Data Synthesis pipeline to generate object detection data
Project description
Object Detection Data Synthesis
Data Synthesis pipeline to generate object detection data
How to run
Run with pip
pip install mdetsyn
And run in python file
from mdetsyn import run_synthesis, create_args
args = create_args()
run_synthesis(args)
Run with command line
python synthesis.py --backgrounds ./backgrounds \
--objects ./objects \
--savename ./synthesis \
--number 1000 \
--class_mapping ./class_mapping.json \
--class_txt ./classes.txt
Sample
- Backgrounds folder contain background images (in any folmat)
├── backgrounds/
├── background-0.jpg
├── background-1.jpg
└── ...
- Objects folder contain object images in subfolders (the best is
.png
format withA
channel but any format is still runnable)
├── objects/
├── class_1/
│ ├── image-0.png
│ ├── image-1.png
│ └── ...
├── class_2/
└── ...
-
Each image in objects folder will be synthesis by
n
times withn
is user input -
Output is a synthesis folder contain
images
andlabels
dir same as YOLO format -
Sample visualization:
Background | Object | Synthesis |
---|---|---|
Support synthesis methods
- Random Resize
- Random Rotate
- Random Transparency
- Random Perspective Transform
- Seamless Clone
- Grayscale
Error and TODO
- Sometimes seamless clone does not work
- Input parameter for each augment
- Add default arguments to argparse help
Project details
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