Objects365_v1

displayName: Objects365 v1
labelTypes:
- Box2D
license:
- CC BY 4.0
mediaTypes:
- Image
paperUrl: https://openaccess.thecvf.com/content_ICCV_2019/papers/Shao_Objects365_A_Large-Scale_High-Quality_Dataset_for_Object_Detection_ICCV_2019_paper.pdf
publishDate: "2019"
publishUrl: https://github.com/open-mmlab/mmdetection/tree/dev-3.x/configs/objects365
publisher:
- Megvii Technology
tags:
- Clothing
- Animals
- Human
taskTypes:
- Object Detection

---
# 数据集介绍
## 简介
Objects365 Dataset V1 是一个全新的数据集，旨在促进目标检测研究，重点关注野外的各种物体。 它有超过 600K 训练图像的 365 个对象类别。 超过 1000 万个高质量的边界框是通过精心设计的三步注释管道手动标记的。 它是迄今为止最大的对象检测数据集（具有完整注释），并为社区建立了更具挑战性的基准。 Objects365 可以作为更好的特征学习数据集，用于对象检测和语义分割等本地化敏感任务。
Objects365 Consortium 不拥有图像的版权。 图片的使用必须遵守 Flickr 使用条款。 图像的用户对数据集的使用承担全部责任，包括但不限于使用他们可能从数据集创建的受版权保护的图像的任何副本。 您不会分发上述图片。 如果侵犯图片版权，我们将立即删除图片。

## Download dataset
:modelscope-code[]{type="git"}

displayName: Objects365 v1
labelTypes:
- Box2D
license:
- CC BY 4.0
mediaTypes:
- Image
paperUrl: https://openaccess.thecvf.com/content_ICCV_2019/papers/Shao_Objects365_A_Large-Scale_High-Quality_Dataset_for_Object_Detection_ICCV_2019_paper.pdf
publishDate: "2019"
publishUrl: https://github.com/open-mmlab/mmdetection/tree/dev-3.x/configs/objects365
publisher:
- Megvii Technology
tags:
- Clothing
- Animals
- Human
taskTypes:
- Object Detection

---
# Dataset Introduction
## Introduction
Objects365 Dataset V1 is a novel dataset designed to advance object detection research, with a focus on diverse objects in the wild. It encompasses 365 object categories across over 600K training images. Over 10 million high-quality bounding boxes were manually annotated through a meticulously crafted three-step annotation pipeline. To date, it represents the largest fully annotated object detection dataset, and has established a more challenging benchmark for the computer vision community. Objects365 can serve as an enhanced feature learning dataset for localization-sensitive tasks such as object detection and semantic segmentation.

The Objects365 Consortium does not hold the copyright of the images included in this dataset. The usage of these images must adhere to the Flickr Terms of Use. Users of the dataset bear full responsibility for its application, including but not limited to any copyrighted image copies derived from the dataset. You are prohibited from redistributing the aforementioned images. We will immediately remove the images upon detection of any copyright infringement.

## Download the Dataset
:modelscope-code[]{type="git"}