Marine ship instance segmentation by deep neural networks using a global and local attention (GALA) mechanism
Visible-ship-dataset is a data set for ship instance segmentation tasks in visible light images. This dataset includes two types of marine ship instance segmentation datasets, named as MariBoats and MariBoatsSubclass respectively, which can be used for different research purpose. The MariBoats dataset used all the 6.2k images and all the ships labelled were assigned to only one category, namely ‘ship’, resulting in 15.7k ship segmentation annotations. This dataset with one category can satisfy the basic instance segmentation requirements (For example, avoiding obstacles (ships) during unmanned driving under the complex sea scene). The MariBoatsSubclass dataset contains 3.1k images and 4.5k ship annotations. This dataset has six categories of marine ships: Engineering Ship (Eng.), Cargo Ship (Carg.), Speedboat (Sp.), Passenger Ship (Pass.), Official Ship (Off.), and Unknown Ship (Unk.). This dataset can be used for both segmentation of ships and precise identification of marine ship categories in marine scenes. the Visible-ship-dataset draws on the construction process of the Microsoft Common Objects in Context (COCO) datasets, including visible light images with different resolutions. This dataset may be a benchmark for researchers to evaluate their approaches.
link：https://pan.baidu.com/s/1Lg2doyPyh2uazRma_pZpJw Extraction code:：2w0m ；weiyun link：https://share.weiyun.com/1jFkqLpK code：4yi5x3
one drive: https://1drv.ms/u/s!AgjHw_dVzKUrkXAwDFi6ZW4WiEho?e=zG9wPm
It is the global and local attention mechanism.
It is a method to convert labelme format to MS COCO format for convolutional neural network training.
It is a method to plot the distribution of image size and object size in a given dataset
It is a method for extracting annotations containing specific object labels from MS COCO format dataset
It is a method for extracting images containing specific object labels from MS COCO format dataset.
It is a method for automatically grabbing images of specific object labels from massive online databases
It is a method for merging a single label dataset into a dataset containing multiple object labels.
It is a method for modifying the target name to a specific label name in the dataset.
This implementation is based on mmdetection(v1.0.0),which can be found in the GitHub by searching the key word of mmdetection.
./tools/dist_train.sh ${CONFIG_FILE} ${GPU_NUM}
Example: ./tools/dist_train.sh configs/solo/solo_r50_fpn_8gpu_1x.py 4
./tools/dist_test.sh CONFIG_FILE CHECKPOINT_FILE GPU_NUM --show --out OUTPUT_FILE --eval segm
Example: ./tools/dist_test.sh configs/solo/solo_r50_fpn_8gpu_1x.py SOLO_R50_1x.pth 8 --show --out results_solo.pkl --eval segm
python tools/test_ins_vis.py CONFIG_FILE CHECKPOINT_FILE --show --save_dir ${SAVE_DIR}
Example: python tools/test_ins_vis.py configs/solo/solo_r50_fpn_8gpu_1x.py SOLO_R50_1x.pth --show --save_dir work_dirs/vis_solo
（Sun Z, Meng C, Huang T, et al. Marine ship instance segmentation by deep neural networks using a global and local attention (GALA) mechanism[J]. Plos one, 2023, 18(2): e0279248.）