# Copyright (c) 2021 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 os

from paddleseg.utils import logger

from ppmatting.core import predict
from ppmatting.utils import get_image_list
from tools.model import get_model


def seg(img_path: str, save_dir: str):
    image_list, image_dir = get_image_list(img_path)
    logger.info('Number of predict images = {}'.format(len(image_list)))

    model = get_model()

    return predict(
        model=model.model,
        model_path=model.path,
        transforms=model.transforms,
        image_list=image_list,
        image_dir=image_dir,
        trimap_list=None,
        save_dir=save_dir,
        fg_estimate=True)


def has_seg(img_path: str, save_dir: str):
    # 是否已经抠过图了
    paths = os.path.splitext(img_path)
    rgba = "{}_rgba{}".format(paths[0], paths[1])
    alpha = "{}_alpha{}".format(paths[0], paths[1])

    rgba_path = os.path.join(save_dir, rgba)
    alpha_path = os.path.join(save_dir, alpha)

    return os.path.exists(rgba_path) and os.path.exists(alpha_path), alpha_path, rgba_path