Skip to content
This repository was archived by the owner on Oct 25, 2021. It is now read-only.
This repository was archived by the owner on Oct 25, 2021. It is now read-only.

How to train on own dataset that already has train, val and test subfolders? #76

@mldlcv

Description

@mldlcv

My dataset has three subfolders - train, val and test. Each of these subfolders have two classes - class1 and class2. How do I use the classification pipeline script to train for this particular setup?

The current script splits the entire data into 5 folds (with 1 val fold) on the fly. But, I want to train for this already existing dataset splitup.

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Type

    No type

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions