mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
71 lines
3.0 KiB
71 lines
3.0 KiB
# This file is part of OpenCV project. |
|
# It is subject to the license terms in the LICENSE file found in the top-level directory |
|
# of this distribution and at http://opencv.org/license.html. |
|
|
|
import numpy as np |
|
import math |
|
import cv2 as cv |
|
import json |
|
|
|
class RandGen: |
|
def __init__(self, seed = 0): |
|
self.rand_gen = np.random.RandomState(seed) |
|
|
|
def randRange(self, min_v, max_v): |
|
return self.rand_gen.rand(1).item() * (max_v - min_v) + min_v |
|
|
|
def project(K, R, t, dist, pts_3d, is_fisheye): |
|
if is_fisheye: |
|
pts_2d = cv.fisheye.projectPoints(pts_3d.T[None,:], cv.Rodrigues(R)[0], t, K, dist.flatten())[0].reshape(-1,2).T |
|
else: |
|
pts_2d = cv.projectPoints(pts_3d, R, t, K, dist)[0].reshape(-1,2).T |
|
return pts_2d |
|
|
|
def projectCamera(camera, pts_3d): |
|
return project(camera.K, camera.R, camera.t, camera.distortion, pts_3d, camera.is_fisheye) |
|
|
|
def eul2rot(theta): # [x y z] |
|
# https://learnopencv.com/rotation-matrix-to-euler-angles/ |
|
R_x = np.array([[1, 0, 0 ], |
|
[0, math.cos(theta[0]), -math.sin(theta[0]) ], |
|
[0, math.sin(theta[0]), math.cos(theta[0]) ]]) |
|
R_y = np.array([[math.cos(theta[1]), 0, math.sin(theta[1]) ], |
|
[0, 1, 0 ], |
|
[-math.sin(theta[1]), 0, math.cos(theta[1]) ]]) |
|
R_z = np.array([[math.cos(theta[2]), -math.sin(theta[2]), 0], |
|
[math.sin(theta[2]), math.cos(theta[2]), 0], |
|
[0, 0, 1]]) |
|
return np.dot(R_z, np.dot(R_y, R_x)) |
|
|
|
def insideImageMask(pts, w, h): |
|
return np.logical_and(np.logical_and(pts[0] < w, pts[1] < h), np.logical_and(pts[0] > 0, pts[1] > 0)) |
|
|
|
def insideImage(pts, w, h): |
|
return insideImageMask(pts, w, h).sum() |
|
|
|
def areAllInsideImage(pts, w, h): |
|
return insideImageMask(pts, w, h).all() |
|
|
|
def writeMatrix(file, M): |
|
for i in range(M.shape[0]): |
|
for j in range(M.shape[1]): |
|
file.write(str(M[i,j]) + ('\n' if j == M.shape[1]-1 else ' ')) |
|
|
|
def saveKDRT(cameras, fname): |
|
file = open(fname, 'w') |
|
for cam in cameras: |
|
writeMatrix(file, cam.K) |
|
writeMatrix(file, cam.distortion) |
|
writeMatrix(file, cam.R) |
|
writeMatrix(file, cam.t) |
|
|
|
def export2JSON(pattern_points, image_points, image_sizes, is_fisheye, json_file): |
|
image_points = image_points.transpose(1,0,3,2) |
|
image_points_list = [[] for i in range(len(image_sizes))] |
|
for c in range(len(image_points)): |
|
for f in range(len(image_points[c])): |
|
if areAllInsideImage(image_points[c][f], image_sizes[c][0], image_sizes[c][1]): |
|
image_points_list[c].append(image_points[c][f].tolist()) |
|
else: |
|
image_points_list[c].append([]) |
|
json.dump({'object_points': pattern_points.tolist(), 'image_points': image_points_list, 'image_sizes': image_sizes, 'is_fisheye': is_fisheye}, open(json_file, 'w'))
|
|
|