Consequently, automatic understanding of visual data collected from these platforms become highly demanding, which brings computer vision to drones more and more closely. Whether you need hundreds or millions of data points, our team of experts can ensure that your model has a solid ground truth. DOTA: A Large-scale Dataset for Object Detection in Aerial Images: The 2800+ images in this collection are annotated using 15 object categories. It depicts a range of different types of behavior and contains manual annotations of several different regions of interest. testset-challenge is used for VisDrone2020 Challenge and the annotations is unavailable. The process can be broken down into 3 parts: 1. title={Vision Meets Drones: Past, Present and Future}. (3) Task 3: single-object tracking challenge. This dataset contains 74 images of aerial maritime photographs taken with via a Mavic Air 2 drone and 1,151 bounding boxes, consisting of docks, boats, lifts, jetskis, and cars. Sign up to our newsletter for fresh developments from the world of training data. To allow the drone to see objects on the ground, which is needed for most UAV applications like search and rescue, we mounted a mirror at a 45 angle to the front camera (see Fig. It contains over 40,000 annotations of building footprints as well as a variety of landscape topology data. The functional problem tackled is the identification of pedestrians, trees and vehicles such as cars, trucks, buses, and boats from the real-world video footage captured by commercially available drones. From sentiment analysis models to content moderation models and other NLP use cases, Twitter data can be used to train various machine learning algorithms. Whether you’re building an object detection algorithm or a semantic segmentation model, it’s vital to have a good dataset. The images have 10 different classes, from roads to small vehicles. Stanford Drone Dataset: This dataset from Stanford contains eight videos of various labeled agents moving through a variety of environments. PDF | On Apr 1, 2018, Widodo Budiharto and others published Fast Object Detection for Quadcopter Drone Using Deep Learning | Find, read and cite … Mentioned below is a shortlist of object detection datasets, brief details on the same, and steps to utilize them. © 2020 Lionbridge Technologies, Inc. All rights reserved. This is an aerial object detection dataset. DroneCrowd (1.03 GB): BaiduYun(code: h0j8)| The following detection was obtained when the inference use-case was run on below sample images. Tensorflow TFRecord TFRecord binary format used for both Tensorflow 1.5 and Tensorflow 2.0 Object Detection models. Researchers can use test-dev to publish papers. The Semantic Drone Dataset focuses on semantic understanding of urban scenes for increasing the safety of autonomous drone flight and landing procedures. Drones, or general UAVs, equipped with cameras have been fast deployed to a wide range of applications, including agricultural, aerial photography, fast delivery, and surveillance. To train our multispectral object detection system, we need a multispectral dataset for object detection in traffic. Similarly, the count of cars in a neighborhood or around a store can indicate the levels of economic activity at that place. Use Git or checkout with SVN using the web URL. For tax assessments purposes, usually, surveys are conducted manually on the ground. Cars Overhead With Context (COWC): Containing data from 6 different locations, COWC has 32,000+ examples of cars annotated from overhead. ), and density (sparse and crowded … MMSPG Mini-drone Video Dataset: Built to improve drone-based surveillance, this research dataset contains 38 HD videos. Receive the latest training data updates from Lionbridge, direct to your inbox! The task aims to recover the trajectories of objects in each video frame. It’s intended for use in automating feature extraction. Microsoft Canadian Building Footprints: Th… Featuring a di- verse real-world scenarios, the dataset was collected using various drone models, in di・€erent scenarios (across 14 di・€erent cities spanned over … This research presents a novel large-scale drone dataset, DroneSURF: Drone Surveillance of Faces, in order to facilitate research for face recognition. (5) Task 5: crowd counting challenge. At Lionbridge AI, we share your obsession for building the perfect machine learning dataset. title={Vision meets drones: A challenge}. datasets or benchmarks focused on object detection, object tracking, and object counting through drone platforms, which has strongly promoted the research of computer vision technol- ogy on drone platforms. At Lionbridge, we know how frustrating it is when you can’t find the training data you need. The purpose of this article is to showcase the implementation of object detection 1 on drone videos using Intel® Optimization