|
|
|
|
#!/usr/bin/env python
|
|
|
|
|
|
|
|
|
|
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
|
|
|
|
|
#
|
|
|
|
|
# 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 os
|
|
|
|
|
import os.path as osp
|
|
|
|
|
|
|
|
|
|
import cv2
|
|
|
|
|
import paddle
|
|
|
|
|
import paddlers
|
|
|
|
|
from tqdm import tqdm
|
|
|
|
|
|
|
|
|
|
import bootstrap
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
def read_file_list(file_list, sep=' '):
|
|
|
|
|
with open(file_list, 'r') as f:
|
|
|
|
|
for line in f:
|
|
|
|
|
line = line.strip()
|
|
|
|
|
parts = line.split(sep)
|
|
|
|
|
yield parts
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
def parse_args():
|
|
|
|
|
parser = argparse.ArgumentParser()
|
|
|
|
|
parser.add_argument(
|
|
|
|
|
"--model_dir", default=None, type=str, help="Path of saved model.")
|
|
|
|
|
parser.add_argument("--data_dir", type=str, help="Path of input dataset.")
|
|
|
|
|
parser.add_argument("--file_list", type=str, help="Path of file list.")
|
|
|
|
|
parser.add_argument(
|
|
|
|
|
"--save_dir",
|
|
|
|
|
default='./exp/predict',
|
|
|
|
|
type=str,
|
|
|
|
|
help="Path of directory to save prediction results.")
|
|
|
|
|
parser.add_argument(
|
|
|
|
|
"--ext",
|
|
|
|
|
default='.png',
|
|
|
|
|
type=str,
|
|
|
|
|
help="Extension name of the saved image file.")
|
|
|
|
|
return parser.parse_args()
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
if __name__ == '__main__':
|
|
|
|
|
args = parse_args()
|
|
|
|
|
|
|
|
|
|
model = paddlers.tasks.load_model(args.model_dir)
|
|
|
|
|
|
|
|
|
|
if not osp.exists(args.save_dir):
|
|
|
|
|
os.makedirs(args.save_dir)
|
|
|
|
|
|
|
|
|
|
with paddle.no_grad():
|
|
|
|
|
for parts in tqdm(read_file_list(args.file_list)):
|
|
|
|
|
im1_path = osp.join(args.data_dir, parts[0])
|
|
|
|
|
im2_path = osp.join(args.data_dir, parts[1])
|
|
|
|
|
|
|
|
|
|
pred = model.predict((im1_path, im2_path))
|
|
|
|
|
cm = pred['label_map']
|
|
|
|
|
# {0,1} -> {0,255}
|
|
|
|
|
cm[cm > 0] = 255
|
|
|
|
|
cm = cm.astype('uint8')
|
|
|
|
|
|
|
|
|
|
if len(parts) > 2:
|
|
|
|
|
name = osp.basename(parts[2])
|
|
|
|
|
else:
|
|
|
|
|
name = osp.basename(im1_path)
|
|
|
|
|
name = osp.splitext(name)[0] + args.ext
|
|
|
|
|
out_path = osp.join(args.save_dir, name)
|
|
|
|
|
cv2.imwrite(out_path, cm)
|
