import os
import re
import json
import logging
import random
import numpy as np
from argparse import ArgumentParser
from util.logging import logging_config
from PIL import Image
logger = logging.getLogger(__name__)
logging_config()
random.seed(1234)
def get_dataset(metadataset_split_file, aircraft_trainval_file,
aircraft_test_file, aircraft_box_file):
with open(metadataset_split_file) as f:
split_data = json.load(f)
test_split = split_data["test"]
bbox_dataset = {}
with open(aircraft_box_file) as f:
for line in f.readlines():
line = line.strip().split()
image_id, bbox_1, bbox_2, bbox_3, bbox_4 = line[0], int(
line[1]), int(line[2]), int(line[3]), int(line[4])
bbox_dataset[image_id] = (bbox_1, bbox_2, bbox_3, bbox_4)
parser.add_argument("--config",
action="store",
type=str,
required=True,
help="config file path")
parser.add_argument("--mode",
action="store",
type=str,
choices=["train", "resume", "eval"],
required=True)
parser.add_argument("--cpu", action="store_true")
parser.add_argument("--log",
action="store",
type=str,
required=False,
default=None,
help="log file path")
# parse args
args = parser.parse_args()
# init config
config = Config(config_path=args.config)
config.load_config()
logging_config(config["checkpoint.save_dir"], args.log)
config.copy_config()
# start training
run(config, args.mode, args.cpu)