ODA-Object-Detection-ttA
ODA is a test-time-augmentation tool for 2d object detectors.
Used in Kaggle object detection competitions!
Install
pip install oda
Usage
See Example.ipynb.
The setup is very simple, similar to ttach.
import oda
# Declare single scale TTA variations
mono = [oda.VerticalFlip(),oda.HorizontalFlip(), oda.Rotate90(), oda.Multiply(0.9), oda.Multiply(1.1)]
# Declare multiscale-TTA with 0.8~1.2x image sizes.
multi = [oda.MultiScale(i) for i in [0.8, 0.9, 1.1, 1.2]] + [oda.MultiScaleFlip(i) for i in [0.8, 0.9, 1.1, 1.2]]
# load image
impath = "imgs/cars3.jpg"
img = loadimg(impath)
# wrap model and tta
tta_model = oda.TTAWrapper(model, mono, multi)
# Execute TTA!
boxes, scores, labels = tta_model.inference(img)
- The image size should be square.
model output wrapping
- Wrap your detection model so that the output is similar to torchvision frcnn format: [["box":[[x,y,x2,y2], [], ..], "labels": [0,1,..], "scores": [1.0, 0.8, ..]]
Thanks
nms, wbf are from https://kaggle.com/zfturbo
tta is based on https://github.com/qubvel/ttach, https://github.com/andrewekhalel/edafa/tree/master/edafa and https://www.kaggle.com/shonenkov/wbf-over-tta-single-model-efficientdet
1 maintainer
Metadata
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Release files for odach 0.1.0-2010290533
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Release files / odach-0.1.0-2010290533.tar.gz
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