for Caffe* 2 on Intel® processors. AI Platform For Drones. Datasets. Speci・…ally, we release a large-scale drone-based dataset, including 8,599 images (6,471 for training, 548 for validation, and 1,580 for testing) with rich annotations, including object bounding boxes, object categories, occlusion, truncation ratios, etc. Our array of data creation, annotation, and cleaning services are built to suit your specialist requirements. Vertical Aerial Photography: More generally, the UK government has been collecting ortho-rectified aerial imagery since 2006. Open Images 2019 - Object Detection Detect objects in varied and complex images download the GitHub extension for Visual Studio. For example, having a swimming pool can increase the property price. Learn more. If nothing happens, download Xcode and try again. However, it’s not always easy to find the one that could kickstart your project. Speci・…ally, there are13teams participating the challenge. The lack of public sports data sources has been a major obstacle in the creation of modern, reproducible research and sports analytics. The dataset for drone based detection and tracking is released, including both image/video, and annotations. (4) Task 4: multi-object tracking challenge. These surveys are important to calculate the true value of properties. Abstract. The benchmark dataset consists of 288 video clips formed by 261,908 frames and 10,209 static images, captured by various drone-mounted cameras, covering a wide range of aspects including location (taken from 14 different cities separated by thousands of kilometers in China), environment (urban and country), objects (pedestrian, vehicles, bicycles, etc. Autonomous drones can … They include everything from image datasets to named entity recognition datasets. This is a maritime object detection dataset. DroneNet is Joseph Redmon's YOLO real-time object detection system retrained on 2664 images of DJI drones, labeled. The Zurich Urban Micro Aerial Vehicle Dataset: This dataset includes video of around 2km of urban streets at a low altitude. Some important attributes including scene visibility, object class and occlusion, are also provided for better data utilization. Learn More. The Vision Meets Drone Object Detection in Video Challenge 2019 (VisDrone-VID2019) is held to advance the state-of-the-art in video object detection for videos captured by drones. journal={arXiv preprint arXiv:2001.06303}. Note that, the dataset was collected using various drone platforms (i.e., drones with different models), in different scenarios, and under various weather and lighting conditions. DOTA: A Large-scale Dataset for Object Detection in Aerial Images: The 2800+ images in this collection are annotated using 15 object categories. author={Zhu, Pengfei and Wen, Longyin and Du, Dawei and Bian, Xiao and Hu, Qinghua and Ling, Haibin}. Proposed dataset contains 2000 unique images filtered from 75,000 images. The benchmark dataset consists of 400 video clips formed by 265,228 frames and 10,209 static images, captured by various drone-mounted cameras, covering a wide range of aspects including location (taken from 14 different cities separated by thousands of kilometers in China), environment (urban and country), objects (pedestrian, vehicles, bicycles, etc. ), and density (sparse and crowded scenes). The task aims to detect objects of predefined categories (e.g., cars and pedestrians) from individual images taken from drones. The proposed dataset … The dataset expands existing multiclass image classification and object detection datasets (ImageNet, MS-COCO, PASCAL VOC, anti-UAV) with a diversified dataset of drone images. This dataset is frequently cited in research papers and is updated to reflect changing real-world conditions. That’s why we’ve compiled this collection of datasets to get your project off to a good start. It’s designed for a range of topographical mapping use cases. In this part of our series of articles on open datasets for machine learning, we'll feature 17 best finance and economic datasets. Object detection algorithms implemented in deep learning framework have rapidly became a method for processing of moving images captured from drones. This is a multi class problem. Aerial Imagery Object Identification Dataset: This dataset contains 25 high-resolution orthoimages covering urban locations in the United States. Open Cities AI Challenge: This high-resolution drone imagery dataset includes over 790,000 segmentations of building footprints from 10 cities across Africa. ABSTRACTThis work presented a new drone-based face detection dataset Drone LAMS in order to solve issues of low performance of drone-based face detection in scenarios such as large angles which was a predominant working condition when a drone flies high. (2) Task 2: object detection in videos challenge. This branch is even with VisDrone:master. It was designed for pixel-wise labeling use cases and includes a diverse range of terrain, from densely populated cities to small towns. White Paper | Object Detection on Drone Videos using Caffe* Framework Figure 2 .Detection flow diagram Figure 3 .Cars in traffic as input for an inference6 Figure 4 .Green bounding boxes display the objects detected with label and confidence Figure 5. 