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Merge remote-tracking branch 'upstream/3.4' into merge-3.4

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This commit is contained in:
Alexander Alekhin 2018-09-19 10:54:15 +03:00
commit 861415133e
10 changed files with 85 additions and 22 deletions
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7
modules/dnn/include/opencv2/dnn/dnn.hpp
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@ -937,6 +937,13 @@ CV__DNN_INLINE_NS_BEGIN
CV_OUT std::vector<int>& indices,
const float eta = 1.f, const int top_k = 0);
/** @brief Release a Myriad device is binded by OpenCV.
*
* Single Myriad device cannot be shared across multiple processes which uses
* Inference Engine's Myriad plugin.
*/
CV_EXPORTS_W void resetMyriadDevice();
//! @}
CV__DNN_INLINE_NS_END
}

13
modules/dnn/src/op_inf_engine.cpp
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@ -443,13 +443,14 @@ void InfEngineBackendNet::init(int targetId)
initPlugin(*this);
}
static std::map<InferenceEngine::TargetDevice, InferenceEngine::InferenceEnginePluginPtr> sharedPlugins;
void InfEngineBackendNet::initPlugin(InferenceEngine::ICNNNetwork& net)
{
CV_Assert(!isInitialized());
try
{
static std::map<InferenceEngine::TargetDevice, InferenceEngine::InferenceEnginePluginPtr> sharedPlugins;
auto pluginIt = sharedPlugins.find(targetDevice);
if (pluginIt != sharedPlugins.end())
{
@ -589,4 +590,14 @@ void forwardInfEngine(Ptr<BackendNode>& node)
#endif // HAVE_INF_ENGINE
}
CV__DNN_INLINE_NS_BEGIN
void resetMyriadDevice()
{
#ifdef HAVE_INF_ENGINE
sharedPlugins.erase(InferenceEngine::TargetDevice::eMYRIAD);
#endif // HAVE_INF_ENGINE
}
CV__DNN_INLINE_NS_END
}} // namespace dnn, namespace cv

11
modules/dnn/test/test_ie_models.cpp
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@ -177,6 +177,11 @@ TEST_P(DNNTestOpenVINO, models)
Target target = (dnn::Target)(int)get<0>(GetParam());
std::string modelName = get<1>(GetParam());
if (target == DNN_TARGET_MYRIAD && (modelName == "landmarks-regression-retail-0001" ||
modelName == "semantic-segmentation-adas-0001" ||
modelName == "face-reidentification-retail-0001"))
throw SkipTestException("");
std::string precision = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? "FP16" : "FP32";
std::string prefix = utils::fs::join("intel_models",
utils::fs::join(modelName,
@ -186,6 +191,8 @@ TEST_P(DNNTestOpenVINO, models)
std::map<std::string, cv::Mat> inputsMap;
std::map<std::string, cv::Mat> ieOutputsMap, cvOutputsMap;
// Single Myriad device cannot be shared across multiple processes.
resetMyriadDevice();
runIE(target, xmlPath, binPath, inputsMap, ieOutputsMap);
runCV(target, xmlPath, binPath, inputsMap, cvOutputsMap);
@ -238,8 +245,8 @@ static testing::internal::ParamGenerator<Target> dnnDLIETargets()
targets.push_back(DNN_TARGET_OPENCL_FP16);
}
#endif
//if (checkMyriadTarget())
// targets.push_back(DNN_TARGET_MYRIAD);
if (checkMyriadTarget())
targets.push_back(DNN_TARGET_MYRIAD);
return testing::ValuesIn(targets);
}

2
modules/ts/misc/run_android.py
View File

@ -123,7 +123,7 @@ class AndroidTestSuite(TestSuite):
def checkPrerequisites(self):
self.adb.init(self.options.serial)
def runTest(self, path, logfile, workingDir, args=[]):
def runTest(self, module, path, logfile, workingDir, args=[]):
args = args[:]
exe = os.path.abspath(path)

