File size: 2,765 Bytes
3894c45 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 |
import os
import sys
import math
import itertools
import numpy as np
import tensorflow as tf
from PIL import Image
from argparse import ArgumentParser as AP
from waymo_open_dataset.utils import range_image_utils
from waymo_open_dataset.utils import transform_utils
from waymo_open_dataset.utils import frame_utils
from waymo_open_dataset import dataset_pb2 as open_dataset
def printProgressBar(i, max, postText):
n_bar = 20 #size of progress bar
j= i/max
sys.stdout.write('\r')
sys.stdout.write(f"[{'=' * int(n_bar * j):{n_bar}s}] {int(100 * j)}% {postText}")
sys.stdout.flush()
def main(cmdline_opt):
DS_PATH = cmdline_opt.load_path
files = os.listdir(DS_PATH)
files = [os.path.join(DS_PATH,x) for x in files]
with open('sunny_sequences.txt') as file:
sunny_sequences = file.read().splitlines()
for index_file, file in enumerate(files):
if not os.path.basename(file).split('_with_camera_labels.tfrecord')[0] in sunny_sequences: # Some sequences are wrongly annotated as sunny. We annotated a subset of really sunny images.
continue
dataset = tf.data.TFRecordDataset(file, compression_type='')
printProgressBar(index_file, len(files), "Files done")
for index_data, data in enumerate(dataset):
frame = open_dataset.Frame()
frame.ParseFromString(bytearray(data.numpy()))
if frame.context.stats.weather == 'sunny':
(range_images, camera_projections, range_image_top_pose) = frame_utils.parse_range_image_and_camera_projection(frame)
for label in frame.camera_labels:
if label.name == open_dataset.CameraName.FRONT:
path = os.path.join(cmdline_opt.save_path,
frame.context.stats.weather,
frame.context.stats.time_of_day,
'{}-{:06}.png'.format(os.path.basename(file), index_data))
im = tf.image.decode_png(frame.images[0].image)
pil_im = Image.fromarray(im.numpy())
res_img = pil_im.resize((480, 320), Image.BILINEAR)
os.makedirs(os.path.dirname(path), exist_ok=True)
res_img.save(path)
else:
break
if __name__ == '__main__':
ap = AP()
ap.add_argument('--load_path', default='/datasets_master/waymo_open_dataset_v_1_2_0/validation', type=str, help='Set a path to load the Waymo dataset')
ap.add_argument('--save_path', default='/datasets_local/datasets_fpizzati/waymo_480x320/val', type=str, help='Set a path to save the dataset')
main(ap.parse_args())
|