File size: 2,915 Bytes
650e244 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 |
# Copyright (c) MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import argparse
import glob
import json
import logging
import os
from dataset import consep_nuclei_dataset
logger = logging.getLogger(__name__)
def main():
logging.basicConfig(
level=logging.INFO,
format="[%(asctime)s] [%(process)s] [%(threadName)s] [%(levelname)s] (%(name)s:%(lineno)d) - %(message)s",
datefmt="%Y-%m-%d %H:%M:%S",
force=True,
)
parser = argparse.ArgumentParser()
parser.add_argument(
"--input",
"-i",
type=str,
default=r"/workspace/data/CoNSeP",
help="Input/Downloaded/Extracted dir for CoNSeP Dataset",
)
parser.add_argument(
"--output",
"-o",
type=str,
default=r"/workspace/data/CoNSePNuclei",
help="Output dir to store pre-processed data",
)
parser.add_argument("--crop_size", "-s", type=int, default=128, help="Crop size for each Nuclei")
parser.add_argument("--limit", "-n", type=int, default=0, help="Non-zero value to limit processing max records")
args = parser.parse_args()
dataset_json = {}
for f, v in {"Train": "training", "Test": "validation"}.items():
logger.info("---------------------------------------------------------------------------------")
if not os.path.exists(os.path.join(args.input, f)):
logger.warning(f"Ignore {f} (NOT Exists in Input Folder)")
continue
logger.info(f"Processing Images/labels for: {f}")
images_path = os.path.join(args.input, f, "Images", "*.png")
labels_path = os.path.join(args.input, f, "Labels", "*.mat")
images = sorted(glob.glob(images_path))
labels = sorted(glob.glob(labels_path))
ds = [{"image": i, "label": l} for i, l in zip(images, labels)]
output_dir = os.path.join(args.output, f) if args.output else f
crop_size = args.crop_size
limit = args.limit
ds_new = consep_nuclei_dataset(ds, output_dir, crop_size, limit=limit)
logger.info(f"Total Generated/Extended Records: {len(ds)} => {len(ds_new)}")
dataset_json[v] = ds_new
ds_file = os.path.join(args.output, "dataset.json")
with open(ds_file, "w") as fp:
json.dump(dataset_json, fp, indent=2)
logger.info(f"Dataset JSON Generated at: {ds_file}")
if __name__ == "__main__":
main()
|