docker build -t person-segmentation .

docker run -it --rm --gpus=all --shm-size 8G -v `pwd`/data:/data -v `pwd`/logs:/logs person-segmentation

python src/train.py --train-images /data/picksart_persons/train/images/ \
                    --train-masks /data/picksart_persons/train/masks/ \
                    --val-images /data/picksart_persons/val/images/ \
                    --val-masks /data/picksart_persons/val/masks/ \
                    --batch-size 4 \
                    --logdir /logs/exp1/

python src/evaluate.py --images /data/picksart_persons/val/images/ \
                       --masks /data/picksart_persons/val/masks/ \
                       --model /path/to/model.pth \
                       --batch-size 4

python src/convert_to_tensorrt.py --input-model /path/to/pytorch-model.pth \
                                  --output-model /path/to/engine.plan

python src/speed_benchmark.py --torch-model /path/to/model.pth \
                              --trt-engine /path/to/ending.plan

trtexec --onnx=/path/to/model.onnx --verbose=True --workspace=9000 --shapes=input:1x3x320x320