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Intel Inference Engine deep learning backend (#10608)

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* Intel Inference Engine deep learning backend.

* OpenFace network using Inference Engine backend
This commit is contained in:
Dmitry Kurtaev
2018-02-06 11:57:35 +03:00
committed by Vadim Pisarevsky
parent 292dfc2d72
commit 10e1de74d2
26 changed files with 1379 additions and 49 deletions
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modules/dnn/test/test_backends.cpp
+36 -2
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@@ -14,7 +14,7 @@ using namespace cv;
using namespace dnn;
using namespace testing;
CV_ENUM(DNNBackend, DNN_BACKEND_DEFAULT, DNN_BACKEND_HALIDE)
CV_ENUM(DNNBackend, DNN_BACKEND_DEFAULT, DNN_BACKEND_HALIDE, DNN_BACKEND_INFERENCE_ENGINE)
CV_ENUM(DNNTarget, DNN_TARGET_CPU, DNN_TARGET_OPENCL)
static void loadNet(const std::string& weights, const std::string& proto,
@@ -151,6 +151,7 @@ TEST_P(DNNTestNetwork, GoogLeNet)
TEST_P(DNNTestNetwork, Inception_5h)
{
if (backend == DNN_BACKEND_INFERENCE_ENGINE) throw SkipTestException("");
processNet("dnn/tensorflow_inception_graph.pb", "", Size(224, 224), "softmax2", "tensorflow",
target == DNN_TARGET_OPENCL ? "dnn/halide_scheduler_opencl_inception_5h.yml" :
"dnn/halide_scheduler_inception_5h.yml");
@@ -158,6 +159,7 @@ TEST_P(DNNTestNetwork, Inception_5h)
TEST_P(DNNTestNetwork, ENet)
{
if (backend == DNN_BACKEND_INFERENCE_ENGINE) throw SkipTestException("");
processNet("dnn/Enet-model-best.net", "", Size(512, 512), "l367_Deconvolution", "torch",
target == DNN_TARGET_OPENCL ? "dnn/halide_scheduler_opencl_enet.yml" :
"dnn/halide_scheduler_enet.yml",
@@ -176,16 +178,48 @@ TEST_P(DNNTestNetwork, MobileNetSSD)
TEST_P(DNNTestNetwork, SSD_VGG16)
{
if (backend == DNN_BACKEND_DEFAULT && target == DNN_TARGET_OPENCL ||
backend == DNN_BACKEND_HALIDE && target == DNN_TARGET_CPU)
backend == DNN_BACKEND_HALIDE && target == DNN_TARGET_CPU ||
backend == DNN_BACKEND_INFERENCE_ENGINE)
throw SkipTestException("");
processNet("dnn/VGG_ILSVRC2016_SSD_300x300_iter_440000.caffemodel",
"dnn/ssd_vgg16.prototxt", Size(300, 300), "detection_out", "caffe");
}
TEST_P(DNNTestNetwork, OpenPose_pose_coco)
{
if (backend == DNN_BACKEND_HALIDE) throw SkipTestException("");
processNet("dnn/openpose_pose_coco.caffemodel", "dnn/openpose_pose_coco.prototxt",
Size(368, 368), "", "caffe");
}
TEST_P(DNNTestNetwork, OpenPose_pose_mpi)
{
if (backend == DNN_BACKEND_HALIDE) throw SkipTestException("");
processNet("dnn/openpose_pose_mpi.caffemodel", "dnn/openpose_pose_mpi.prototxt",
Size(368, 368), "", "caffe");
}
TEST_P(DNNTestNetwork, OpenPose_pose_mpi_faster_4_stages)
{
if (backend == DNN_BACKEND_HALIDE) throw SkipTestException("");
// The same .caffemodel but modified .prototxt
// See https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/src/openpose/pose/poseParameters.cpp
processNet("dnn/openpose_pose_mpi.caffemodel", "dnn/openpose_pose_mpi_faster_4_stages.prototxt",
Size(368, 368), "", "caffe");
}
TEST_P(DNNTestNetwork, OpenFace)
{
processNet("dnn/openface_nn4.small2.v1.t7", "", Size(96, 96), "", "torch");
}
const tuple<DNNBackend, DNNTarget> testCases[] = {
#ifdef HAVE_HALIDE
tuple<DNNBackend, DNNTarget>(DNN_BACKEND_HALIDE, DNN_TARGET_CPU),
tuple<DNNBackend, DNNTarget>(DNN_BACKEND_HALIDE, DNN_TARGET_OPENCL),
#endif
#ifdef HAVE_INF_ENGINE
tuple<DNNBackend, DNNTarget>(DNN_BACKEND_INFERENCE_ENGINE, DNN_TARGET_CPU),
#endif
tuple<DNNBackend, DNNTarget>(DNN_BACKEND_DEFAULT, DNN_TARGET_OPENCL)
};