odach 0.1.0-2010290533

ODAch is a test-time-augmentation tool for pytorch 2d object detectors.

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