import trimesh import numpy as np import imageio import copy import cv2 import os from glob import glob import open3d from multiprocessing import Pool import json from utils import * if __name__ == '__main__' : H = 480 W = 720 intrinsics = np.array([[1000.,0.], [0., 1000.]]) cam_path = "traj_vis/Hemi12_transforms.json" location_path = "traj_vis/location_data_desert.json" video_name = "D_loc1_61_t3n13_003d_Hemi12_1.json" with open(location_path, 'r') as f: locations = json.load(f) locations_info = {locations[idx]['name']:locations[idx] for idx in range(len(locations))} location_name = video_name.split('_')[1] location_info = locations_info[location_name] translation = location_info['coordinates']['CameraTarget']['position'] vis_all = [] # vis cam with open(cam_path, 'r') as file: data = json.load(file) cam_poses = [] for i, key in enumerate(data.keys()): if "C_" in key: cam_poses.append(parse_matrix(data[key])) cam_poses = np.stack(cam_poses) cam_poses = np.transpose(cam_poses, (0,2,1)) cam_poses[:,:3,3] /= 100. relative_pose = np.linalg.inv(cam_poses[0]) cam_num = len(cam_poses) for idx in range(cam_num): cam_pose = cam_poses[idx] cam_pose = cam_pose[:, [1,2,0,3]] cam_pose = relative_pose @ cam_pose cam_points_vis = get_cam_points_vis(W, H, intrinsics, cam_pose, [0.4, 0.4, 0.4], frustum_length=1.) vis_all.append(cam_points_vis) # vis gt obj poses start_frame_ind = 10 sample_n_frames = 77 frame_indices = np.linspace(start_frame_ind, start_frame_ind + sample_n_frames - 1, sample_n_frames, dtype=int) with open('traj_vis/'+video_name, 'r') as file: data = json.load(file) obj_poses = [] for i, key in enumerate(data.keys()): obj_poses.append(parse_matrix(data[key][0]['matrix'])) obj_poses = np.stack(obj_poses) obj_poses = np.transpose(obj_poses, (0,2,1)) obj_poses[:,:3,3] -= translation obj_poses[:,:3,3] /= 100. obj_poses = obj_poses[:, :, [1,2,0,3]] obj_poses = relative_pose @ obj_poses obj_poses = obj_poses[frame_indices] obj_num = len(obj_poses) for idx in range(obj_num): obj_pose = obj_poses[idx] if idx % 5 == 0: cam_points_vis = get_cam_points_vis(W, H, intrinsics, obj_pose, [0.8, 0., 0.], frustum_length=0.5) vis_all.append(cam_points_vis) if len(data[key])>=2: with open('traj_vis/'+video_name, 'r') as file: data = json.load(file) obj_poses = [] for i, key in enumerate(data.keys()): obj_poses.append(parse_matrix(data[key][1]['matrix'])) obj_poses = np.stack(obj_poses) obj_poses = np.transpose(obj_poses, (0,2,1)) obj_poses[:,:3,3] -= translation obj_poses[:,:3,3] /= 100. obj_poses = obj_poses[:, :, [1,2,0,3]] obj_poses = relative_pose @ obj_poses obj_poses = obj_poses[frame_indices] obj_num = len(obj_poses) for idx in range(obj_num): obj_pose = obj_poses[idx] if (idx % 5 == 0) : cam_points_vis = get_cam_points_vis(W, H, intrinsics, obj_pose, [0., 0.8,0.], frustum_length=0.5) vis_all.append(cam_points_vis) if len(data[key])>=3: with open('traj_vis/'+video_name, 'r') as file: data = json.load(file) obj_poses = [] for i, key in enumerate(data.keys()): obj_poses.append(parse_matrix(data[key][2]['matrix'])) obj_poses = np.stack(obj_poses) obj_poses = np.transpose(obj_poses, (0,2,1)) obj_poses[:,:3,3] -= translation obj_poses[:,:3,3] /= 100. obj_poses = obj_poses[:, :, [1,2,0,3]] obj_poses = relative_pose @ obj_poses obj_poses = obj_poses[frame_indices] obj_num = len(obj_poses) for idx in range(obj_num): obj_pose = obj_poses[idx] if (idx % 5 == 0): cam_points_vis = get_cam_points_vis(W, H, intrinsics, obj_pose, [0., 0., 0.8], frustum_length=0.5) vis_all.append(cam_points_vis) # vis coordinates axis = open3d.geometry.TriangleMesh.create_coordinate_frame(size=2, origin=[0,0,0]) # vis_all.append(axis) open3d.visualization.draw_geometries(vis_all)