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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. | |
| """ | |
| This code is refer from: | |
| https://github.com/whai362/PSENet/blob/python3/models/loss/iou.py | |
| """ | |
| import paddle | |
| EPS = 1e-6 | |
| def iou_single(a, b, mask, n_class): | |
| valid = mask == 1 | |
| a = a.masked_select(valid) | |
| b = b.masked_select(valid) | |
| miou = [] | |
| for i in range(n_class): | |
| if a.shape == [0] and a.shape == b.shape: | |
| inter = paddle.to_tensor(0.0) | |
| union = paddle.to_tensor(0.0) | |
| else: | |
| inter = ((a == i).logical_and(b == i)).astype('float32') | |
| union = ((a == i).logical_or(b == i)).astype('float32') | |
| miou.append(paddle.sum(inter) / (paddle.sum(union) + EPS)) | |
| miou = sum(miou) / len(miou) | |
| return miou | |
| def iou(a, b, mask, n_class=2, reduce=True): | |
| batch_size = a.shape[0] | |
| a = a.reshape([batch_size, -1]) | |
| b = b.reshape([batch_size, -1]) | |
| mask = mask.reshape([batch_size, -1]) | |
| iou = paddle.zeros((batch_size, ), dtype='float32') | |
| for i in range(batch_size): | |
| iou[i] = iou_single(a[i], b[i], mask[i], n_class) | |
| if reduce: | |
| iou = paddle.mean(iou) | |
| return iou | |