| |
| import cv2 |
| import numpy as np |
| import argparse |
|
|
| def get_center_point(num_cams,cameras): |
| A = np.zeros((3 * num_cams, 3 + num_cams)) |
| b = np.zeros((3 * num_cams, 1)) |
| camera_centers=np.zeros((3,num_cams)) |
| for i in range(num_cams): |
| if 'cam_%d' % i in cameras: |
| P0 = cameras['cam_%d' % i][:3, :] |
| else: |
| P0 = cameras[i] |
| K = cv2.decomposeProjectionMatrix(P0)[0] |
| R = cv2.decomposeProjectionMatrix(P0)[1] |
| c = cv2.decomposeProjectionMatrix(P0)[2] |
| c = c / c[3] |
| camera_centers[:,i]=c[:3].flatten() |
|
|
| v=R[2,:] |
| A[3 * i:(3 * i + 3), :3] = np.eye(3) |
| A[3 * i:(3 * i + 3), 3 + i] = -v |
| b[3 * i:(3 * i + 3)] = c[:3] |
|
|
| return camera_centers |
|
|
| def normalize_cameras(original_cameras_filename,output_cameras_filename,num_of_cameras, scene_bounding_sphere=3.0): |
| cameras = np.load(original_cameras_filename) |
| if num_of_cameras==-1: |
| all_files=cameras.files |
| maximal_ind=0 |
| for field in all_files: |
| maximal_ind=np.maximum(maximal_ind,int(field.split('_')[-1])) |
| num_of_cameras=maximal_ind+1 |
|
|
| camera_centers = get_center_point(num_of_cameras, cameras) |
|
|
| center = np.array([0, 0, 0]) |
|
|
| max_radius = np.linalg.norm((center[:, np.newaxis] - camera_centers), axis=0).max() * 1.1 |
|
|
| normalization = np.eye(4).astype(np.float32) |
|
|
| normalization[0, 0] = max_radius / scene_bounding_sphere |
| normalization[1, 1] = max_radius / scene_bounding_sphere |
| normalization[2, 2] = max_radius / scene_bounding_sphere |
|
|
| cameras_new = {} |
| for i in range(num_of_cameras): |
| cameras_new['scale_mat_%d' % i] = normalization |
| cameras_new['world_mat_%d' % i] = cameras['cam_%d' % i].copy() |
|
|
| np.savez(output_cameras_filename, **cameras_new) |
|
|
|
|
| if __name__ == "__main__": |
| parser = argparse.ArgumentParser(description='Normalizing cameras') |
| parser.add_argument('--input_cameras_file', type=str, default="cameras.npz", |
| help='the input cameras file') |
| parser.add_argument('--output_cameras_file', type=str, default="cameras_normalize.npz", |
| help='the output cameras file') |
| parser.add_argument('--number_of_cams',type=int, default=-1, |
| help='Number of cameras, if -1 use all') |
|
|
| args = parser.parse_args() |
| normalize_cameras(args.input_cameras_file, args.output_cameras_file, args.number_of_cams) |
