Patchmentation
Patchmentation is a python library to perform patch augmentation, a data augmentation technique for object detection, that allows for the synthesis of new images by combining objects from one or more source images into a background image.
The process of patch augmentation involves extracting objects of interest from the source images, transforming them, and then pasting them onto the background image to create a composite image, therefore increasing diversity at the object level. The resulting dataset offers a greater variety of object combinations within a single image, making it more robust and accurate when training object detection models.
Installation
The easiest way to install patchmentation is through pip.
pip install patchmentation
Note: Some functionality of patchmentation might not be working on non-Linux systems.
External Links
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GitHub Repository: https://github.com/Xu-Justin/patchmentation
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Docs: TBA
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Research Paper: TBA
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Benchmarking Results: https://github.com/Xu-Justin/patchmentation-yolov5
This project was developed as part of thesis project, Computer Science, BINUS University.
Metadata
Release files for patchmentation 0.1.16
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| patchmentation-0.1.16-py3-none-any.whl | Python 3 | none | any | Details |
Release files / patchmentation-0.1.16-py3-none-any.whl
| Download URL | patchmentation-0.1.16-py3-none-any.whl |
|---|---|
| Size | 27.3 kB |
| Tags | Python 3 |
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