| 1234567891011121314151617181920212223242526272829 |
- # copyright (c) 2020 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 numpy as np
- def interpretation_predict(model, images):
- model.arrange_transforms(
- transforms=model.test_transforms, mode='test')
- new_imgs = []
- for i in range(images.shape[0]):
- img = images[i]
- new_imgs.append(model.test_transforms(img)[0])
- new_imgs = np.array(new_imgs)
- result = model.exe.run(
- model.test_prog,
- feed={'image': new_imgs},
- fetch_list=list(model.explanation_feats.values()))
- return result
|