Creating a dataset for a classification or segmentation task. If an annotation file is present, the annotations are also prepared. The dataset is created based on an imageset.

Imageset

Imagesets are collected images to build a dataset from, stored in the imagesets folder. The imagesets folder contains the following folder structure:

• imagesets/[imageset_type]/[imageset_name]

Inside the [imageset_name] folder are the following files / folders

• test/: test images (benchmark)
• trainval/: training and validation images for cross validation
• categories.txt: all categories (classes) the imageset contains

Dataset Folders

Data-sets are stored in the datasets base folder. The datasets folder contains the following folder structure:

• datasets/[dataset_type]/[dataset_name] where [dataset_type] is the same as the corresponding [imageset_type] and [dataset_name] is the same as the corresponding [imageset_name].

Inside the [dataset_name] folder are the following files / folders

• test/: test set (benchmark)
• train/: training set
• val/: validation set
• categories.txt: all categories (classes) the dataset contains

class Dataset[source]

Dataset(input_adapter:AnnotationAdapter, output_adapter:AnnotationAdapter, split=None, seed=None, sample=None) :: ABC

Dataset base class to build datasets. args: the arguments containing the parameters