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# Copyright (c) Facebook, Inc. and its affiliates.
# Copyright (c) Meta Platforms, Inc. All Rights Reserved
import tqdm
import os
import os.path as osp
from pathlib import Path
import numpy as np
from PIL import Image
import scipy.io
def convert_pc59(mask_path, new_mask_path, pc59_dict):
mat = scipy.io.loadmat(mask_path)
mask = mat['LabelMap']
mask_copy = np.ones_like(mask, dtype=np.uint8) * 255
for trID, clsID in pc59_dict.items():
mask_copy[mask == clsID] = trID
min_value = np.amin(mask_copy)
assert min_value >= 0, print(min_value)
Image.fromarray(mask_copy).save(new_mask_path, "PNG")
def convert_pc459(mask_path, new_mask_path):
mat = scipy.io.loadmat(mask_path)
mask = mat['LabelMap']
mask = mask - 1
min_value = np.amin(mask)
assert min_value >= 0, print(min_value)
Image.fromarray(mask).save(new_mask_path, "TIFF")
if __name__ == "__main__":
dataset_dir = Path(os.getenv("DETECTRON2_DATASETS", "datasets"))
print('Caution: we only generate the validation set!')
pc_path = dataset_dir / "VOCdevkit/VOC2010"
val_list = open(pc_path / "pascalcontext_val.txt", "r")
pc459_labels = open(pc_path / "labels.txt", "r")
pc59_labels = open(pc_path / "59_labels.txt", "r")
pc459_dict = {}
for line in pc459_labels.readlines():
if ':' in line:
idx, name = line.split(':')
idx = int(idx.strip())
name = name.strip()
pc459_dict[name] = idx
pc59_dict = {}
for i, line in enumerate(pc59_labels.readlines()):
name = line.split(':')[-1].strip()
if name is not '':
pc59_dict[i] = pc459_dict[name]
pc459_dir = pc_path / "annotations_detectron2" / "pc459_val"
pc459_dir.mkdir(parents=True, exist_ok=True)
pc59_dir = pc_path / "annotations_detectron2" / "pc59_val"
pc59_dir.mkdir(parents=True, exist_ok=True)
for line in tqdm.tqdm(val_list.readlines()):
fileid = line.strip()
ori_mask = f'{pc_path}/trainval/{fileid}.mat'
pc459_dst = f'{pc459_dir}/{fileid}.tif'
pc59_dst = f'{pc59_dir}/{fileid}.png'
if osp.exists(ori_mask):
convert_pc459(ori_mask, pc459_dst)
convert_pc59(ori_mask, pc59_dst, pc59_dict) |