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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,96 @@ | ||
| /* Copyright (c) 2016 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. */ | ||
|
|
||
| #include "paddle/operators/iou_similarity_op.h" | ||
|
|
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| namespace paddle { | ||
| namespace operators { | ||
|
|
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| class IOUSimilarityOp : public framework::OperatorWithKernel { | ||
| public: | ||
| using framework::OperatorWithKernel::OperatorWithKernel; | ||
|
|
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| protected: | ||
| void InferShape(framework::InferShapeContext *ctx) const override { | ||
| PADDLE_ENFORCE(ctx->HasInput("X"), | ||
| "Input(X) of IOUSimilarityOp should not be null."); | ||
| PADDLE_ENFORCE(ctx->HasInput("Y"), | ||
| "Input(Y) of IOUSimilarityOp should not be null."); | ||
| auto x_dims = ctx->GetInputDim("X"); | ||
| 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."); | ||
| PADDLE_ENFORCE_EQ(x_dims[1], 4UL, "The shape of X is [N, 4]"); | ||
| PADDLE_ENFORCE_EQ(y_dims.size(), 2UL, "The rank of Input(Y) must be 2."); | ||
| PADDLE_ENFORCE_EQ(y_dims[1], 4UL, "The shape of Y is [M, 4]"); | ||
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| ctx->ShareLoD("X", /*->*/ "Out"); | ||
| ctx->SetOutputDim("Out", framework::make_ddim({x_dims[0], y_dims[0]})); | ||
| } | ||
| }; | ||
|
|
||
| class IOUSimilarityOpMaker : public framework::OpProtoAndCheckerMaker { | ||
| public: | ||
| IOUSimilarityOpMaker(OpProto *proto, OpAttrChecker *op_checker) | ||
| : OpProtoAndCheckerMaker(proto, op_checker) { | ||
| AddInput("X", | ||
| "(LoDTensor, default LoDTensor<float>) " | ||
| "Box list X is a 2-D LoDTensor with shape [N, 4] holds N boxes, " | ||
| "each box is represented as [xmin, ymin, xmax, ymax], " | ||
| "the shape of X is [N, 4]. [xmin, ymin] is the left top " | ||
| "coordinate of the box if the input is image feature map, they " | ||
| "are close to the origin of the coordinate system. " | ||
| "[xmax, ymax] is the right bottom coordinate of the box. " | ||
| "This tensor can contain LoD information to represent a batch " | ||
| "of inputs. One instance of this batch can contain different " | ||
| "numbers of entities."); | ||
| AddInput("Y", | ||
| "(Tensor, default Tensor<float>) " | ||
| "Box list Y holds M boxes, each box is represented as " | ||
| "[xmin, ymin, xmax, ymax], the shape of X is [N, 4]. " | ||
| "[xmin, ymin] is the left top coordinate of the box if the " | ||
| "input is image feature map, and [xmax, ymax] is the right " | ||
| "bottom coordinate of the box."); | ||
|
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| AddOutput("Out", | ||
| "(LoDTensor, the lod is same as input X) The output of " | ||
| "iou_similarity op, a tensor with shape [N, M] " | ||
| "representing pairwise iou scores."); | ||
|
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| AddComment(R"DOC( | ||
| IOU Similarity Operator. | ||
| Computes intersection-over-union (IOU) between two box lists. | ||
| Box list 'X' should be a LoDTensor and 'Y' is a common Tensor, | ||
| boxes in 'Y' are shared by all instance of the batched inputs of X. | ||
| Given two boxes A and B, the calculation of IOU is as follows: | ||
| $$ | ||
| IOU(A, B) = | ||
| \frac{area(A\cap B)}{area(A)+area(B)-area(A\cap B)} | ||
| $$ | ||
| )DOC"); | ||
| } | ||
| }; | ||
| } // namespace operators | ||
| } // namespace paddle | ||
|
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| namespace ops = paddle::operators; | ||
| REGISTER_OP_WITHOUT_GRADIENT(iou_similarity, ops::IOUSimilarityOp, | ||
| ops::IOUSimilarityOpMaker); | ||
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| REGISTER_OP_CPU_KERNEL( | ||
| iou_similarity, | ||
| ops::IOUSimilarityKernel<paddle::platform::CPUDeviceContext, float>, | ||
| ops::IOUSimilarityKernel<paddle::platform::CPUDeviceContext, double>); |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,21 @@ | ||
