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Merge pull request #9842 from alalek:fix_dnn_experimental

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This commit is contained in:
Alexander Alekhin 2017-10-13 15:25:06 +00:00
commit 827c7515c9
2 changed files with 14 additions and 14 deletions
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24
modules/dnn/src/darknet/darknet_io.cpp
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@ -103,14 +103,14 @@ namespace cv {
void setLayerBlobs(int i, std::vector<cv::Mat> blobs)
{
cv::dnn::experimental_dnn_v1::LayerParams &params = net->layers[i].layerParams;
cv::dnn::LayerParams &params = net->layers[i].layerParams;
params.blobs = blobs;
}
cv::dnn::experimental_dnn_v1::LayerParams getParamConvolution(int kernel, int pad,
cv::dnn::LayerParams getParamConvolution(int kernel, int pad,
int stride, int filters_num)
{
cv::dnn::experimental_dnn_v1::LayerParams params;
cv::dnn::LayerParams params;
params.name = "Convolution-name";
params.type = "Convolution";
@ -128,7 +128,7 @@ namespace cv {
void setConvolution(int kernel, int pad, int stride,
int filters_num, int channels_num, int use_batch_normalize, int use_relu)
{
cv::dnn::experimental_dnn_v1::LayerParams conv_param =
cv::dnn::LayerParams conv_param =
getParamConvolution(kernel, pad, stride, filters_num);
darknet::LayerParameter lp;
@ -148,7 +148,7 @@ namespace cv {
if (use_batch_normalize)
{
cv::dnn::experimental_dnn_v1::LayerParams bn_param;
cv::dnn::LayerParams bn_param;
bn_param.name = "BatchNorm-name";
bn_param.type = "BatchNorm";
@ -168,7 +168,7 @@ namespace cv {
if (use_relu)
{
cv::dnn::experimental_dnn_v1::LayerParams activation_param;
cv::dnn::LayerParams activation_param;
activation_param.set<float>("negative_slope", 0.1f);
activation_param.name = "ReLU-name";
activation_param.type = "ReLU";
@ -189,7 +189,7 @@ namespace cv {
void setMaxpool(size_t kernel, size_t pad, size_t stride)
{
cv::dnn::experimental_dnn_v1::LayerParams maxpool_param;
cv::dnn::LayerParams maxpool_param;
maxpool_param.set<cv::String>("pool", "max");
maxpool_param.set<int>("kernel_size", kernel);
maxpool_param.set<int>("pad", pad);
@ -212,7 +212,7 @@ namespace cv {
void setConcat(int number_of_inputs, int *input_indexes)
{
cv::dnn::experimental_dnn_v1::LayerParams concat_param;
cv::dnn::LayerParams concat_param;
concat_param.name = "Concat-name";
concat_param.type = "Concat";
concat_param.set<int>("axis", 1); // channels are in axis = 1
@ -235,7 +235,7 @@ namespace cv {
void setIdentity(int bottom_index)
{
cv::dnn::experimental_dnn_v1::LayerParams identity_param;
cv::dnn::LayerParams identity_param;
identity_param.name = "Identity-name";
identity_param.type = "Identity";
@ -256,7 +256,7 @@ namespace cv {
void setReorg(int stride)
{
cv::dnn::experimental_dnn_v1::LayerParams reorg_params;
cv::dnn::LayerParams reorg_params;
reorg_params.name = "Reorg-name";
reorg_params.type = "Reorg";
reorg_params.set<int>("reorg_stride", stride);
@ -277,7 +277,7 @@ namespace cv {
void setPermute()
{
cv::dnn::experimental_dnn_v1::LayerParams permute_params;
cv::dnn::LayerParams permute_params;
permute_params.name = "Permute-name";
permute_params.type = "Permute";
int permute[] = { 0, 2, 3, 1 };
@ -300,7 +300,7 @@ namespace cv {
void setRegion(float thresh, int coords, int classes, int anchors, int classfix, int softmax, int softmax_tree, float *biasData)
{
cv::dnn::experimental_dnn_v1::LayerParams region_param;
cv::dnn::LayerParams region_param;
region_param.name = "Region-name";
region_param.type = "Region";

4
modules/dnn/src/darknet/darknet_io.hpp
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@ -78,10 +78,10 @@ namespace cv {
class LayerParameter {
std::string layer_name, layer_type;
std::vector<std::string> bottom_indexes;
cv::dnn::experimental_dnn_v1::LayerParams layerParams;
cv::dnn::LayerParams layerParams;
public:
friend class setLayersParams;
cv::dnn::experimental_dnn_v1::LayerParams getLayerParams() const { return layerParams; }
cv::dnn::LayerParams getLayerParams() const { return layerParams; }
std::string name() const { return layer_name; }
std::string type() const { return layer_type; }
int bottom_size() const { return bottom_indexes.size(); }