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Merge pull request #10854 from pengli:dnn

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This commit is contained in:
Alexander Alekhin 2018-02-14 12:49:53 +00:00
commit cff79609c8
6 changed files with 50 additions and 16 deletions
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7
modules/dnn/src/layers/convolution_layer.cpp
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@ -824,6 +824,13 @@ public:
for (int i = 0; i < inputs.size(); ++i)
CV_Assert(inputs[i].u != outputs[0].u);
int inpH = inputs[0].size[2];
int inpW = inputs[0].size[3];
int out_h = (inpH + 2 * pad.height - (dilation.height * (kernel.height - 1) + 1)) / stride.height + 1;
int out_w = (inpW + 2 * pad.width - (dilation.width * (kernel.width - 1) + 1)) / stride.width + 1;
if (out_h != outputs[0].size[2] || out_w != outputs[0].size[3])
return false;
int group = inputs[0].size[1] / umat_blobs[0].size[1];
if (convolutionOp.empty())

3
modules/dnn/src/layers/detection_output_layer.cpp
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@ -249,7 +249,8 @@ public:
kernel.set(6, (int)num_loc_classes);
kernel.set(7, (int)background_label_id);
kernel.set(8, (int)clip);
kernel.set(9, ocl::KernelArg::PtrWriteOnly(outmat));
kernel.set(9, (int)_locPredTransposed);
kernel.set(10, ocl::KernelArg::PtrWriteOnly(outmat));
if (!kernel.run(1, &nthreads, NULL, false))
return false;

12
modules/dnn/src/layers/prior_box_layer.cpp
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@ -317,7 +317,17 @@ public:
variance.copyTo(umat_variance);
int real_numPriors = _numPriors >> (_offsetsX.size() - 1);
umat_scales = UMat(1, &real_numPriors, CV_32F, 1.0f);
if (_scales.empty())
{
_scales.resize(real_numPriors, 1.0f);
umat_scales = UMat(1, &real_numPriors, CV_32F, 1.0f);
}
else
{
CV_Assert(_scales.size() == real_numPriors);
Mat scales(1, _scales.size(), CV_32FC1, &_scales[0]);
scales.copyTo(umat_scales);
}
}
size_t nthreads = _layerHeight * _layerWidth;

34
modules/dnn/src/opencl/detection_output.cl
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@ -51,6 +51,7 @@ __kernel void DecodeBBoxesCORNER(const int nthreads,
const int num_loc_classes,
const int background_label_id,
const int clip_bbox,
const int locPredTransposed,
__global Dtype* bbox_data)
{
for (int index = get_global_id(0); index < nthreads; index += get_global_size(0))
@ -75,10 +76,18 @@ __kernel void DecodeBBoxesCORNER(const int nthreads,
bbox_vec = loc_vec * prior_variance;
}
bbox_xmin = bbox_vec.x;
bbox_ymin = bbox_vec.y;
bbox_xmax = bbox_vec.z;
bbox_ymax = bbox_vec.w;
if (locPredTransposed)
{
bbox_ymin = bbox_vec.x;
bbox_xmin = bbox_vec.y;
bbox_ymax = bbox_vec.z;
bbox_xmax = bbox_vec.w;
} else {
bbox_xmin = bbox_vec.x;
bbox_ymin = bbox_vec.y;
bbox_xmax = bbox_vec.z;
bbox_ymax = bbox_vec.w;
}
Dtype4 prior_vec = vload4(0, prior_data + p);
Dtype val;
@ -114,6 +123,7 @@ __kernel void DecodeBBoxesCENTER_SIZE(const int nthreads,
const int num_loc_classes,
const int background_label_id,
const int clip_bbox,
const int locPredTransposed,
__global Dtype* bbox_data)
{
for (int index = get_global_id(0); index < nthreads; index += get_global_size(0))
@ -138,10 +148,18 @@ __kernel void DecodeBBoxesCENTER_SIZE(const int nthreads,
bbox_vec = loc_vec * prior_variance;
}
bbox_xmin = bbox_vec.x;
bbox_ymin = bbox_vec.y;
bbox_xmax = bbox_vec.z;
bbox_ymax = bbox_vec.w;
if (locPredTransposed)
{
bbox_ymin = bbox_vec.x;
bbox_xmin = bbox_vec.y;
bbox_ymax = bbox_vec.z;
bbox_xmax = bbox_vec.w;
} else {
bbox_xmin = bbox_vec.x;
bbox_ymin = bbox_vec.y;
bbox_xmax = bbox_vec.z;
bbox_ymax = bbox_vec.w;
}
Dtype4 prior_vec = vload4(0, prior_data + p);
Dtype prior_width = prior_vec.z - prior_vec.x;

4
modules/dnn/test/test_backends.cpp
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@ -174,9 +174,7 @@ TEST_P(DNNTestNetwork, MobileNet_SSD_Caffe)
TEST_P(DNNTestNetwork, MobileNet_SSD_TensorFlow)
{
if (backend == DNN_BACKEND_DEFAULT && target == DNN_TARGET_OPENCL ||
backend == DNN_BACKEND_HALIDE)
throw SkipTestException("");
if (backend == DNN_BACKEND_HALIDE) throw SkipTestException("");
Mat sample = imread(findDataFile("dnn/street.png", false));
Mat inp = blobFromImage(sample, 1.0f / 127.5, Size(300, 300), Scalar(127.5, 127.5, 127.5), false);
processNet("dnn/ssd_mobilenet_v1_coco.pb", "dnn/ssd_mobilenet_v1_coco.pbtxt",

6
modules/dnn/test/test_tf_importer.cpp
View File

@ -285,7 +285,7 @@ TEST(Test_TensorFlow, Inception_v2_SSD)
normAssert(detections, ref);
}
OCL_TEST(Test_TensorFlow, DISABLED_MobileNet_SSD)
OCL_TEST(Test_TensorFlow, MobileNet_SSD)
{
std::string netPath = findDataFile("dnn/ssd_mobilenet_v1_coco.pb", false);
std::string netConfig = findDataFile("dnn/ssd_mobilenet_v1_coco.pbtxt", false);
@ -317,8 +317,8 @@ OCL_TEST(Test_TensorFlow, DISABLED_MobileNet_SSD)
std::vector<Mat> output;
net.forward(output, outNames);
normAssert(target[0].reshape(1, 1), output[0].reshape(1, 1));
normAssert(target[1].reshape(1, 1), output[1].reshape(1, 1), "", 1e-5, 2e-4);
normAssert(target[0].reshape(1, 1), output[0].reshape(1, 1), "", 1e-5, 1.5e-4);
normAssert(target[1].reshape(1, 1), output[1].reshape(1, 1), "", 1e-5, 3e-4);
normAssert(target[2].reshape(1, 1), output[2].reshape(1, 1), "", 4e-5, 1e-2);
}