person_monitor/dependence/PaddleDetection/dataset/mot/gen_labels_MOT.py

# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import os.path as osp
import os
import numpy as np

MOT_data = 'MOT16'

# choose a data in ['MOT15', 'MOT16', 'MOT17', 'MOT20']
# or your custom data (prepare it following the 'docs/tutorials/PrepareMOTDataSet.md')


def mkdirs(d):
    if not osp.exists(d):
        os.makedirs(d)


seq_root = './{}/images/train'.format(MOT_data)
label_root = './{}/labels_with_ids/train'.format(MOT_data)
mkdirs(label_root)
seqs = [s for s in os.listdir(seq_root)]

tid_curr = 0
tid_last = -1
for seq in seqs:
    seq_info = open(osp.join(seq_root, seq, 'seqinfo.ini')).read()
    seq_width = int(seq_info[seq_info.find('imWidth=') + 8:seq_info.find(
        '\nimHeight')])
    seq_height = int(seq_info[seq_info.find('imHeight=') + 9:seq_info.find(
        '\nimExt')])

    gt_txt = osp.join(seq_root, seq, 'gt', 'gt.txt')
    gt = np.loadtxt(gt_txt, dtype=np.float64, delimiter=',')

    seq_label_root = osp.join(label_root, seq, 'img1')
    mkdirs(seq_label_root)

    for fid, tid, x, y, w, h, mark, label, _ in gt:
        if mark == 0 or not label == 1:
            continue
        fid = int(fid)
        tid = int(tid)
        if not tid == tid_last:
            tid_curr += 1
            tid_last = tid
        x += w / 2
        y += h / 2
        label_fpath = osp.join(seq_label_root, '{:06d}.txt'.format(fid))
        label_str = '0 {:d} {:.6f} {:.6f} {:.6f} {:.6f}\n'.format(
            tid_curr, x / seq_width, y / seq_height, w / seq_width,
            h / seq_height)
        with open(label_fpath, 'a') as f:
            f.write(label_str)