dataeval.utils.data.datasets.MILCO¶
-
class dataeval.utils.data.datasets.MILCO(root, download=
False, transforms=None, verbose=False)¶ A side-scan sonar dataset focused on mine (object) detection.
The dataset comes from the paper Side-scan sonar imaging data of underwater vehicles for mine detection by N.P. Santos et. al. (2024).
This class only accesses a portion of the above dataset due to size constraints. The full dataset contains 1170 side-scan sonar images collected using a 900-1800 kHz Marine Sonic dual frequency side-scan sonar of a Teledyne Marine Gavia Autonomous Underwater Vehicle. All the images were carefully analyzed and annotated, including the image coordinates of the Bounding Box (BB) of the detected objects divided into NOn-Mine-like BOttom Objects (NOMBO) and MIne-Like COntacts (MILCO) classes.
This dataset is consists of 261 images (120 images from 2015, 93 images from 2017, and 48 images from 2021). In these 261 images, there are 315 MILCO objects, and 175 NOMBO objects. The class “0” corresponds to a MILCO object and the class “1” corresponds to a NOMBO object. The raw BB coordinates provided in the downloaded text files are (x, y, w, h), given as percentages of the image (x_BB = x/img_width, y_BB = y/img_height, etc.). The images come in 2 sizes, 416 x 416 or 1024 x 1024.
- Parameters:¶
- root : str or pathlib.Path¶
Root directory of dataset where the
milcofolder exists.- 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.
- transforms : Transform | Sequence[Transform] | None, default None¶
Transform(s) to apply to the data.
- verbose : bool, default False¶
If True, outputs print statements.
- index2label¶
Dictionary which translates from class integers to the associated class strings.
- Type:¶
dict