24
modules/ts/misc/run_long.py
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@ -7,6 +7,18 @@ from pprint import PrettyPrinter as PP
LONG_TESTS_DEBUG_VALGRIND = [
('calib3d', 'Calib3d_InitUndistortRectifyMap.accuracy', 2017.22),
('dnn', 'Reproducibility*', 1000), # large DNN models
('dnn', '*RCNN*', 1000), # very large DNN models
('dnn', '*RFCN*', 1000), # very large DNN models
('dnn', '*EAST*', 1000), # very large DNN models
('dnn', '*VGG16*', 1000), # very large DNN models
('dnn', '*ZFNet*', 1000), # very large DNN models
('dnn', '*ResNet101_DUC_HDC*', 1000), # very large DNN models
('dnn', '*LResNet100E_IR*', 1000), # very large DNN models
('dnn', '*read_yolo_voc_stream*', 1000), # very large DNN models
('dnn', '*eccv16*', 1000), # very large DNN models
('dnn', '*OpenPose*', 1000), # very large DNN models
('dnn', '*SSD/*', 1000), # very large DNN models
('face', 'CV_Face_FacemarkLBF.test_workflow', 10000.0), # >40min on i7
('features2d', 'Features2d/DescriptorImage.no_crash/3', 1000),
('features2d', 'Features2d/DescriptorImage.no_crash/4', 1000),
('features2d', 'Features2d/DescriptorImage.no_crash/5', 1000),
@ -29,6 +41,8 @@ LONG_TESTS_DEBUG_VALGRIND = [
('shape', 'Shape_SCD.regression', 3311.46),
('tracking', 'AUKF.br_mean_squared_error', 10764.6),
('tracking', 'UKF.br_mean_squared_error', 5228.27),
('tracking', '*DistanceAndOverlap*/1', 1000.0), # dudek
('tracking', '*DistanceAndOverlap*/2', 1000.0), # faceocc2
('videoio', 'Videoio_Video.ffmpeg_writebig', 1000),
('xfeatures2d', 'Features2d_RotationInvariance_Descriptor_BoostDesc_LBGM.regression', 1124.51),
('xfeatures2d', 'Features2d_RotationInvariance_Descriptor_VGG120.regression', 2198.1),
@ -41,17 +55,21 @@ LONG_TESTS_DEBUG_VALGRIND = [
('xfeatures2d', 'Features2d_ScaleInvariance_Descriptor_VGG64.regression', 1163.41),
('xfeatures2d', 'Features2d_ScaleInvariance_Descriptor_VGG80.regression', 1179.06),
('ximgproc', 'L0SmoothTest.SplatSurfaceAccuracy', 6382.26),
('ximgproc', 'L0SmoothTest_perf.perf/17', 2052.16),
('ximgproc', 'RollingGuidanceFilterTest_perf.perf/59', 2760.29),
('ximgproc', 'perf*/1*:perf*/2*:perf*/3*:perf*/4*:perf*/5*:perf*/6*:perf*/7*:perf*/8*:perf*/9*', 1000.0), # only first 10 parameters
('ximgproc', 'TypicalSet1/RollingGuidanceFilterTest.MultiThreadReproducibility/5', 1086.33),
('ximgproc', 'TypicalSet1/RollingGuidanceFilterTest.MultiThreadReproducibility/7', 1405.05),
('ximgproc', 'TypicalSet1/RollingGuidanceFilterTest.SplatSurfaceAccuracy/5', 1253.07),
('ximgproc', 'TypicalSet1/RollingGuidanceFilterTest.SplatSurfaceAccuracy/7', 1599.98),
('ximgproc', '*MultiThreadReproducibility*/1:*MultiThreadReproducibility*/2:*MultiThreadReproducibility*/3:*MultiThreadReproducibility*/4:*MultiThreadReproducibility*/5:*MultiThreadReproducibility*/6:*MultiThreadReproducibility*/7:*MultiThreadReproducibility*/8:*MultiThreadReproducibility*/9:*MultiThreadReproducibility*/1*', 1000.0),
('ximgproc', '*AdaptiveManifoldRefImplTest*/1:*AdaptiveManifoldRefImplTest*/2:*AdaptiveManifoldRefImplTest*/3', 1000.0),
('ximgproc', '*JointBilateralFilterTest_NaiveRef*', 1000.0),
('ximgproc', '*RollingGuidanceFilterTest_BilateralRef*/1*:*RollingGuidanceFilterTest_BilateralRef*/2*:*RollingGuidanceFilterTest_BilateralRef*/3*', 1000.0),
('ximgproc', '*JointBilateralFilterTest_NaiveRef*', 1000.0),
]
def longTestFilter(data, module=None):
res = ['*', '-'] + [v for _, v, m in data if module is None or m == module]
res = ['*', '-'] + [v for m, v, _time in data if module is None or m == module]
return '--gtest_filter={}'.format(':'.join(res))

