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MyCamera.py
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#!/usr/bin/env python
# encoding: utf-8
"""
Author(s): Matthew Loper
See LICENCE.txt for licensing and contact information.
"""
__all__ = ['ProjectPoints3D', 'ProjectPoints', 'RigidTransform']
import chumpy as ch
from chumpy import depends_on, Ch
from opendr.cvwrap import cv2
import numpy as np
import scipy.sparse as sp
from chumpy.utils import row, col
from opendr.geometry import Rodrigues
def RigidTransformSlow(**kwargs):
# Returns a Ch object with dterms 'v', 'rt', and 't'
result = Ch(lambda v, rt, t: v.dot(Rodrigues(rt=rt)) + t)
if len(kwargs) > 0:
result.set(**kwargs)
return result
class RigidTransform(Ch):
dterms = 'v', 'rt', 't'
def compute_r(self):
return (cv2.Rodrigues(self.rt.r)[0].dot(self.v.r.T) + col(self.t.r)).T.copy()
def compute_dr_wrt(self, wrt):
if wrt not in (self.v, self.rt, self.t):
return
if wrt is self.t:
if not hasattr(self, '_drt') or self._drt.shape[0] != self.v.r.size:
IS = np.arange(self.v.r.size)
JS = IS % 3
data = np.ones(len(IS))
self._drt = sp.csc_matrix((data, (IS, JS)))
return self._drt
if wrt is self.rt:
rot, rot_dr = cv2.Rodrigues(self.rt.r)
rot_dr = rot_dr.reshape((3, 3, 3))
dr = np.einsum('abc, zc -> zba', rot_dr, self.v.r).reshape((-1, 3))
return dr
if wrt is self.v:
rot = cv2.Rodrigues(self.rt.r)[0]
IS = np.repeat(np.arange(self.v.r.size), 3)
JS = np.repeat(np.arange(self.v.r.size).reshape((-1, 3)), 3, axis=0)
data = np.vstack([rot for i in range(self.v.r.size / 3)])
result = sp.csc_matrix((data.ravel(), (IS.ravel(), JS.ravel())))
return result
class ProjectPointsOrthogonal(Ch):
dterms = 'v', 'rt', 't', 'f', 'c', 'k'
def is_valid(self):
if any([len(v.r.shape) > 1 for v in [self.rt, self.t, self.f, self.c, self.k]]):
return False, 'rt, t, f, c, and k must be 1D'
if any([v.r.size != 3 for v in [self.rt, self.t]]):
return False, 'rt and t must have size=3'
if any([v.r.size != 2 for v in [self.f, self.c]]):
return False, 'f and c must have size=2'
return True, ''
def compute_r(self):
return self.r_and_derivatives[0].squeeze()
# return self.get_r_and_derivatives(self.v.r, self.rt.r, self.t.r, self.f.r, self.c.r, self.k.r)[0].squeeze()
def compute_dr_wrt(self, wrt):
if wrt not in [self.v, self.rt, self.t, self.f, self.c, self.k]:
return None
j = self.r_and_derivatives[1]
if wrt is self.rt:
return j[:, :3]
elif wrt is self.t:
return j[:, 3:6]
elif wrt is self.f:
return j[:, 6:8]
elif wrt is self.c:
return j[:, 8:10]
elif wrt is self.k:
return j[:, 10:10 + self.k.size]
elif wrt is self.v:
rot = cv2.Rodrigues(self.rt.r)[0]
data = np.asarray(j[:, 3:6].dot(rot), order='C').ravel()
IS = np.repeat(np.arange(self.v.r.size * 2 / 3), 3)
JS = np.asarray(np.repeat(np.arange(self.v.r.size).reshape((-1, 3)), 2, axis=0),
order='C').ravel()
result = sp.csc_matrix((data, (IS, JS)))
