S083
收藏NIAID Data Ecosystem2026-03-12 收录
下载链接:
https://zenodo.org/record/3600131
下载链接
链接失效反馈官方服务:
资源简介:
A fully annotated subset of the SO242/1_83-1_AUV10 image dataset. The annotations are given as train and test splits that can be used to evaluate machine learning methods. The following classes of fauna were used for annotation:
anemone
coral
crustacean
ipnops fish
litter
ophiuroid
other fauna
sea cucumber
sponge
stalked crinoid
For a definition of the classes see [1].
Related datasets:
S155: https://doi.org/10.5281/zenodo.3603803
S171: https://doi.org/10.5281/zenodo.3603809
S233: https://doi.org/10.5281/zenodo.3603815
This dataset contains the following files:
annotations/test.csv: The BIIGLE CSV annotation report of the annotations of the test split of this dataset. These annotations are used to test the performance of the trained Mask R-CNN model.
annotations/train.csv: The BIIGLE CSV annotation report of the annotations of the train split of this dataset. These annotations are used to generate the annotation patches which are transformed with scale and style transfer to be used to train the Mask R-CNN model.
images/: Directory that contains all the original image files.
dataset.json: JSON file that contains information about the dataset.
name: The name of the dataset.
images_dir: Name of the directory that contains the original image files.
metadata_file: Path to the CSV file that contains image metadata.
test_annotations_file: Path to the CSV file that contains the test annotations.
train_annotations_file: Path to the CSV file that contains the train annotations.
annotation_patches_dir: Name of the directory that should contain the scale- and style-transferred annotation patches.
crop_dimension: Edge length of an annotation or style patch in pixels.
metadata.csv: A CSV file that contains metadata for each original image file. In this case the distance of the camera to the sea floor is given for each image.
创建时间:
2020-10-06



