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#!/usr/bin/env python
# --------------------------------------------------------------------------------
# MPViT: Multi-Path Vision Transformer for Dense Prediction
# Copyright (c) 2022 Electronics and Telecommunications Research Institute (ETRI).
# All Rights Reserved.
# Written by Youngwan Lee
# --------------------------------------------------------------------------------
"""
Detection Training Script for MPViT.
"""
import os
import itertools
import torch
from typing import Any, Dict, List, Set
from detectron2.data import build_detection_train_loader
from detectron2.checkpoint import DetectionCheckpointer
from detectron2.config import get_cfg
from detectron2.engine import DefaultTrainer, default_argument_parser, default_setup, launch
from detectron2.evaluation import COCOEvaluator
from detectron2.solver.build import maybe_add_gradient_clipping
from ditod import add_vit_config
from ditod import DetrDatasetMapper
from detectron2.data.datasets import register_coco_instances
import logging
from detectron2.utils.logger import setup_logger
from detectron2.utils import comm
from detectron2.engine.defaults import create_ddp_model
import weakref
from detectron2.engine.train_loop import AMPTrainer, SimpleTrainer
from ditod import MyDetectionCheckpointer, ICDAREvaluator
from ditod import MyTrainer
def setup(args):
"""
Create configs and perform basic setups.
"""
cfg = get_cfg()
# add_coat_config(cfg)
add_vit_config(cfg)
cfg.merge_from_file(args.config_file)
cfg.merge_from_list(args.opts)
cfg.freeze()
default_setup(cfg, args)
return cfg
def main(args):
cfg = setup(args)
"""
register publaynet first
"""
register_coco_instances(
"publaynet_train",
{},
cfg.PUBLAYNET_DATA_DIR_TRAIN + ".json",
cfg.PUBLAYNET_DATA_DIR_TRAIN
)
register_coco_instances(
"publaynet_val",
{},
cfg.PUBLAYNET_DATA_DIR_TEST + ".json",
cfg.PUBLAYNET_DATA_DIR_TEST
)
register_coco_instances(
"icdar2019_train",
{},
cfg.ICDAR_DATA_DIR_TRAIN + ".json",
cfg.ICDAR_DATA_DIR_TRAIN
)
register_coco_instances(
"icdar2019_test",
{},
cfg.ICDAR_DATA_DIR_TEST + ".json",
cfg.ICDAR_DATA_DIR_TEST
)
if args.eval_only:
model = MyTrainer.build_model(cfg)
DetectionCheckpointer(model, save_dir=cfg.OUTPUT_DIR).resume_or_load(
cfg.MODEL.WEIGHTS, resume=args.resume
)
res = MyTrainer.test(cfg, model)
return res
trainer = MyTrainer(cfg)
trainer.resume_or_load(resume=args.resume)
return trainer.train()
if __name__ == "__main__":
parser = default_argument_parser()
parser.add_argument("--debug", action="store_true", help="enable debug mode")
args = parser.parse_args()
print("Command Line Args:", args)
if args.debug:
import debugpy
print("Enabling attach starts.")
debugpy.listen(address=('0.0.0.0', 9310))
debugpy.wait_for_client()
print("Enabling attach ends.")
launch(
main,
args.num_gpus,
num_machines=args.num_machines,
machine_rank=args.machine_rank,
dist_url=args.dist_url,
args=(args,),
)
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