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@Manojbhat09
Created April 29, 2020 19:29
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Convert Argoverse format to KITTI
# Converting the ply files into the bin files
import sys
sys.path.remove('/opt/ros/kinetic/lib/python2.7/dist-packages')
print("removed ros")
import pyntcloud
import numpy as np
import glob
import pdb
import os
import json
import matplotlib.pyplot as plt
import argoverse
import shutil
from tqdm import tqdm
from argoverse.data_loading.argoverse_tracking_loader import ArgoverseTrackingLoader
import argoverse.visualization.visualization_utils as viz_util
from scipy.spatial.transform import Rotation
'''
To get the internsity and ring information from argoverse data just attach this code to plyfile.py
inside the api folder
def convert_listed_path(file_path):
data = pyntcloud.PyntCloud.from_file(os.fspath(file_path))
x = np.array(data.points.x)[:, np.newaxis]
y = np.array(data.points.y)[:, np.newaxis]
z = np.array(data.points.z)[:, np.newaxis]
i = np.array(data.points.intensity)[:, np.newaxis]
ring = np.array(data.points.laser_number)[:, np.newaxis]
return np.concatenate((x, y, z, i, ring), axis=1)
if __name__ == "__main__":
pointcloud_paths = os.path.join("/home/droid/manoj_work/data/argoverse/scene1/lidar", "*")
pcd_list = glob.glob(pointcloud_paths)
save_folder = os.path.join("/home/droid/manoj_work/data/argoverse/", "argo_sample")
if(not os.path.exists(save_folder)): os.makedirs(save_folder)
for i, each in enumerate(pcd_list):
save_path = os.path.join(save_folder, "{0:010d}".format(i)+".bin")
pointcloud = convert_listed_path(each)
np.array(pointcloud).tofile(save_path)
print("Saved ", each)
'''
def get_objects_from_label(label_file):
# Opens a label file, and passes the object to Object3d object, Read the json GT labels
f = open(label_file)
label_data = json.load(f)
objects = [object3d.Object3d(data) for data in label_data]
return objects
def check_make_(save_dir, display=True):
if not os.path.exists(save_dir):
if display:
print("Making folder ", save_dir)
os.makedirs(save_dir)
else:
if display:
print("Folder present ", save_dir)
else:
pass
def dump(calib_file, calib):
with open(calib_file, 'w') as outfile:
json.dump(calib, outfile, ensure_ascii=False, indent=4)
def dump_img(file, img):
plt.imsave(file, img , format='png')
def dump_pcd(file, pcd):
pcd.tofile(file)
def cpy(source, destination):
shutil.copy(source, destination)
if __name__=="__main__":
'''
Data-format:
data/
kitti/
Argoverse/
val/
train/
log_id_1/
image_01/
velodyne_points/
data/
timestamps.txt/
log_id_2/
...
'''
cwd = os.getcwd()
base_root = "/home/droid/manoj_work"
root_dir = os.path.join(base_root, "data", "raw_Argoverse") + "/"
save_h5_root = os.path.join(base_root, "data", "Argoverse") + "/"
dataset = ['train', 'val', 'test']
folders = [os.path.join(root_dir, folder) for folder in ['train', 'val', 'test']]
choice = 0 #args.dataset_choice
folder_choice = folders[choice]
dataset_choice = dataset[choice]
root_dir_choice = os.path.join(root_dir, dataset_choice)
save_dir = os.path.join(save_h5_root, dataset_choice)
check_make_(save_dir)
split = folder_choice[len(os.path.dirname(folder_choice))+1:]
is_test = (split == 'test')
lidar_pathlist = []
label_pathlist = []
actual_idx_list = []
calib_objects= []
logidx_to_count_map= {}
log_to_count_map= {}
print("____________SPLIT IS : {} ______________".format(split))
if split == 'train' or split == 'val':
imageset_dir = os.path.join(root_dir,split)
splitname = lambda x: [x[len(imageset_dir+"/"):-4].split("/")[0], x[len(imageset_dir+"/"):-4].split("/")[2].split("_")[1]]
data_loader = ArgoverseTrackingLoader(os.path.join(root_dir,split))
camera = data_loader.CAMERA_LIST[0]
print("Chosen camera is : ", camera)
log_list = data_loader.log_list
path_count = 0
for log_id, log in enumerate(log_list):
log_folder = os.path.join(save_dir, "{0:010d}".format(log_id))
check_make_(log_folder)
pcd_folder = os.path.join(log_folder, "velodyne_points", "data")
check_make_(pcd_folder)
oxts_folder = os.path.join(log_folder, "oxts")
check_make_(oxts_folder)
img_folder = os.path.join(log_folder, "image_01", "data")
check_make_(img_folder)
img_box_folder = os.path.join(log_folder, "imagebox_01", "data")
check_make_(img_box_folder)
calib = data_loader.get_calibration(camera)
calib_src = os.path.join(root_dir_choice, log, "vehicle_calibration_info.json")
oxts_root_src = os.path.join(root_dir_choice, log, "poses")
cpy(calib_src, os.path.join(log_folder, "calib_{0:010d}".format(log_id)+".json"))
argoverse_data = data_loader.get(log)
lidar_lst = data_loader.get(log).lidar_list
lidar_pathlist.extend(lidar_lst)
label_pathlist.extend(data_loader.get(log).label_list)
assert len(lidar_pathlist) == len(label_pathlist)
for idx, each_path in enumerate(tqdm(lidar_lst)):
ide = log_id + idx
img = argoverse_data.get_image_sync(ide, camera = camera)
objects = argoverse_data.get_label_object(ide)
img_vis = viz_util.show_image_with_boxes(img, objects, calib)
lidar_pts = argoverse_data.get_lidar(ide)
img_file = os.path.join(img_folder, "{0:010d}".format(ide)+".json")
img_box_file = os.path.join(img_box_folder, "{0:010d}".format(ide)+".json")
objects_file = os.path.join(oxts_folder, "{0:010d}".format(ide)+".json")
dump_img(os.path.join(img_folder, "{0:010d}".format(ide)+".png"), img)
dump_img(os.path.join(img_box_folder, "{0:010d}".format(ide)+".png"), img_vis)
dump(os.path.join(oxts_folder, "{0:010d}".format(ide)+".json"), objects)
dump_pcd(os.path.join(pcd_folder, "{0:010d}".format(ide)+".bin"), lidar_pts)
actual_idx_list.extend([splitname(each) for each in lidar_lst])
idx_list = np.arange(path_count, path_count + len(lidar_lst))
logidx_to_count_map[log_id] = idx_list
log_to_count_map[log] = idx_list
path_count+=len(lidar_lst)
dump(os.path.join(save_dir, "logidx_to_count_map.json"), logidx_to_count_map)
dump(os.path.join(save_dir, "log_to_count_map.json"), log_to_count_map)
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