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Configuration error
Configuration error
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# Copyright (c) 2021 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.
import argparse
import os
import sys
import cv2
import numpy as np
import paddle
from paddleseg.cvlibs import manager, Config
from paddleseg.utils import get_sys_env, logger
LOCAL_PATH = os.path.dirname(os.path.abspath(__file__))
sys.path.append(os.path.join(LOCAL_PATH, '..'))
manager.BACKBONES._components_dict.clear()
manager.TRANSFORMS._components_dict.clear()
import ppmatting
from ppmatting.core import predict
from ppmatting.utils import get_image_list, estimate_foreground_ml
def parse_args():
parser = argparse.ArgumentParser(
description='PP-HumanSeg inference for video')
parser.add_argument(
"--config",
dest="cfg",
help="The config file.",
default=None,
type=str,
required=True)
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='Image including human',
type=str,
default=None)
parser.add_argument(
'--trimap_path',
dest='trimap_path',
help='The path of trimap',
type=str,
default=None)
parser.add_argument(
'--background',
dest='background',
help='Background for replacing. It is a string which specifies the background color (r,g,b,w) or a path to background image. If not specified, a green background is used.',
type=str,
default=None)
parser.add_argument(
'--save_dir',
dest='save_dir',
help='The directory for saving the inference results',
type=str,
default='./output')
parser.add_argument(
'--fg_estimate',
default=True,
type=eval,
choices=[True, False],
help='Whether to estimate foreground when predicting.')
return parser.parse_args()
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)
msg = '\n---------------Config Information---------------\n'
msg += str(cfg)
msg += '------------------------------------------------'
logger.info(msg)
model = cfg.model
transforms = ppmatting.transforms.Compose(cfg.val_transforms)
alpha, fg = predict(
model,
model_path=args.model_path,
transforms=transforms,
image_list=[args.image_path],
trimap_list=[args.trimap_path],
save_dir=args.save_dir,
fg_estimate=args.fg_estimate)
img_ori = cv2.imread(args.image_path)
bg = get_bg(args.background, img_ori.shape)
alpha = alpha / 255.0
alpha = alpha[:, :, np.newaxis]
com = alpha * fg + (1 - alpha) * bg
com = com.astype('uint8')
com_save_path = os.path.join(args.save_dir,
os.path.basename(args.image_path))
cv2.imwrite(com_save_path, com)
def get_bg(background, img_shape):
bg = np.zeros(img_shape)
if background == 'r':
bg[:, :, 2] = 255
elif background is None or background == 'g':
bg[:, :, 1] = 255
elif background == 'b':
bg[:, :, 0] = 255
elif background == 'w':
bg[:, :, :] = 255
elif not os.path.exists(background):
raise Exception('The --background is not existed: {}'.format(
background))
else:
bg = cv2.imread(background)
bg = cv2.resize(bg, (img_shape[1], img_shape[0]))
return bg
if __name__ == "__main__":
args = parse_args()
main(args)
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