14
modules/ts/misc/run_suite.py
View File

@ -77,7 +77,7 @@ class TestSuite(object):
return False
return os.access(fullpath, os.X_OK)
def wrapCommand(self, cmd, env):
def wrapCommand(self, module, cmd, env):
if self.options.valgrind:
res = ['valgrind']
supp = self.options.valgrind_supp or []
@ -88,7 +88,7 @@ class TestSuite(object):
print("WARNING: Valgrind suppression file is missing, SKIP: %s" % f)
res.extend(self.options.valgrind_opt)
has_gtest_filter = next((True for x in cmd if x.startswith('--gtest_filter=')), False)
return res + cmd + ([longTestFilter(LONG_TESTS_DEBUG_VALGRIND)] if not has_gtest_filter else [])
return res + cmd + ([longTestFilter(LONG_TESTS_DEBUG_VALGRIND, module)] if not has_gtest_filter else [])
elif self.options.qemu:
import shlex
res = shlex.split(self.options.qemu)
@ -107,14 +107,14 @@ class TestSuite(object):
pass
return False
def runTest(self, path, logfile, workingDir, args=[]):
def runTest(self, module, path, logfile, workingDir, args=[]):
args = args[:]
exe = os.path.abspath(path)
if path == "java":
if module == "java":
cmd = [self.cache.ant_executable, "-Dopencv.build.type=%s" % self.cache.build_type, "buildAndTest"]
ret = execute(cmd, cwd=self.cache.java_test_dir)
return None, ret
elif path in ['python2', 'python3']:
elif module in ['python2', 'python3']:
executable = os.getenv('OPENCV_PYTHON_BINARY', None)
if executable is None:
executable = path
@ -140,7 +140,7 @@ class TestSuite(object):
env['OPENCV_TRACE_SYNC_OPENCL'] = '1'
tempDir = TempEnvDir('OPENCV_TEMP_PATH', "__opencv_temp.")
tempDir.init()
cmd = self.wrapCommand([exe] + args, env)
cmd = self.wrapCommand(module, [exe] + args, env)
log.warning("Run: %s" % " ".join(cmd))
ret = execute(cmd, cwd=workingDir, env=env)
try:
@ -184,7 +184,7 @@ class TestSuite(object):
if self.options.dry_run:
logfile, r = None, 0
else:
logfile, r = self.runTest(exe, logname, workingDir, args + more_args)
logfile, r = self.runTest(test, exe, logname, workingDir, args + more_args)
log.debug("Test returned: %s ==> %s", r, logfile)
if r != 0:

23
samples/dnn/tf_text_graph_common.py
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@ -302,3 +302,26 @@ def removeUnusedNodesAndAttrs(to_remove, graph_def):
for i in reversed(range(len(node.input))):
if node.input[i] in removedNodes:
del node.input[i]
def writeTextGraph(modelPath, outputPath, outNodes):
try:
import cv2 as cv
cv.dnn.writeTextGraph(modelPath, outputPath)
except:
import tensorflow as tf
from tensorflow.tools.graph_transforms import TransformGraph
with tf.gfile.FastGFile(modelPath, 'rb') as f:
graph_def = tf.GraphDef()
graph_def.ParseFromString(f.read())
graph_def = TransformGraph(graph_def, ['image_tensor'], outNodes, ['sort_by_execution_order'])
for node in graph_def.node:
if node.op == 'Const':
if 'value' in node.attr:
del node.attr['value']
tf.train.write_graph(graph_def, "", outputPath, as_text=True)

3
samples/dnn/tf_text_graph_faster_rcnn.py
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@ -1,6 +1,5 @@
import argparse
import numpy as np
import cv2 as cv
from tf_text_graph_common import *
@ -42,7 +41,7 @@ def createFasterRCNNGraph(modelPath, configPath, outputPath):
print('Features stride: %f' % features_stride)
# Read the graph.
cv.dnn.writeTextGraph(modelPath, outputPath)
writeTextGraph(modelPath, outputPath, ['num_detections', 'detection_scores', 'detection_boxes', 'detection_classes'])
graph_def = parseTextGraph(outputPath)
removeIdentity(graph_def)

3
samples/dnn/tf_text_graph_mask_rcnn.py
View File

@ -1,6 +1,5 @@
import argparse
import numpy as np
import cv2 as cv
from tf_text_graph_common import *
parser = argparse.ArgumentParser(description='Run this script to get a text graph of '
@ -48,7 +47,7 @@ print('Height stride: %f' % height_stride)
print('Features stride: %f' % features_stride)
# Read the graph.
cv.dnn.writeTextGraph(args.input, args.output)
writeTextGraph(args.input, args.output, ['num_detections', 'detection_scores', 'detection_boxes', 'detection_classes', 'detection_masks'])
graph_def = parseTextGraph(args.output)
removeIdentity(graph_def)

7
samples/dnn/tf_text_graph_ssd.py
View File

@ -11,7 +11,6 @@
# See details and examples on the following wiki page: https://github.com/opencv/opencv/wiki/TensorFlow-Object-Detection-API
import argparse
from math import sqrt
import cv2 as cv
from tf_text_graph_common import *
def createSSDGraph(modelPath, configPath, outputPath):
@ -52,12 +51,12 @@ def createSSDGraph(modelPath, configPath, outputPath):
print('Input image size: %dx%d' % (image_width, image_height))
# Read the graph.
cv.dnn.writeTextGraph(modelPath, outputPath)
graph_def = parseTextGraph(outputPath)
inpNames = ['image_tensor']
outNames = ['num_detections', 'detection_scores', 'detection_boxes', 'detection_classes']
writeTextGraph(modelPath, outputPath, outNames)
graph_def = parseTextGraph(outputPath)
def getUnconnectedNodes():
unconnected = []
for node in graph_def.node: