Drone-detection-dataset

Dataset containing IR, visible and audio data that can be used to train and evaluate drone detection sensors and systems.

Video labels: Airplane, Bird, Drone and Helicopter. Audio labels: Drone, Helicopter and Background.

The dataset contains 90 audio clips and 650 videos (365 IR and 285 visible). If all images are extracted from all the videos the dataset has a total of 203328 annotated images.

Free to download, use and edit. Descriptions of the videos are found in "Video_dataset_description.xlsx". The videos can be used as they are, or together with the respective label-files. The annotations are in .mat-format and have been done using the Matlab video labeler. Some instructions and examples are found in "Create_a_dataset_from_videos_and_labels.m"

Reading the labels in Python (no MATLAB required)

The .mat label files use MATLAB Computer Vision Toolbox groundTruth MCOS objects, which scipy.io.loadmat, pymatreader, and mat73 cannot decode (see Issue #3).

You can now read the labels in pure Python with mcos-decoder (PyPI, DOI 10.5281/zenodo.19728531):

pip install mcos-decoder

from mcos_decoder import load_groundtruth

bboxes = load_groundtruth("Data/Video_IR/IR_DRONE_001_LABELS.mat")
# → list[(x, y, w, h) | None] of length n_frames
# Each entry is the per-frame bbox in pixels, or None when target absent.

for frame_idx, bbox in enumerate(bboxes, start=1):
    if bbox is None:
        print(f"Frame {frame_idx}: target absent")
    else:
        x, y, w, h = bbox
        print(f"Frame {frame_idx}: bbox=({x:.1f}, {y:.1f}, {w:.1f}, {h:.1f})")

The decoder has been validated on all 365 IR sequences across the four target classes (AIRPLANE, BIRD, DRONE, HELICOPTER) — bbox counts match the official MATLAB reference. See mcos-decoder/README.md for details.

Please cite:
"Svanström F. (2020). Drone Detection and Classification using Machine Learning and Sensor Fusion". Link to thesis
or
"Svanström F, Englund C and Alonso-Fernandez F. (2020). Real-Time Drone Detection and Tracking With Visible, Thermal and Acoustic Sensors". Link to ICPR2020-paper
or
"Svanström F, Alonso-Fernandez F and Englund C. (2021). A Dataset for Multi-Sensor Drone Detection". Link to Data in Brief

Contact:
DroneDetectionThesis@gmail.com