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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)
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