iShip-1: 海面小目標船舶目標檢測數據集
iShip-1: Maritime Small-Scale Ship Detection Dataset
數據集概覽 Overview of the iShip-1
iShip-1數據集一共有17236張多視角、多天氣條件下拍攝的岸上和船上的圖像和相應的候選框標注數據組成。iShip-1將船型按功能劃分為5類，同時創新性地提供了小目標船的標注，為海面船舶檢測提出全新的挑戰。iShip-1提供VOC，COCO和YOLO格式的標注，以方便研究者們進行海面目標檢測的算法研究，助力人工智能賦能智能海洋。
The iShip-1 dataset consists of a total of 17,236 images of shore and ship taken under multi-view and multi-weather conditions and the corresponding annotations. iShip-1 divides ship types into 5 categories, and also innovatively provides the labels of small-scale ships, which poses a brand-new challenge for ship detection. iShip-1 provides VOC, COCO, and YOLO formats to facilitate researchers to conduct algorithmic research on ship detection, and help AI to empower the smart ocean.
數據集介紹 Introduction to the iShip-1
我們重新標注了Seaships數據集[1]共7000張圖像，并自行采集了10,236幅在不同天氣條件下拍攝的岸上和船上圖像。這些目標物按照功能劃分為5類：散貨船（Bulk Carrier），貨船（Cargo Ship）, 客船（Passenger Ship）, 漁船（Fishing Vessel）, 娛樂用船（Pleasure Craft），而小目標船（在圖片中所占面積比例小于0.5%）則統一被劃分為其他船（Other Ship）。圖像分辨率在800x600到6000x4000。
We re-labelled a total of 7,000 images from the Seaships dataset [1] and collected 10,236 shore and ship images taken under different weather conditions. These objects are classified into five categories according to their functions: Bulk Carrier, Cargo Ship, Passenger Ship, Fishing Vessel, and Pleasure Craft, while small objects (less than 0.5% of the area in the image) are uniformly classified as Other Ship. Image resolutions range from 800x600 to 6000x4000.
這些分類統計可視化結果如下：
The results of these categorical statistics are shown below:
我們使用多種模型在數據集上進行了基準測試，證明數據集在小目標檢測算法領域是具有一定的研究價值的。
We benchmarked the dataset using a variety of models and proved that the dataset’s research value in the field of small object detection algorithms.
下圖為yolov5在iShip-1上的PR曲線，其中小目標船檢測對模型提出了更大的挑戰。
The figure below shows the PR curve of yolov5 on iShip-1, where small-scale ship detection poses a greater challenge to the model.
部署推理視頻【2】：
Result Video [2]:
數據集樣例 Samples of the iShip-1
數據集使用說明 Instructions for use of the iShip-1
在images目錄下存放了jpg格式的圖片用于訓練，labels目錄下是YOLO格式的標注文件，annotations下是VOC格式的標注文件，coco目錄下是COCO格式的標注文件。
The images in jpg format are stored in the images directory for training, the labels directory contains annotation files in YOLO format, the annotations directory contains annotation files in VOC format, and the coco directory contains annotation files in COCO format.
數據集下載地址 Download Address
百度網盤：
鏈接：https://pan.baidu.com/s/17dRa-CvrX75jiw_Y0RHzbQ?pwd=f3rq
提取碼：f3rq
Google Netdisk:
link: https://drive.google.com/file/d/1iwC_ITv2_x1vZFQ7Z8ZnL_kSXMB3DrOa/view?usp=sharing
參考文獻 Reference：
[1] Shao, Z., Wu, W., Wang, Z., Du, W., Li, C.: Seaships: A large-scale precisely annotated dataset for ship detection. IEEE transactions on multimedia 20(10), 2593–2604 (2018)
[2] Prasad, D.K., Rajan, D., Rachmawati, L., Rajabally, E., Quek, C.: Video processing from electro-optical sensors for object detection and tracking in a maritime environment: A survey. IEEE Transactions on Intelligent Transportation Systems 18(8), 1993–2016 (2017)