train.py

from detectron2.utils.logger import setup_logger

setup_logger()

from detectron2.data.datasets import register_coco_instances
from detectron2.engine import DefaultTrainer

import os
import pickle

from utlis import *

config_file_path = "COCO-InstanceSegmentation/mask_rcnn_R_101_FPN_3x.yaml"
checkpoint_url = "COCO-InstanceSegmentation/mask_rcnn_R_101_FPN_3x.yaml"

output_dir = "/content/drive/MyDrive/vstech/1"
num_classes = 1

device = "cuda"

train_dataset_name = "LP_train"
train_images_path = "/content/drive/MyDrive/image_test/train"
train_json_annot_path = "/content/drive/MyDrive/image_test/train.json"

test_dataset_name = "LP_test"
test_images_path = "/content/drive/MyDrive/image_test/test"
test_json_annot_path = "/content/drive/MyDrive/image_test/test.json"

cfg_save_path = "IS_COVER_MASK_cfg.pickle"

########################
register_coco_instances(name= train_dataset_name, metadata={},
                        json_file=train_json_annot_path,image_root=train_images_path)

register_coco_instances(name=test_dataset_name, metadata={},
                        json_file=test_json_annot_path,image_root=test_images_path)

# plot_samples(dataset_name=train_dataset_name,n=2)

#########################
def main():
    cfg = get_train_cfg(config_file_path,checkpoint_url,train_dataset_name,test_dataset_name,num_classes,device,output_dir)

    with open(cfg_save_path, 'wb') as f:
        pickle.dump(cfg,f,protocol=pickle.HIGHEST_PROTOCOL)

    os.makedirs(cfg.OUTPUT_DIR, exist_ok=True)

    trainer = DefaultTrainer(cfg)
    trainer.resume_or_load(resume=False)

    trainer.train()

if __name__ == '__main__':
    main()