README.md

Semantic segmentation

The sample training script was made to train object detection models on PASCAL VOC 2012.

Ensure that you have holocron installed

git clone https://github.com/frgfm/Holocron.git
pip install -e Holocron/. --upgrade

No need to download the dataset, torchvision will handle this for you! From there, you can run your training with the following command

python train.py VOC2012 --model unet3p -b 4 -j 16 --opt radam --lr 1e-5 --sched onecycle --epochs 20

Performances are evaluated on the validation set of the dataset using the mean IoU metric.

Size (px)	Epochs	args	mean IoU	# Runs
256	200	VOC2012 --model unet_rexnet13 -b 16 --loss label_smoothing --opt adamp --device 0 --lr 2e-3 --epochs 200	32.14	1
256	20	VOC2012 --model unet3p -b 4 -j 16 --opt radam --lr 1e-5 --sched onecycle --epochs 20	14.17	1

Model	mean IoU	Param #	Interpolation	Image size
unet		18.11M	bilinear	256
unetp		28.28M	bilinear	256
unetpp		29.54M	bilinear	256
unet3p		26.93M	bilinear	256
unet_tvvgg11		32.17M	bilinear	256
unet_tvresnet34		36.25M	bilinear	256
unet_rexnet13	32.14	9.34M	bilinear	256