# Tencent is pleased to support the open source community by making GNES available.
#
# Copyright (C) 2019 THL A29 Limited, a Tencent company. 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 numpy as np
from PIL import Image
from ..base import BaseImagePreprocessor
from ...proto import gnes_pb2, blob2array, array2blob
[docs]class SizedPreprocessor(BaseImagePreprocessor):
def __init__(self,
target_width: int = 224,
target_height: int = 224,
*args, **kwargs):
super().__init__(*args, **kwargs)
self.target_width = target_width
self.target_height = target_height
[docs]class ResizeChunkPreprocessor(SizedPreprocessor):
[docs] def apply(self, doc: 'gnes_pb2.Document') -> None:
super().apply(doc)
for c in doc.chunks:
img = blob2array(c.blob)
img = np.array(Image.fromarray(img.astype('uint8')).resize((self.target_width, self.target_height)))
c.blob.CopyFrom(array2blob(img))