#!/usr/bin/env bash

GPUS=4
PORT=${PORT:-29500}
PYTHON=${PYTHON:-"python"}

CONFIG=configs/icdar2017mlt/base.py
WORK_DIR=work_dirs/mask_rcnn_r50_fpn_train_base

$PYTHON -m torch.distributed.launch --nproc_per_node=$GPUS \
                                    --nnodes=1 --node_rank=0 --master_addr="localhost" \
                                    --master_port=$PORT \
                                    tools/train.py \
                                    $CONFIG \
                                    --no-validate \
                                    --launcher pytorch \
                                    --work-dir ${WORK_DIR} \
                                    --seed 0

#!/usr/bin/env bash

GPUS=4
PORT=${PORT:-29500}
PYTHON=${PYTHON:-"python"}

CONFIG=configs/icdar2017mlt/vrm.py
WORK_DIR=work_dirs/mask_rcnn_r50_fpn_train_vrm

$PYTHON -m torch.distributed.launch --nproc_per_node=$GPUS \
                                    --nnodes=1 --node_rank=0 --master_addr="localhost" \
                                    --master_port=$PORT \
                                    tools/train.py \
                                    $CONFIG \
                                    --no-validate \
                                    --launcher pytorch \
                                    --work-dir ${WORK_DIR} \
                                    --seed 0

#!/usr/bin/env bash

GPUS=4
PORT=${PORT:-29500}
PYTHON=${PYTHON:-"python"}

# pre-training
CONFIG=configs/icdar2017mlt/core_pretrain.py
WORK_DIR=work_dirs/mask_rcnn_r50_fpn_train_core_pretrain

$PYTHON -m torch.distributed.launch --nproc_per_node=$GPUS \
                                    --nnodes=1 --node_rank=0 --master_addr="localhost" \
                                    --master_port=$PORT \
                                    tools/train.py \
                                    $CONFIG \
                                    --no-validate \
                                    --launcher pytorch \
                                    --work-dir ${WORK_DIR} \
                                    --seed 0

# training
CONFIG=configs/icdar2017mlt/core.py
WORK_DIR=work_dirs/mask_rcnn_r50_fpn_train_core

$PYTHON -m torch.distributed.launch --nproc_per_node=$GPUS \
                                    --nnodes=1 --node_rank=0 --master_addr="localhost" \
                                    --master_port=$PORT \
                                    tools/train.py \
                                    $CONFIG \
                                    --no-validate \
                                    --launcher pytorch \
                                    --work-dir ${WORK_DIR} \
                                    --seed 0

GPUS=4
PORT=${PORT:-29500}
CONFIG=path/to/config
CHECKPOINT=path/to/checkpoint

python -m torch.distributed.launch --nproc_per_node=$GPUS --master_port=$PORT \
    ./tools/test.py $CONFIG $CHECKPOINT --launcher pytorch \
    --eval segm \
    --not-encode-mask \
    --eval-options "jsonfile_prefix=path/to/work_dir/results/eval" "gt_path=data/icdar2017mlt/icdar2017mlt_gt.zip"

data
└── icdar2017mlt
    ├── annotations
    |   ├── ICDAR2017_train.json
    |   └── ICDAR2017_val.json
    ├── icdar2017mlt_gt.zip
    └── image
         ├── train
         └── val

@inproceedings{9428457,
  author={Lin, Jingyang and Pan, Yingwei and Lai, Rongfeng and Yang, Xuehang and Chao, Hongyang and Yao, Ting},
  booktitle={2021 IEEE International Conference on Multimedia and Expo (ICME)},
  title={Core-Text: Improving Scene Text Detection with Contrastive Relational Reasoning},
  year={2021},
  pages={1-6},
  doi={10.1109/ICME51207.2021.9428457}
}