* Normalize the result */
v = frustum[4, :3]
t = np.sqrt(np.sum(np.multiply(v, v)))
frustum[4, :] = frustum[4, :]/t
#/* Extract the NEAR plane */
frustum[5, :] = clip[3, :] + clip[2, :]
#/* Normalize the result */
v = frustum[5, :3]
t = np.sqrt(np.sum(np.multiply(v, v)))
frustum[5, :] = frustum[5, :]/t
return frustum
def calc_inside(camera_matrix, rmat, tvec, width, height, obj_points):
frustum = extract_frustum(camera_matrix, rmat, tvec, width, height)
inside = 0
for point in obj_points:
if(point_in_frustum(point[0], point[1], point[2], frustum) > 0):
inside += 1
return inside
def point_in_frustum(x, y, z, frustum):
for p in range(0, 3):
if(frustum[p, 0] * x + frustum[p, 1] * y + frustum[p, 2] + z + frustum[p, 3] <= 0):
return False
return True