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"""
TODOs:
- argparse
- List sequences by number
- Get rid of asserts
"""
import pandas as pd
import os.path as osp
import os
import json
import configparser
import tqdm
import argparse
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument('--motsynth-path', help="Directory path containing the 'annotations' directory with .json files")
parser.add_argument('--save-path', help='Root file in which the new annoation files will be stored. If not provided, motsynth-root will be used')
parser.add_argument('--save-dir', default='mots_annotations', help="name of directory within 'save-path'in which MOTS annotation files will be stored")
args = parser.parse_args()
if args.save_path is None:
args.save_path = args.motsynth_path
return args
def save_seqinfo(seqinfo_path, info):
seqinfo = configparser.ConfigParser()
seqinfo.optionxform = str # Otherwise capital letters are ignored in keys
seqinfo['Sequence'] = dict(name=info['seq_name'],
frameRate=info['fps'],
seqLength=info['sequence_length'],
imWidth= info['img_width'],
imHeight= info['img_height'],
weather=info['weather'],
time=info['time'],
isNight=info['is_night'],
isMoving=info['is_moving'],
FOV=info['cam_fov'],
imExt='.jpg',
fx=1158,
fy=1158,
cx=960,
cy=540)
with open(seqinfo_path, 'w') as configfile: # save
seqinfo.write(configfile, space_around_delimiters=False)
def main(args):
ann_dir = osp.join(args.motsynth_path, 'annotations')
mots_ann_dir = osp.join(args.save_path, args.save_dir)
seqs = [f'{seq_num:03}' for seq_num in range(768) if seq_num not in (629, 757, 524, 652)]
for seq in tqdm.tqdm(seqs):
ann_path = osp.join(ann_dir, f'{seq}.json')
with open(ann_path) as f:
seq_ann = json.load(f)
rows = []
img_id2frame = {im['id']: im['frame_n'] for im in seq_ann['images']}
for ann in seq_ann['annotations']:
assert ann['category_id'] == 1
if ann['area']: # Include only objects with non-empty masks
if not ann['iscrowd']:
mots_id = 2000 + ann['ped_id']
else: # ID = 10000 means that the instance should be ignored during eval.
mots_id = 10000
row = {'time_frame': img_id2frame[ann['image_id']],# STARTS AT 0!!!
'id': mots_id,
'class_id': 2,
'img_height': ann['segmentation']['size'][0],
'img_width': ann['segmentation']['size'][1],
'rle': ann['segmentation']['counts']}
rows.append(row)
# Save gt.txt file
# Format in https://www.vision.rwth-aachen.de/page/mots
mots_ann = pd.DataFrame(rows, columns = ['time_frame', 'id', 'class_id', 'img_height', 'img_width', 'rle'])
gt_dir = osp.join(mots_ann_dir, seq, 'gt')
os.makedirs(gt_dir, exist_ok=True)
mots_ann.to_csv(osp.join(gt_dir, 'gt.txt'), header=None, index=None, sep=' ')
# Save seqinfo.ini
seqinfo_path = osp.join(mots_ann_dir, seq, 'seqinfo.ini')
save_seqinfo(seqinfo_path, info = seq_ann['info'])
if __name__ =='__main__':
args = parse_args()
main(args) |