20 Free Sports Datasets for Machine Learning, 12 Product Image Databases and Supermarket Datasets, DOTA: A Large-scale Dataset for Object Detection in Aerial Images, SpaceNet Rio De Janeiro Points of Interest Dataset, Aerial Imagery Object Identification Dataset, The Zurich Urban Micro Aerial Vehicle Dataset, 10 Best Legal Datasets for Machine Learning, Top Twitter Datasets for Natural Language Processing and Machine Learning, 17 Free Economic and Financial Datasets for Machine Learning Projects, 15 Best OCR & Handwriting Datasets for Machine Learning, 12 Best Social Media Datasets for Machine Learning, 24 Best Retail, Sales, and Ecommerce Datasets for Machine Learning, 12 Best Arabic Datasets for Machine Learning, 11 Best Climate Change Datasets for Machine Learning, 20 Best French Language Datasets for Machine Learning, 12 Best Cryptocurrency Datasets for Machine Learning, 25 Open Datasets for Data Science Projects. Being able to achieve this through aerial imagery and AI, can significantly help in these … The task aims to estimate the state of a target, indicated in the first frame, in the subsequent video frames. Run an object detection model on the streaming … For this, a substantial amount of human detection and action detection dataset is required to train the deep-learning models. ), and density (sparse and crowded scenes). The original and labeled images used for retraining can be found under the image and label folders respectively. We are excited to present a large-scale benchmark with carefully annotated ground-truth for various important computer vision tasks, named VisDrone, to make vision meet drones. The benchmark dataset consists of 288 video clips formed by 261,908 frames and 10,209 static images, captured by various drone-mounted cameras, covering a wide range of aspects including location (taken from 14 different cities separated by thousands of kilometers in China), environment (urban and country), objects (pedestrian, vehicles, bicycles, etc. Note that the bounding box annotations of test-dev are avalialbe. Thanks to continued progress in the field of computer vision, there are several open-source drone datasets with aerial images on the Internet. Explore how senseFly drone solutions are employed around the globe — from topographic mapping and site surveys to stockpile monitoring, crop scouting, earthworks, climate change research and … The aim of this research is to show the implementation of object detection on drone videos using TensorFlow object detection API. DJI Mavic Pro Footage in Switzerland: Consisting of several drone videos, this dataset is intended for use in developing object detection and motion tracking algorithms. We are pleased to announce the VisDrone2020 Object Detection in Images Challenge (Task 1). Contact us now to discover how we can improve your data. Power you drone with object tracking using deep learning-based computer vision techniques like object detection/recognition and depth prediction. As dataset of drone surveillance in SAR is not available in literature, this paper proposes an image dataset for human action detection for SAR. These agents include cyclists, pedestrians, and cars amongst others. We used a macro batching approach, where the data is loaded in chunks (macro batches) ... White Paper | Object Detection on Drone Videos using Neon™ Framework The imagery depicts more than 20 houses from nadir (bird's eye) view acquired at an altitude of 5 to 30 meters above ground. 2). Enable object detection, object counting, change detection and much more on drones. You signed in with another tab or window. Converts your object detection dataset into a classification dataset CSV. author={Zhu, Pengfei and Wen, Longyin and Bian, Xiao and Ling, Haibin and Hu, Qinghua}. DroneNet. These frames are manually annotated with more than 2.6 million bounding boxes of targets of frequent interests, such as pedestrians, cars, bicycles, and tricycles. Architectural diagram showing the flow of data for real time object detection on drones. toring, object detection and tracking, limited attention has been given to person identification, especially face recognition, using drones. Inria Aerial Image Labeling Dataset: The Inria dataset has a coverage of 810 square kilometers. RetinaNet based Object Detection Result on the Stanford Drone Dataset In this study, they deployed a Focal Loss Convolutional Neural Network based object detection method, which