dataeval.utils.datasets.AntiUAVDetection

class dataeval.utils.datasets.AntiUAVDetection(root, image_set='train', transforms=None, download=False, verbose=False)

A UAV detection dataset focused on detecting UAVs in natural images against large variation in backgrounds.

The dataset comes from the paper Vision-based Anti-UAV Detection and Tracking by Jie Zhao et. al. (2022).

The dataset is approximately 1.3 GB and can be found here. Images are collected against a variety of different backgrounds with a variety in the number and type of UAV. Ground truth labels are provided for the train, validation and test set. There are 35 different types of drones along with a variety in lighting conditions and weather conditions.

There are 10,000 images: 5200 images in the training set, 2200 images in the validation set, and 2600 images in the test set. The dataset only has a single UAV class with the focus being on identifying object location in the image. Ground-truth bounding boxes are provided in (x0, y0, x1, y1) format. The images come in a variety of sizes from 3744 x 5616 to 160 x 240.

Parameters:
root : str or pathlib.Path

Root directory where the data should be downloaded to or the antiuavdetection folder of the already downloaded data.

image_set : "train", "val", "test", or "base", default "train"

If “base”, then the full dataset is selected (train, val and test).

transforms : Transform, Sequence[Transform] or None, default None

Transform(s) to apply to the data.

download : bool, default False

If True, downloads the dataset from the internet and puts it in root directory. Class checks to see if data is already downloaded to ensure it does not create a duplicate download.

verbose : bool, default False

If True, outputs print statements.

path

Location of the folder containing the data.

Type:

pathlib.Path

image_set

The selected image set from the dataset.

Type:

“train”, “val”, “test”, or “base”

index2label

Dictionary which translates from class integers to the associated class strings.

Type:

dict[int, str]

label2index

Dictionary which translates from class strings to the associated class integers.

Type:

dict[str, int]

Return type:

dict[str, int]

metadata

Typed dictionary containing dataset metadata, such as id which returns the dataset class name.

Type:

DatasetMetadata

transforms

The transforms to be applied to the data.

Type:

Sequence[Transform]

size

The size of the dataset.

Type:

int

Note

Data License: Apache 2.0