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gray2pseudo_color.py
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gray2pseudo_color.py
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# coding: utf8
# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve.
#
# 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.
from __future__ import print_function
import argparse
import os
import os.path as osp
import sys
import numpy as np
from PIL import Image
def parse_args():
parser = argparse.ArgumentParser(
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument(
'dir_or_file', help='input gray label directory or file list path')
parser.add_argument('output_dir', help='output colorful label directory')
parser.add_argument('--dataset_dir', help='dataset directory')
parser.add_argument('--file_separator', help='file list separator')
return parser.parse_args()
def get_color_map_list(num_classes):
"""
Returns the color map for visualizing the segmentation mask,
which can support arbitrary number of classes.
Args:
num_classes (int): Number of classes.
Returns:
(list). The color map.
"""
num_classes += 1
color_map = num_classes * [0, 0, 0]
for i in range(0, num_classes):
j = 0
lab = i
while lab:
color_map[i * 3] |= (((lab >> 0) & 1) << (7 - j))
color_map[i * 3 + 1] |= (((lab >> 1) & 1) << (7 - j))
color_map[i * 3 + 2] |= (((lab >> 2) & 1) << (7 - j))
j += 1
lab >>= 3
color_map = color_map[3:]
return color_map
def gray2pseudo_color(args):
"""将灰度标注图片转换为伪彩色图片"""
input = args.dir_or_file
output_dir = args.output_dir
if not osp.exists(output_dir):
os.makedirs(output_dir)
print('Creating colorful label directory:', output_dir)
color_map = get_color_map_list(256)
if os.path.isdir(input):
for fpath, dirs, fs in os.walk(input):
for f in fs:
try:
grt_path = osp.join(fpath, f)
_output_dir = fpath.replace(input, '')
_output_dir = _output_dir.lstrip(os.path.sep)
im = Image.open(grt_path)
lbl = np.asarray(im)
lbl_pil = Image.fromarray(lbl.astype(np.uint8), mode='P')
lbl_pil.putpalette(color_map)
real_dir = osp.join(output_dir, _output_dir)
if not osp.exists(real_dir):
os.makedirs(real_dir)
new_grt_path = osp.join(real_dir, f)
lbl_pil.save(new_grt_path)
print('New label path:', new_grt_path)
except:
continue
elif os.path.isfile(input):
if args.dataset_dir is None or args.file_separator is None:
print('No dataset_dir or file_separator input!')
sys.exit()
with open(input) as f:
for line in f:
parts = line.strip().split(args.file_separator)
grt_name = parts[1]
grt_path = os.path.join(args.dataset_dir, grt_name)
im = Image.open(grt_path)
lbl = np.asarray(im)
lbl_pil = Image.fromarray(lbl.astype(np.uint8), mode='P')
lbl_pil.putpalette(color_map)
grt_dir, _ = osp.split(grt_name)
new_dir = osp.join(output_dir, grt_dir)
if not osp.exists(new_dir):
os.makedirs(new_dir)
new_grt_path = osp.join(output_dir, grt_name)
lbl_pil.save(new_grt_path)
print('New label path:', new_grt_path)
else:
print('It\'s neither a dir nor a file')
if __name__ == '__main__':
args = parse_args()
gray2pseudo_color(args)