| /* Copyright (c) 2016 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. */ | ||
|
|
||
| #include "paddle/operators/iou_similarity_op.h" | ||
|
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| namespace ops = paddle::operators; | ||
| REGISTER_OP_CUDA_KERNEL( | ||
| iou_similarity, | ||
| ops::IOUSimilarityKernel<paddle::platform::CUDADeviceContext, float>, | ||
| ops::IOUSimilarityKernel<paddle::platform::CUDADeviceContext, double>); |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,90 @@ | ||
| /* Copyright (c) 2016 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. */ | ||
|
|
||
| #pragma once | ||
| #include "paddle/framework/op_registry.h" | ||
| #include "paddle/platform/for_range.h" | ||
|
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| template <typename T> | ||
| inline HOSTDEVICE T IOUSimilarity(T xmin1, T ymin1, T xmax1, T ymax1, T xmin2, | ||
| T ymin2, T xmax2, T ymax2) { | ||
| constexpr T zero = static_cast<T>(0); | ||
| T area1 = (ymax1 - ymin1) * (xmax1 - xmin1); | ||
| T area2 = (ymax2 - ymin2) * (xmax2 - xmin2); | ||
| T inter_xmax = xmax1 > xmax2 ? xmax2 : xmax1; | ||
| T inter_ymax = ymax1 > ymax2 ? ymax2 : ymax1; | ||
| T inter_xmin = xmin1 > xmin2 ? xmin1 : xmin2; | ||
| T inter_ymin = ymin1 > ymin2 ? ymin1 : ymin2; | ||
| T inter_height = inter_ymax - inter_ymin; | ||
| T inter_width = inter_xmax - inter_xmin; | ||
| inter_height = inter_height > zero ? inter_height : zero; | ||
| inter_width = inter_width > zero ? inter_width : zero; | ||
| T inter_area = inter_width * inter_height; | ||
| T union_area = area1 + area2 - inter_area; | ||
| T sim_score = inter_area / union_area; | ||
| return sim_score; | ||
| } | ||
|
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| template <typename T> | ||
| struct IOUSimilarityFunctor { | ||
| IOUSimilarityFunctor(const T* x, const T* y, T* z, int cols) | ||
| : x_(x), y_(y), z_(z), cols_(static_cast<size_t>(cols)) {} | ||
|
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| inline HOSTDEVICE void operator()(size_t row_id) const { | ||
| T x_min1 = x_[row_id * 4]; | ||
| T y_min1 = x_[row_id * 4 + 1]; | ||
| T x_max1 = x_[row_id * 4 + 2]; | ||
| T y_max1 = x_[row_id * 4 + 3]; | ||
| for (size_t i = 0; i < cols_; ++i) { | ||
| T x_min2 = y_[i * 4]; | ||
| T y_min2 = y_[i * 4 + 1]; | ||
| T x_max2 = y_[i * 4 + 2]; | ||
| T y_max2 = y_[i * 4 + 3]; | ||
|
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| T sim = IOUSimilarity(x_min1, y_min1, x_max1, y_max1, x_min2, y_min2, | ||
| x_max2, y_max2); | ||
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| z_[row_id * cols_ + i] = sim; | ||
| } | ||
| } | ||
| const T* x_; | ||
| const T* y_; | ||
| T* z_; | ||
| const size_t cols_; | ||
| }; | ||
|
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| namespace paddle { | ||
| namespace operators { | ||
|
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| template <typename DeviceContext, typename T> | ||
| class IOUSimilarityKernel : public framework::OpKernel<T> { | ||
| public: | ||
| void Compute(const framework::ExecutionContext& ctx) const override { | ||
| const framework::LoDTensor* in_x = ctx.Input<framework::LoDTensor>("X"); | ||
| const framework::Tensor* in_y = ctx.Input<framework::Tensor>("Y"); | ||
| framework::LoDTensor* out = ctx.Output<framework::LoDTensor>("Out"); | ||
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| int x_n = in_x->dims()[0]; | ||
| int y_n = in_y->dims()[0]; | ||
| IOUSimilarityFunctor<T> functor(in_x->data<T>(), in_y->data<T>(), | ||
| out->mutable_data<T>(ctx.GetPlace()), y_n); | ||
|
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| platform::ForRange<DeviceContext> for_range( | ||
| static_cast<const DeviceContext&>(ctx.device_context()), x_n); | ||
| for_range(functor); | ||
| } | ||
| }; // namespace operators | ||
|
|
||
| } // namespace operators | ||
| } // namespace paddle |
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