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98 lines
3.8 KiB
98 lines
3.8 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include "paddle/fluid/operators/detection/iou_similarity_op.h"
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namespace paddle {
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namespace operators {
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class IOUSimilarityOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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protected:
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void InferShape(framework::InferShapeContext *ctx) const override {
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PADDLE_ENFORCE(ctx->HasInput("X"),
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"Input(X) of IOUSimilarityOp should not be null.");
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PADDLE_ENFORCE(ctx->HasInput("Y"),
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"Input(Y) of IOUSimilarityOp should not be null.");
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auto x_dims = ctx->GetInputDim("X");
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auto y_dims = ctx->GetInputDim("Y");
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PADDLE_ENFORCE_EQ(x_dims.size(), 2UL, "The rank of Input(X) must be 2.");
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PADDLE_ENFORCE_EQ(x_dims[1], 4UL, "The shape of X is [N, 4]");
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PADDLE_ENFORCE_EQ(y_dims.size(), 2UL, "The rank of Input(Y) must be 2.");
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PADDLE_ENFORCE_EQ(y_dims[1], 4UL, "The shape of Y is [M, 4]");
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ctx->ShareLoD("X", /*->*/ "Out");
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ctx->SetOutputDim("Out", framework::make_ddim({x_dims[0], y_dims[0]}));
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}
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};
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class IOUSimilarityOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("X",
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"(LoDTensor, default LoDTensor<float>) "
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"Box list X is a 2-D LoDTensor with shape [N, 4] holds N boxes, "
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"each box is represented as [xmin, ymin, xmax, ymax], "
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"the shape of X is [N, 4]. [xmin, ymin] is the left top "
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"coordinate of the box if the input is image feature map, they "
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"are close to the origin of the coordinate system. "
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"[xmax, ymax] is the right bottom coordinate of the box. "
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"This tensor can contain LoD information to represent a batch "
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"of inputs. One instance of this batch can contain different "
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"numbers of entities.");
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AddInput("Y",
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"(Tensor, default Tensor<float>) "
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"Box list Y holds M boxes, each box is represented as "
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"[xmin, ymin, xmax, ymax], the shape of X is [N, 4]. "
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"[xmin, ymin] is the left top coordinate of the box if the "
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"input is image feature map, and [xmax, ymax] is the right "
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"bottom coordinate of the box.");
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AddOutput("Out",
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"(LoDTensor, the lod is same as input X) The output of "
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"iou_similarity op, a tensor with shape [N, M] "
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"representing pairwise iou scores.");
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AddComment(R"DOC(
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**IOU Similarity Operator**
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Computes intersection-over-union (IOU) between two box lists.
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Box list 'X' should be a LoDTensor and 'Y' is a common Tensor,
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boxes in 'Y' are shared by all instance of the batched inputs of X.
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Given two boxes A and B, the calculation of IOU is as follows:
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$$
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IOU(A, B) =
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\\frac{area(A\\cap B)}{area(A)+area(B)-area(A\\cap B)}
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$$
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)DOC");
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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REGISTER_OPERATOR(iou_similarity, ops::IOUSimilarityOp,
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ops::IOUSimilarityOpMaker,
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paddle::framework::EmptyGradOpMaker);
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REGISTER_OP_CPU_KERNEL(
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iou_similarity,
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ops::IOUSimilarityKernel<paddle::platform::CPUDeviceContext, float>,
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ops::IOUSimilarityKernel<paddle::platform::CPUDeviceContext, double>);
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