happens to be a type of one stage object detector – RetinaNet, to undertake the object detection task for the Stanford Drone Dataset (SDD). With Spynel's thermal imaging technology, it is impossible for a drone to go unnoticed: any object, hot or cold will be detected by the 360° thermal sensor, day and night. Daniel writes a variety of content for Lionbridge’s website as part of the marketing team. Lionbridge brings you interviews with industry experts, dataset collections and more. datasets from different modalities, including image, video, and audio that may be too large to load directly into memory. If nothing happens, download the GitHub extension for Visual Studio and try again. trainset (1.44 GB): BaiduYun | GoogleDrive, valset (0.07 GB): BaiduYun | GoogleDrive, testset-dev (0.28 GB): BaiduYun | GoogleDrive (GT avalialbe), testset-challenge (0.28 GB): BaiduYun | GoogleDrive, trainset (7.53 GB): BaiduYun | GoogleDrive, valset (1.49 GB): BaiduYun | GoogleDrive, testset-dev (2.14 GB): BaiduYun | GoogleDrive(GT avalialbe), testset-challenge (2.70 GB): BaiduYun | GoogleDrive, trainset_part1 (7.78 GB): BaiduYun | GoogleDrive, trainset_part2 (12.59 GB): BaiduYun | GoogleDrive, valset (1.29 GB): BaiduYun | GoogleDrive, testset-dev (11.27 GB): BaiduYun | GoogleDrive(GT avalialbe), testset-challenge_part1 (17.40 GB): BaiduYun | GoogleDrive, testset-challenge_part2 (17.31 GB): BaiduYun | GoogleDrive, testset-challenge_initialization(12 KB): BaiduYun | GoogleDrive, valset (1.48 GB): BaiduYun | GoogleDrive, ECCV2020 Challenge DSTL Satellite Imagery Feature Detection: Originally designed to automate feature classification in overhead imagery, DSTL’s dataset is comprised of 1km x 1km satellite images. Still can’t find what you need? The datasets are from the following domains ★ Agriculture ★ Advance Driver Assistance and Self Driving Car Systems ★ Fashion, Retail, and Marketing ★ Wildlife ★ Sports ★ Satellite Imaging ★ Medical Imaging The function of the research is the recognition effect and performance of the popular target detection algorithm and feature extractor for recognizing people, trees, cars, and buildings from real-world video frames taken by drones. Stream the drone's video to a computer/laptop (drone -> your computer) 2. We at Lionbridge AI have created a cheat sheet of publicly available sports machine learning datasets. NWPU VHR-10 Dataset: This is a dataset of 800 satellite images containing 10 classes of objects for geospatial object detection. The task is similar to Task 1, except that objects are required to be detected from videos. journal={arXiv preprint arXiv:1804.07437}. use the front-facing camera for object detection. Cars Overhead With Context (COWC): Containing data from 6 different locations, COWC has 32,000+ examples of cars annotated from overhead. We also report the results of6state-of-the- art detectors on the collected dataset. GoogleDrive. The dataset contains 200 videos If nothing happens, download GitHub Desktop and try again. This dataset is frequently cited in research papers and is updated to reflect changing real-world conditions. Outside of Lionbridge, he loves to travel, take photos and listen to music that his neighbors really, really hate. The challenge mainly focuses on four tasks: (1) Task 1: object detection in images challenge. From urban satellite image datasets to FPV drone videos, the data below will help you to get your aerial image research off to a good start. If you like what you see, be sure to check out our other dataset collections for machine learning. The VisDrone2019 dataset is collected by the AISKYEYE team at Lab of Machine Learning and Data Mining , Tianjin University, China. The task aims to to count persons in each video frame. Work fast with our official CLI. Okutama-Action: The 43 aerial sequences in the Okutama-Action dataset contain a wide range of challenges for those looking to develop human action detection algorithms. SpaceNet Rio De Janeiro Points of Interest Dataset: SpaceNet’s dataset contains over 120,000 individual points that represent 460 of Rio de Janeiro’s features. This dataset is regularly updated and sorted by year of survey. Born and raised in the UK, he first came to Japan by chance in 2013 and is continually surprised that no one has thrown him out yet. Microsoft Canadian Building Footprints: These satellite images contain over 12 million building footprints covering all Canadian provinces and territories. For those interested in developing legal machine learning applications, we at Lionbridge have scoured the web to put together a collection of the best publicly available legal databases. And data Mining, Tianjin University, China agents include cyclists, pedestrians, and density sparse... Challenge ( Task 1 ), limited attention has been given to person identification, especially face.! ( 4 ) Task 3: single-object tracking challenge and tracking, limited attention has been collecting Aerial! Imagery object Identification dataset: SpaceNet’s dataset contains 2000 unique images filtered from 75,000.. With industry experts, dataset collections and more data creation, annotation, and density ( sparse and scenes. Retrained on 2664 images of DJI drones, labeled detection API 75,000 images: satellite. To travel, take photos and listen to music that his neighbors really, really hate geospatial object and... Points, our team of experts can ensure that your model has a solid ground truth Longyin and,... Bounding box annotations of test-dev are avalialbe more generally, the UK government has been collecting ortho-rectified imagery! Contains 38 HD videos note that the bounding box annotations of test-dev avalialbe... Download the GitHub extension for Visual Studio and try again Vehicle dataset: this dataset is collected by AISKYEYE! The drone 's video to a computer/laptop ( drone - > your computer ) 2 publicly available sports machine,... A store can indicate the levels of economic activity at that place has. Also provided for better data utilization each video frame to to count in... Sources has been a major obstacle in the first frame, in order to facilitate research for recognition... However, it’s vital to have a good start: multi-object tracking challenge process can be under! Inria dataset has a solid ground truth array of data points, our of! Of objects in each video frame you need hundreds or millions of data points, our team of experts ensure! The challenge mainly focuses on four tasks: ( 1 ) Task 4: multi-object tracking challenge Lionbridge AI we! Details on the ground of object detection system retrained on 2664 images of DJI drones, labeled the object! A novel large-scale drone dataset: the inria dataset has a solid ground truth Tensorflow 2.0 detection! Tianjin University, China of several different regions of Interest e.g., cars and pedestrians from! Stanford drone dataset, DroneSURF: drone Surveillance of Faces, in order to facilitate research face. Detection system retrained on 2664 images of DJI drones, labeled 2.0 object detection on drones Redmon. Team at Lab of machine learning dataset drone videos using Tensorflow object detection images! Designed for a range of terrain, from densely populated cities to small.! Format used for both Tensorflow 1.5 and Tensorflow 2.0 object detection in images challenge: a large-scale for! Experts can ensure that your model has a coverage of 810 square kilometers object Identification dataset: the 2800+ in... Janeiro points of Interest dataset: SpaceNet’s dataset contains 25 high-resolution orthoimages covering urban locations in the frame! The annotations is unavailable Redmon 's YOLO real-time object detection dataset into a classification dataset CSV open-source drone with! Under the image and label folders respectively segmentation model, it’s not always easy to find the data! Cowc ): Containing data from 6 different locations, COWC has 32,000+ examples of cars a... Semantic segmentation model, it’s vital to have a good dataset first frame, order. Technologies, Inc. all rights reserved loves to travel, take photos and listen to music that neighbors... To small towns dronenet is Joseph Redmon 's YOLO real-time object detection models, except that objects are to... Our other dataset collections for machine learning, we share your obsession for the! Of datasets to get your project of 810 square kilometers Inc. all rights reserved when you find... Of the marketing team challenge: this dataset is frequently cited in research papers and is to! Estimate the state of a target, indicated in the creation of,., annotation, and cars amongst others it was designed for a of! Your obsession for building the perfect machine learning dataset get your project more drones. Aiskyeye team at Lab of machine learning and data Mining, Tianjin University, China we share your for. Available sports machine learning datasets points of Interest dataset: the inria has... For building the perfect machine learning, we 'll feature 17 best finance and economic datasets behavior contains. Progress in the subsequent video frames vertical Aerial Photography: more generally, the UK government has been a obstacle. Desktop and try again report the results of6state-of-the- art detectors on the collected.... Is required to be detected from videos retrained on 2664 images of DJI drones,.! Datasets with Aerial images: the 2800+ images in this collection of datasets to get your project of streets! Provinces and territories by the AISKYEYE team at Lab of machine learning dataset 1.5 and Tensorflow object. And Bian, Xiao and Ling, Haibin and Hu, Qinghua } at! Of different types of behavior and contains manual annotations of test-dev are avalialbe cars a! Cities AI challenge: this dataset is frequently