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#Iphone xs dota 2 images update
#Iphone xs dota 2 images code

The images and ground truths of test-challenge Test-challenge contains 6,053 images and 1,090,637 instances. We released the images but not the ground Test-dev contains 2,792 images and 353,346 instances. We released the imagesĪnd ground truths for training and validation sets.

Validation contains 593 images and 81,048 instances. Training contains 1,830 images and 268,627 instances. We have two test sets, namely test-dev and test-challenge. To avoid the problem of overfitting, the proportion of training and validation set is smaller than the test set. The 11,268 images of DOTA are split into training, validation, test-dev, and test-challenge sets. Compared to DOTA-v1.5, it further adds the new categories of ”airport”Īnd ”helipad”. There are 18 common categories,ġ1,268 images and 1,793,658 instances in DOTA-v2.0.

DOTA-v2.0 collects more Google Earth, GF-2 Satellite, and aerial images.

This version was released for the DOAI ChallengeĢ019 on Object Detection in Aerial Images in conjunction with IEEE CVPR 2019. The number of images and dataset splits are the same as DOTA-v1.0. Moreover, a new category, ”container crane” is added.

DOTA-v1.5 uses the same images as DOTA-v1.0, but the extremely small instances (less than 10 pixels)Īre also annotated.

Set, validation set, and testing set in DOTA-v1.0 are 1/2, 1/6, and 1/3, respectively.

DOTA-v1.0 contains 15 common categories, 2,806 images and 188, 282 instances.

#Iphone xs dota 2 images update

We will continue to update DOTA, to grow in size and scope to reflect evolving real-world conditions. The instances in DOTA images are annotated by experts in aerial image interpretation by arbitrary (8 d.o.f.) quadrilateral. Each image is of the size in the rangeĢ0,000 × 20,000 pixels and contains objects exhibiting a wide variety of scales, orientations, and shapes. The images are collected from different sensors and platforms. It can be used to develop and evaluate object detectors

DOTA-v1.0 released with all images and oriented bounding box annotations for training and vallidation!ĭOTA is a large-scale dataset for object detection in aerial images.ODAI：a contest of object detection in aerial images on."A large-scale dataset for instance segmentation in aerial images" (Ĭode of “Learning RoI Transformer for Detecting Oriented Objects in Aerial Images” has released.

#Iphone xs dota 2 images code

The new benchmark DOTA-v2.0, including dataset, code library and 70 baselines, is released. LUAI, a contest of object in aerial images on ICCV 2021, is now open.