def rotate_phone(phone_pts, rotation_vector, camera_vector):
ext = camera_utils.create_extrinsic_matrix(rotation_vector, camera_vector)
new_pts = np.matmul(ext, phone_pts.T).T
new_pts = camera_utils.back_2_3d(new_pts)
obj_pts = camera_utils.print_obj_verts(new_pts)
#new_pts_list = new_pts.tolist()
#print obj_pts
#print new_pts_list
top_left = new_pts[0]
bottom_right = new_pts[2]
center_x = (top_left[0] + bottom_right[0]) / 2.
center_y = (top_left[1] + bottom_right[1]) / 2.
return obj_pts, new_pts, (center_x, center_y)
phone_pts = np.array([
[0.,0.,0., 1.],
[0,-0.1509,0., 1.],
[-0.0757 ,-0.1509 , 0., 1.],
[-0.0757, 0., 0., 1.]
])
phone_pts = np.array([
[ 0.0550 , -0.0017 , -0.0640,1],
[-0.0015 , -0.0518 , 0.0666,1],
[-0.0550 , 0.0017 , 0.0640,1],
[ 0.0015 , 0.0518 , -0.0666,1]
])
ext_matrix = camera_utils.create_extrinsic_matrix(
rotation_vector,
center_vector)
int_matrix = camera_utils.create_intrinsic_matrix(
fx, fy, width/2., height/2.)
camera_matrix = np.matmul(int_matrix, ext_matrix)
points_2d = np.matmul(camera_matrix, phone_pts.T).T
w_coords = points_2d[:,2]
points_2d = points_2d / w_coords[:,None]
phone_pts = np.asarray(phone_pts[:,:2], dtype = np.float32)
points_2d = np.asarray( points_2d[:,:2], dtype = np.float32)
phone_pts = np.asarray([
def project_points(rotated_pts, center_vector, height, width, fx, fy,
adversary_metadata, render_image_data, homography_im,
display):
reference_im = 'xr_.png'
capture_im = render_image_data
ones = np.ones(4)[np.newaxis].T
rotated_pts = np.hstack((rotated_pts, ones))
ext_matrix = camera_utils.create_extrinsic_matrix(np.array([0., 180., 0.]),
center_vector)
int_matrix = camera_utils.create_intrinsic_matrix(fx, fy, width / 2.,
height / 2.)
camera_matrix = np.matmul(int_matrix, ext_matrix)
points_2d = np.matmul(camera_matrix, rotated_pts.T).T
w_coords = points_2d[:, 2]
points_2d = points_2d / w_coords[:, None]
rotated_pts = np.asarray(rotated_pts[:, :2], dtype=np.float32)
points_2d = np.asarray(points_2d[:, :2], dtype=np.float32)
phone_pts = np.asarray([[0, 0], [0, 632], [312, 632], [312, 0]],
dtype=np.float32)
h, status = cv2.findHomography(points_2d, phone_pts)
#im_src = cv2.imread(capture_im)
#im_src = adjust_cv2_color(im_src)
im_src = render_image_data
im_dest = cv2.imread(reference_im)
im_dest = adjust_cv2_color(im_dest)
im_out = cv2.warpPerspective(im_src,
h, (im_dest.shape[1], im_dest.shape[0]),
flags=cv2.INTER_LINEAR)
im_out = np.fliplr(im_out)
#save image below
#need to write metadata here!!
#metadata = json.dumps(metadata)
#tifffile.imsave('microscope.tif', data, description=metadata)
#homography_im_tiff = homography_im.split('.')[0] + '.tif'
#tifffile.imsave(homography_im_tiff, im_out, description=adversary_metadata)
image_name = homography_im.split('/')[-1]
csv_filename = "/".join(
homography_im.split('/')[:len(homography_im.split('/')) -
1]) + '/metadata.csv'
homography_IM = Image.fromarray(im_out)
#homography_IM.show()
print(homography_im)
homography_IM.save(homography_im)
write_meta_to_csv(csv_filename, image_name, adversary_metadata)
if display:
display_images([reference_im, homography_im, capture_im], points_2d)