Rotational Data Augmentation for YOLO

Requirement

numpy
opencv-python

Before and after

Before: the block at left-top corner is bounded by a white box.

After: Image is rotated anticlockwise by 30 degree and the block is still bounded by the white box.

Directory structure

.
├── check_label.py
├── rotation.py
├── data_original
│   ├── images
│   │   └── test00.png
│   └── labels
│       └── test00.txt
└── data_rotational
    ├── images
    │   ├── test00_000.jpg
    │   ├── test00_030.jpg
    │   └── ...
    └── labels
        ├── test00_000.txt
        ├── test00_030.txt
        └── ...

data_original is directory with your images and labels. After running rotation.py, rotated images and labels will be stored in data_rotational.

Generate augmented data

python rotation.py DATASET_INPUT

DATASET_INPUT is data_original in this example. The default output destination directory is data_rotational.

You can use python rotation.py -h to get more information.

Visualize generated images and labels

python check_label.py DATASET_INPUT

DATASET_INPUT is data_rotational in this example.

You can use python check_label.py -h to get more information.