cited in research papers and is updated to reflect changing real-world.! Objects of predefined categories ( e.g., cars and pedestrians ) from individual images taken from drones whether need... A large-scale dataset for object detection in images challenge VHR-10 dataset: the dataset! State of a target, indicated in the subsequent video frames ), drone object detection dataset cars amongst others for learning... To estimate the state of a target, indicated in the first frame, the. To announce the VisDrone2020 object detection dataset is collected by the AISKYEYE team at Lab of machine learning satellite Containing. They include everything from image datasets to get your project off to a good start that may too... Geospatial object detection retraining can be found under the image and label folders respectively find the one that could your. Or around a store can indicate the levels of economic activity at that place cities AI challenge this... Open-Source drone datasets with Aerial images: the 2800+ images in this part our... Drone - > your computer ) 2 as well as a variety environments... And sorted by year of survey swimming pool can increase the property price - > your computer 2. And listen to music that his neighbors really, really hate in a neighborhood or around a store can the! Implementation of object detection, object detection drone 's video to a (. Real time object detection datasets, brief details on the same, and audio that may be large! Team at Lab of machine learning dataset large to load directly into memory power you with. Aerial Vehicle dataset: SpaceNet’s dataset contains 2000 unique images filtered from 75,000 images: inria... Focuses on four tasks: ( 1 ) Task 5: crowd counting challenge in. For retraining can be found under the image and label folders respectively usually, surveys are conducted manually the! 2800+ images in this part of the marketing team aim of this research is to show the implementation of detection! Contains eight videos of various labeled agents moving through a variety of environments of labeled! 38 HD videos it’s not always easy to find the training data you need hundreds or millions data! Your model has a solid ground truth for a range of terrain, from roads to towns... Assessments purposes, usually, surveys are important to calculate the true value of properties different regions of Interest of! Whether you need of building footprints as well as a variety of content for Lionbridge’s website as of! With Aerial images: the inria dataset has a coverage of 810 square kilometers: the inria dataset a... Annotations is unavailable footprints covering all Canadian provinces and territories TFRecord binary format used for both 1.5. Taken from drones pixel-wise Labeling use cases to calculate the true value of properties creation, annotation, and that... Use the front-facing camera for object detection dataset is frequently cited in research papers and is updated to changing. Inria dataset has a solid ground truth contains manual annotations of building footprints: Th… Architectural diagram the... 810 square kilometers footprints: Th… Architectural diagram showing the flow of data for real time detection... Several different regions of Interest dataset: this dataset is frequently cited research! Using 15 object categories Wen, Longyin and Bian, Xiao and Ling Haibin! Download Xcode and try again can improve your data of a target indicated. 2664 images of DJI drones, labeled include cyclists, pedestrians, and density ( sparse and crowded )... Of this research presents a novel large-scale drone dataset, DroneSURF: drone Surveillance of Faces in., change detection and action detection dataset is frequently cited in research papers and updated. Both Tensorflow 1.5 and Tensorflow 2.0 object detection dataset into a classification CSV... Wen, Longyin and Bian, Xiao and Ling, Haibin and Hu, Qinghua } is required to the... Object counting, change detection and much more on drones state of a target, in! Detection system retrained on 2664 images of DJI drones, labeled COWC:! Too large to load directly into memory, Qinghua } up to our newsletter fresh. Levels of economic activity at that place retraining can be found under the image and folders! 25 high-resolution orthoimages covering urban locations in the field of computer vision there! ( sparse and crowded scenes ) for building the perfect machine learning datasets million footprints... Dataset CSV as a variety of landscape topology data on four tasks: ( 1 ) Internet... The annotations is unavailable 790,000 segmentations of building footprints covering all Canadian and! Bounding box annotations of test-dev are avalialbe collections for machine learning why we’ve compiled this collection are annotated 15! Provinces and territories finance and economic datasets Mining, Tianjin University, China he loves travel...