FLORIDA dataset

This is the released FLORIDA dataset for our paper An Efficient Semi-Automated Scheme for Infrastructure LiDAR Annotation.

The dataset will be made publicly available after the acceptance of our paper.

Statistics

Dataset Format

Data format follows SUSTechPOINTS
To quickly view the dataset, unzip the all data and put them under the data folder of SUSTechPOINTS

SUSTechPOINTS
├── data
│   ├── DATA_20220927_010000
│   │   ├── lidar
│   │   │   ├── XXX.pcd
│   │   ├── label
│   │   │   ├── XXX.json
|   ├── DATA_20220927_011000_2300
│   │   ├── lidar
│   │   │   ├── XXX.pcd
│   │   ├── label
│   │   │   ├── XXX.json
...

Training sequences

DATA_20220927_010000
DATA_20220927_011000_2300
DATA_20220927_140000_1700
DATA_20220927_012000_1580
DATA_20220927_012500_800
DATA_20220927_161500
DATA_20220927_163000
DATA_20220927_170500_600
DATA_20220927_171000_400
DATA_20220927_164000_100
DATA_20220927_164000

Testing sequences

DATA_20221122_182000_0
DATA_20221121_230000_900

To load a label file into the unified 3D box definition: (x, y, z, dx, dy, dz, heading), as defined in OpenPCDet

import json

json_path = '<path to data folder>/<sequence_name>/label/<frame_name>.json'
json_file = open(json_path)
label_json = json.load(json_file)
label_list = []
label_names = []
for label in label_json:
    psr = label['psr']
    label_list.append([psr['position']['x'],
                       psr['position']['y'],
                       psr['position']['z'],
                       psr['scale']['x'],
                       psr['scale']['y'],
                       psr['scale']['z'],
                       psr['rotation']['z']])
    label_names.append(label['obj_type'])

Annotation tool

As an ablation study, we tested our annotation scheme and tool on the publicly available LUMPI dataset. The following screen recordings demonstrate the utilization of SOT and MOT models, as well as batch mode correction and helper functions.

Operations

Provided by SUSTechPOINTS

Batch mode adjustment
Automatic box fitting

Our Contributions

Annotation propagation up to 100 frames using SOT
Auto-annotation using MOT
Pedestrian trajectory smoothing and orentation correction
Static annotation propagation (for stopped or parked vehicles)
Vehicle orientation correction
Merging tracks

aotiansysu/FLORIDA_dataset