718c41634f
1.项目后端整体迁移至PaddleOCR-NCNN算法，已通过基本的兼容性测试 2.工程改为使用CMake组织，后续为了更好地兼容第三方库，不再提供QMake工程 3.重整权利声明文件，重整代码工程，确保最小化侵权风险 Log: 切换后端至PaddleOCR-NCNN，切换工程为CMake Change-Id: I4d5d2c5d37505a4a24b389b1a4c5d12f17bfa38c
118 lines
3.2 KiB
C++
118 lines
3.2 KiB
C++
// Tencent is pleased to support the open source community by making ncnn available.
|
|
//
|
|
// Copyright (C) 2020 THL A29 Limited, a Tencent company. All rights reserved.
|
|
//
|
|
// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
|
|
// in compliance with the License. You may obtain a copy of the License at
|
|
//
|
|
// https://opensource.org/licenses/BSD-3-Clause
|
|
//
|
|
// 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 "layer/priorbox.h"
|
|
#include "testutil.h"
|
|
|
|
static int test_priorbox_caffe()
|
|
{
|
|
ncnn::Mat min_sizes(1);
|
|
min_sizes[0] = 105.f;
|
|
|
|
ncnn::Mat max_sizes(1);
|
|
max_sizes[0] = 150.f;
|
|
|
|
ncnn::Mat aspect_ratios(2);
|
|
aspect_ratios[0] = 2.f;
|
|
aspect_ratios[1] = 3.f;
|
|
|
|
ncnn::ParamDict pd;
|
|
pd.set(0, min_sizes);
|
|
pd.set(1, max_sizes);
|
|
pd.set(2, aspect_ratios);
|
|
pd.set(3, 0.1f); // variances[0]
|
|
pd.set(4, 0.1f); // variances[1]
|
|
pd.set(5, 0.2f); // variances[2]
|
|
pd.set(6, 0.2f); // variances[3]
|
|
pd.set(7, 1); // flip
|
|
pd.set(8, 0); // clip
|
|
pd.set(9, -233); // image_width
|
|
pd.set(10, -233); // image_height
|
|
pd.set(11, -233.f); // step_width
|
|
pd.set(12, -233.f); // step_height
|
|
pd.set(13, 0.f); // offset
|
|
pd.set(14, 0.f); // step_mmdetection
|
|
pd.set(15, 0.f); // center_mmdetection
|
|
|
|
std::vector<ncnn::Mat> weights(0);
|
|
|
|
std::vector<ncnn::Mat> as(2);
|
|
as[0] = RandomMat(72, 72, 1);
|
|
as[1] = RandomMat(512, 512, 1);
|
|
|
|
int ret = test_layer<ncnn::PriorBox>("PriorBox", pd, weights, as, 1);
|
|
if (ret != 0)
|
|
{
|
|
fprintf(stderr, "test_priorbox_caffe failed\n");
|
|
}
|
|
|
|
return ret;
|
|
}
|
|
|
|
static int test_priorbox_mxnet()
|
|
{
|
|
ncnn::Mat min_sizes(2);
|
|
min_sizes[0] = 0.15f;
|
|
min_sizes[1] = 0.2121f;
|
|
|
|
ncnn::Mat max_sizes(0);
|
|
|
|
ncnn::Mat aspect_ratios(5);
|
|
aspect_ratios[0] = 1.f;
|
|
aspect_ratios[1] = 2.f;
|
|
aspect_ratios[2] = 0.5f;
|
|
aspect_ratios[3] = 3.f;
|
|
aspect_ratios[4] = 0.333333;
|
|
|
|
ncnn::ParamDict pd;
|
|
pd.set(0, min_sizes);
|
|
pd.set(1, max_sizes);
|
|
pd.set(2, aspect_ratios);
|
|
pd.set(3, 0.1f); // variances[0]
|
|
pd.set(4, 0.1f); // variances[1]
|
|
pd.set(5, 0.2f); // variances[2]
|
|
pd.set(6, 0.2f); // variances[3]
|
|
pd.set(7, 0); // flip
|
|
pd.set(8, 0); // clip
|
|
pd.set(9, -233); // image_width
|
|
pd.set(10, -233); // image_height
|
|
pd.set(11, -233.f); // step_width
|
|
pd.set(12, -233.f); // step_height
|
|
pd.set(13, 0.5f); // offset
|
|
pd.set(14, 0.f); // step_mmdetection
|
|
pd.set(15, 0.f); // center_mmdetection
|
|
|
|
std::vector<ncnn::Mat> weights(0);
|
|
|
|
std::vector<ncnn::Mat> as(1);
|
|
as[0] = RandomMat(72, 72, 1);
|
|
|
|
int ret = test_layer<ncnn::PriorBox>("PriorBox", pd, weights, as, 1);
|
|
if (ret != 0)
|
|
{
|
|
fprintf(stderr, "test_priorbox_mxnet failed\n");
|
|
}
|
|
|
|
return ret;
|
|
}
|
|
|
|
int main()
|
|
{
|
|
SRAND(7767517);
|
|
|
|
return 0
|
|
|| test_priorbox_caffe()
|
|
|| test_priorbox_mxnet();
|
|
}
|