TTPLA: An Aerial-Image Dataset for Detection and Segmentation of Transmission Towers and Power Lines

Abstract

Accurate detection and segmentation of transmission towers (TTs) and power lines (PLs) from aerial images plays a key role in protecting power-grid security and low-altitude UAV safety. Meanwhile, aerial images of TTs and PLs pose a number of new challenges to the computer vision researchers who work on object detection and segmentation -PLs are long and thin, and may show similar color as the background; TTs can be of various shapes and most likely made up of line structures of various sparsity; The background scene, lighting, and object sizes can vary significantly from one image to another. In this paper we collect and release a new TT/PL Aerial-image (TTPLA) dataset, consisting of 1,100 images with the resolution of 3,840×2,160 pixels, as well as manually labeled 8,987 instances of TTs and PLs. We develop novel policies for collecting, annotating, and labeling the images in TTPLA. Different from other relevant datasets, TTPLA supports evaluation of instance segmentation, besides detection and semantic segmentation. To build a baseline for detection and segmentation tasks on TTPLA, we report the performance of several state-of-the-art deep learning models on our dataset. TTPLA dataset is publicly available at https://github.com/r3ab/ttpla_dataset

Overview of Image Datasets for Deep Learning Applications in Diagnostics of Power Infrastructure

“…A number of the listed image batches could be used for classification problems [13,15,17,[19][20][21]23,24,[28][29][30][32][33][34][35]. There are also sets that provide ground truth labels for detection algorithms [12,[14][15][16][17][18][19][20][21][22][23][25][26][27][28][29][30][31][32][33][34][35], but as can be easily noticed, some of the sets fit into both categories. There are also several that support segmentation tasks as well [22,26,31,33].…”

“…There are also sets that provide ground truth labels for detection algorithms [12,[14][15][16][17][18][19][20][21][22][23][25][26][27][28][29][30][31][32][33][34][35], but as can be easily noticed, some of the sets fit into both categories. There are also several that support segmentation tasks as well [22,26,31,33]. Some of the reviewed collections have been in the public domain for several years.…”

“…TTPLA: An Aerial-Image Dataset for Detection and Segmentation of Transmission Towers and Power Lines [22] The best average scores for the bounding box and mask are 22.96% and 15.72%, respectively.…”