From dfa753c6b4a6466b4b80f8b3184063131c93fc6d Mon Sep 17 00:00:00 2001 From: Liubov Batanina Date: Tue, 14 May 2019 12:35:41 +0300 Subject: [PATCH] Support OCV backend --- modules/dnn/src/layers/batch_norm_layer.cpp | 22 +++++++++++---------- modules/dnn/test/test_onnx_importer.cpp | 4 ++-- modules/dnn/test/test_tf_importer.cpp | 4 ++-- 3 files changed, 16 insertions(+), 14 deletions(-) diff --git a/modules/dnn/src/layers/batch_norm_layer.cpp b/modules/dnn/src/layers/batch_norm_layer.cpp index 6c1fc6ef29..b2fd75aef1 100644 --- a/modules/dnn/src/layers/batch_norm_layer.cpp +++ b/modules/dnn/src/layers/batch_norm_layer.cpp @@ -153,7 +153,7 @@ public: virtual bool supportBackend(int backendId) CV_OVERRIDE { - return (backendId == DNN_BACKEND_OPENCV && (dims == 4 || dims == 2)) || + return (backendId == DNN_BACKEND_OPENCV) || (backendId == DNN_BACKEND_HALIDE && haveHalide()) || (backendId == DNN_BACKEND_INFERENCE_ENGINE && haveInfEngine() && (preferableTarget == DNN_TARGET_CPU || dims == 4)); } @@ -181,11 +181,12 @@ public: } UMat &inpBlob = inputs[0]; - CV_Assert(inpBlob.dims == 2 || inpBlob.dims == 4); int groups = inpBlob.size[0]; int channels = inpBlob.size[1]; - int rows = inpBlob.dims > 2 ? inpBlob.size[2] : 1; - int cols = inpBlob.dims > 2 ? inpBlob.size[3] : 1; + int planeSize = 1; + for (size_t i = 2; i < inpBlob.dims; i++) { + planeSize *= inpBlob.size[i]; + } String opts = (use_half) ? " -DDtype=half" : " -DDtype=float"; for (size_t ii = 0; ii < outputs.size(); ii++) @@ -199,7 +200,7 @@ public: } else { - MatShape s = shape(groups * channels, rows * cols); + MatShape s = shape(groups * channels, planeSize); UMat src = inputs[ii].reshape(1, s.size(), &s[0]); UMat dst = outputs[ii].reshape(1, s.size(), &s[0]); int number = (s[1] % 8 == 0) ? 8 : ((s[1] % 4 == 0) ? 4 : 1); @@ -251,9 +252,10 @@ public: CV_Assert(inputs.size() == 1); Mat &inpBlob = inputs[0]; - CV_Assert(inpBlob.dims == 2 || inpBlob.dims == 4); - int rows = inpBlob.dims > 2 ? inpBlob.size[2] : 1; - int cols = inpBlob.dims > 2 ? inpBlob.size[3] : 1; + int planeSize = 1; + for (size_t i = 2; i < inpBlob.dims; i++) { + planeSize *= inpBlob.size[i]; + } for (size_t ii = 0; ii < outputs.size(); ii++) { @@ -265,8 +267,8 @@ public: { float w = weights_.at(n); float b = bias_.at(n); - Mat inpBlobPlane(rows, cols, CV_32F, inpBlob.ptr(num, n)); - Mat outBlobPlane(rows, cols, CV_32F, outBlob.ptr(num, n)); + Mat inpBlobPlane(1, planeSize, CV_32F, inpBlob.ptr(num, n)); + Mat outBlobPlane(1, planeSize, CV_32F, outBlob.ptr(num, n)); inpBlobPlane.convertTo(outBlobPlane, CV_32F, w, b); } } diff --git a/modules/dnn/test/test_onnx_importer.cpp b/modules/dnn/test/test_onnx_importer.cpp index 10402a3dda..bf9f25d214 100644 --- a/modules/dnn/test/test_onnx_importer.cpp +++ b/modules/dnn/test/test_onnx_importer.cpp @@ -169,8 +169,8 @@ TEST_P(Test_ONNX_layers, BatchNormalization) TEST_P(Test_ONNX_layers, BatchNormalization3D) { - if (backend != DNN_BACKEND_INFERENCE_ENGINE || target != DNN_TARGET_CPU) - throw SkipTestException("Only DLIE backend on CPU is supported"); + if (backend == DNN_BACKEND_INFERENCE_ENGINE && target != DNN_TARGET_CPU) + throw SkipTestException(""); testONNXModels("batch_norm_3d"); } diff --git a/modules/dnn/test/test_tf_importer.cpp b/modules/dnn/test/test_tf_importer.cpp index 64a56ee94f..2c7ae44783 100644 --- a/modules/dnn/test/test_tf_importer.cpp +++ b/modules/dnn/test/test_tf_importer.cpp @@ -190,8 +190,8 @@ TEST_P(Test_TensorFlow_layers, batch_norm) TEST_P(Test_TensorFlow_layers, batch_norm3D) { - if (backend != DNN_BACKEND_INFERENCE_ENGINE || target != DNN_TARGET_CPU) - throw SkipTestException("Only DLIE backend on CPU is supported"); + if (backend == DNN_BACKEND_INFERENCE_ENGINE && target != DNN_TARGET_CPU) + throw SkipTestException(""); runTensorFlowNet("batch_norm3d"); }