return result
# def unproject_points(self, uvd, camera_space=False):
# cam = ProjectPoints3D(**{k: getattr(self, k) for k in self.dterms if hasattr(self, k)})
#
# try:
# xy_undistorted_camspace = cv2.undistortPoints(
# np.asarray(uvd[:, :2].reshape((1, -1, 2)).copy()), np.asarray(cam.camera_mtx),
# cam.k.r)
# xyz_camera_space = np.hstack((xy_undistorted_camspace.squeeze(), col(uvd[:, 2])))
# xyz_camera_space[:, :2] *= col(xyz_camera_space[:, 2]) # scale x,y by z
# if camera_space:
# return xyz_camera_space
# other_answer = xyz_camera_space - row(cam.view_mtx[:, 3]) # translate
# result = other_answer.dot(cam.view_mtx[:, :3]) # rotate
# except: # slow way, probably not so good. But doesn't require cv2.undistortPoints.
# cam.v = np.ones_like(uvd)
# ch.minimize(cam - uvd, x0=[cam.v], method='dogleg', options={'disp': 0})
# result = cam.v.r
# return result
#
# def unproject_depth_image(self, depth_image, camera_space=False):
# us = np.arange(depth_image.size) % depth_image.shape[1]
# vs = np.arange(depth_image.size) // depth_image.shape[1]
# ds = depth_image.ravel()
# uvd = ch.array(np.vstack((us.ravel(), vs.ravel(), ds.ravel())).T)
# xyz = self.unproject_points(uvd, camera_space=camera_space)
# return xyz.reshape((depth_image.shape[0], depth_image.shape[1], -1))
@depends_on('f', 'c')
def camera_mtx(self):
return np.array(
[[self.f.r[0], 0, self.c.r[0]], [0., self.f.r[1], self.c.r[1]], [0., 0., 0.]],
dtype=np.float64)
@depends_on('t', 'rt')
def view_mtx(self):
R = cv2.Rodrigues(self.rt.r)[0]
return np.hstack((R, col(self.t.r))) # (3,4)
@depends_on('v', 'rt', 't', 'f', 'c', 'k')
def r_and_derivatives(self):
v = self.v.r.reshape((-1, 3)).copy()
v_proj = np.matmul(v, self.view_mtx[:3, :3].transpose()) + self.view_mtx[:3, 3] # (N,3), transform into Cam. coord.
v_proj = v_proj[:, :2] # (N,2), cuz. depth can be ignored under ortho. proj.
v_proj = v_proj * self.f.r[np.newaxis, :] + self.c.r[np.newaxis, :] # (N,2), ortho. proj.
J = np.zeros((self.v.r.shape[0], 10 + self.k.size)) # empty Jacobian. cuz we don't optimize anything here
return v_proj, J
# v = self.v.r.reshape((-1, 3)).copy()
# return cv2.projectPoints(v, self.rt.r, self.t.r, self.camera_mtx, self.k.r)
@property
def view_matrix(self):
R = cv2.Rodrigues(self.rt.r)[0]
return np.hstack((R, col(self.t.r)))
def project_points(self, points):
# sanity check
assert( (len(points.shape)==2) and (points.shape[1]==3) )
# orthographic projection
v_proj = np.matmul(points, self.view_mtx[:3, :3].transpose()) + self.view_mtx[:3, 3] # (N,3), transform into Cam. coord.
v_proj = v_proj[:, :2] # (N,2), cuz. depth can be ignored under ortho. proj.
v_proj = v_proj * self.f.r[np.newaxis, :] + self.c.r[np.newaxis, :] # (N,2), ortho. proj.
return v_proj
# class ProjectPoints3D(ProjectPoints):
# dterms = 'v', 'rt', 't', 'f', 'c', 'k'
#
# def compute_r(self):
# result = ProjectPoints.compute_r(self)
# return np.hstack((result, col(self.z_coords.r)))
#
# @property
# def z_coords(self):
# assert (self.v.r.shape[1] == 3)
# return RigidTransform(v=self.v, rt=self.rt, t=self.t)[:, 2]
#
# def compute_dr_wrt(self, wrt):
# result = ProjectPoints.compute_dr_wrt(self, wrt)
# if result is None:
# return None
#
# if sp.issparse(result):
# drz = self.z_coords.dr_wrt(wrt).tocoo()
# result = result.tocoo()
# result.row = result.row * 3 / 2
#
# IS = np.concatenate((result.row, drz.row * 3 + 2))
# JS = np.concatenate((result.col, drz.col))
# data = np.concatenate((result.data, drz.data))
#
# result = sp.csc_matrix((data, (IS, JS)), shape=(self.v.r.size, wrt.r.size))
# else:
# bigger = np.zeros((result.shape[0] / 2, 3, result.shape[1]))
# bigger[:, :2, :] = result.reshape((-1, 2, result.shape[-1]))
# drz = self.z_coords.dr_wrt(wrt)
# if drz is not None:
# if sp.issparse(drz):
# drz = drz.todense()
# bigger[:, 2, :] = drz.reshape(bigger[:, 2, :].shape)
#
# result = bigger.reshape((-1, bigger.shape[-1]))
#
# return result
#
#
# def main():
# import unittest
# from test_camera import TestCamera
# suite = unittest.TestLoader().loadTestsFromTestCase(TestCamera)
# unittest.TextTestRunner(verbosity=2).run(suite)
#
#
# if __name__ == '__main__':
# main()
#