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# Copyright (c) 2020 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 paddle
from paddleseg.cvlibs import manager, Config
from paddleseg.utils import get_sys_env, logger, config_check
from paddleseg.core import predict
def parse_args():
parser = argparse.ArgumentParser(description='Model prediction')
# params of prediction
parser.add_argument(
"--config", dest="cfg", help="The config file.", default=None, type=str)
parser.add_argument(
'--model_path',
dest='model_path',
help='The path of model for prediction',
type=str,
default=None)
parser.add_argument(
'--image_path',
dest='image_path',
help=
'The path of image, it can be a file or a directory including images',
type=str,
default=None)
parser.add_argument(
'--save_dir',
dest='save_dir',
help='The directory for saving the predicted results',
type=str,
default='./output/result')
# augment for prediction
parser.add_argument(
'--aug_pred',
dest='aug_pred',
help='Whether to use mulit-scales and flip augment for prediction',
action='store_true')
parser.add_argument(
'--scales',
dest='scales',
nargs='+',
help='Scales for augment',
type=float,
default=1.0)
parser.add_argument(
'--flip_horizontal',
dest='flip_horizontal',
help='Whether to use flip horizontally augment',
action='store_true')
parser.add_argument(
'--flip_vertical',
dest='flip_vertical',
help='Whether to use flip vertically augment',
action='store_true')
# sliding window prediction
parser.add_argument(
'--is_slide',
dest='is_slide',
help='Whether to prediction by sliding window',
action='store_true')
parser.add_argument(
'--crop_size',
dest='crop_size',
nargs=2,
help=
'The crop size of sliding window, the first is width and the second is height.',
type=int,
default=None)
parser.add_argument(
'--stride',
dest='stride',
nargs=2,
help=
'The stride of sliding window, the first is width and the second is height.',
type=int,
default=None)
return parser.parse_args()
def get_image_list(image_path):
"""Get image list"""
valid_suffix = [
'.JPEG', '.jpeg', '.JPG', '.jpg', '.BMP', '.bmp', '.PNG', '.png'
]
image_list = []
image_dir = None
if os.path.isfile(image_path):
if os.path.splitext(image_path)[-1] in valid_suffix:
image_list.append(image_path)
elif os.path.isdir(image_path):
image_dir = image_path
for root, dirs, files in os.walk(image_path):
for f in files:
if '.ipynb_checkpoints' in root:
continue
if os.path.splitext(f)[-1] in valid_suffix:
image_list.append(os.path.join(root, f))
else:
raise FileNotFoundError(
'`--image_path` is not found. it should be an image file or a directory including images'
)
if len(image_list) == 0:
raise RuntimeError('There are not image file in `--image_path`')
return image_list, image_dir
def main(args):
env_info = get_sys_env()
place = 'gpu' if env_info['Paddle compiled with cuda'] and env_info[
'GPUs used'] else 'cpu'
paddle.set_device(place)
if not args.cfg:
raise RuntimeError('No configuration file specified.')
cfg = Config(args.cfg)
val_dataset = cfg.val_dataset
if not val_dataset:
raise RuntimeError(
'The verification dataset is not specified in the configuration file.'
)
msg = '\n---------------Config Information---------------\n'
msg += str(cfg)
msg += '------------------------------------------------'
logger.info(msg)
model = cfg.model
transforms = val_dataset.transforms
image_list, image_dir = get_image_list(args.image_path)
logger.info('Number of predict images = {}'.format(len(image_list)))
config_check(cfg, val_dataset=val_dataset)
predict(
model,
model_path=args.model_path,
transforms=transforms,
image_list=image_list,
image_dir=image_dir,
save_dir=args.save_dir,
aug_pred=args.aug_pred,
scales=args.scales,
flip_horizontal=args.flip_horizontal,
flip_vertical=args.flip_vertical,
is_slide=args.is_slide,
crop_size=args.crop_size,
stride=args.stride,
)
if __name__ == '__main__':
args = parse_args()
main(args)
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