Flip

Synthetic Data generation with Flip! Generate thousands of new 2D images from a small batch of objects and backgrounds.

Installation

Install Flip using pip:

pip install flip-data

Dependencies

Flip requires:

• Python (>= 3.7)
• Opencv (>= 4.3.0)
• Numpy (>= 1.19.1)

Quick Start (Example)

To try Flip library you can run examples/data_generator.py. You will need to add background images and objects to compose your new training dataset, then place them in the following directories:

BACKGROUNDS_PATTERN = "examples/data/backgrounds/*"
OBJECTS_PATTERN = "examples/data/objects/**/*"

The main workflow in Flip is to create transformers and then execute them as follows:

## Import Flip transformers
import flip.transformers as tr

OUT_DIR = "examples/result"

...

## Create Child transformers
transform_objects = [
        tr.data_augmentation.Rotate(mode='random'),
        tr.data_augmentation.Flip(mode='y'),
        tr.data_augmentation.RandomResize(
            mode='symmetric_w',
            relation='parent',
            w_percentage_min=0.2,
            w_percentage_max=0.5
        )
    ]

## Create main transformer
transform = tr.Compose([
    tr.ApplyToObjects(transform_objects),
    tr.domain_randomization.ObjectsRandomPosition(
        x_min=0, y_min=0.4, x_max=0.7, y_max=0.7, mode='percentage'
    ),
    tr.data_augmentation.Flip('x'),
    tr.domain_randomization.Draw(),
    tr.labeler.CreateBoundingBoxes(),
    tr.io.CreateJson(out_dir=OUT_DIR, name='img_generate.jpg'),
    tr.io.CreateJson(out_dir=OUT_DIR, name='json_generated.jpg')
])

## Execute transformations
el = tr.Element(image=..., objects=...)
[el] = transform(el)

Transformers

The main transformers are:

• Transformer
• Compose
• ApplyToObjects

By the way, all Transformers will be executed over objects of class Element and will return a new transformed Element.

Data Augmentation

• Flip: Flip the Element in x or y axis.
• RandomResize: Change the size of an Element randomly.
• Rotate: Rotate Element randomly.

Random Domain

• Draw: Draw objects over background Element to merge them into a new image.
• ObjectsRandomPosition: Set Random positions to objects over background Element.

Labeler

• CreateBoundingBoxes: Draw bounding boxes around the objects contained by a background Element.

IO

• SaveImage: Save a .jpg File with the new generated image.
• Json: Save generated Labels as a Json.
• Csv: Save generated Labels as a CSV.

Want to Contribute or have any doubts or feedback?

If you want extra info, email me at [email protected]

Report Issues

Please help us by reporting any issues you may have while using Flip.

License

• Flip License