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Merge pull request #21910 from zihaomu:fast_conv_ARM

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DNN: Accelerating convolution

* Fast Conv of ARM, X86 and universal intrinsics.

* improve code style.

* error fixed.

* improve the License

* optimize memory allocated and Adjust the threshold.

* change FasterRCNN_vgg16 to 2GB memory.
This commit is contained in:
Zihao Mu
2022-07-01 18:03:15 +08:00
committed by GitHub
parent b91f173680
commit 59b870a87a
11 changed files with 3286 additions and 12 deletions
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modules/dnn/test/test_int8_layers.cpp
+7 -7
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@@ -696,7 +696,7 @@ TEST_P(Test_Int8_nets, GoogLeNet)
Mat blob = blobFromImages(inpMats, 1.0, Size(224, 224), Scalar(), false);
Mat ref = blobFromNPY(_tf("googlenet_prob.npy"));
float l1 = 2e-4, lInf = 0.06;
float l1 = 2e-4, lInf = 0.07;
testClassificationNet(net, blob, ref, l1, lInf);
}
@@ -718,7 +718,7 @@ TEST_P(Test_Int8_nets, ResNet50)
Mat blob = blobFromImage(inp, 1.0, Size(224, 224), Scalar(), false);
Mat ref = blobFromNPY(_tf("resnet50_prob.npy"));
float l1 = 3e-4, lInf = 0.04;
float l1 = 3e-4, lInf = 0.05;
testClassificationNet(net, blob, ref, l1, lInf);
}
@@ -952,7 +952,7 @@ TEST_P(Test_Int8_nets, EfficientDet)
0, 17, 0.8245924, 0.16657517850399017, 0.3996818959712982, 0.4111558794975281, 0.9306337833404541,
0, 7, 0.8039304, 0.6118435263633728, 0.13175517320632935, 0.9065558314323425, 0.2943994700908661);
float confThreshold = 0.65, scoreDiff = 0.17, iouDiff = 0.18;
float confThreshold = 0.65, scoreDiff = 0.3, iouDiff = 0.18;
testDetectionNet(net, blob, ref, confThreshold, scoreDiff, iouDiff);
}
@@ -1016,7 +1016,7 @@ TEST_P(Test_Int8_nets, FasterRCNN_vgg16)
#if defined(OPENCV_32BIT_CONFIGURATION) && defined(HAVE_OPENCL)
CV_TEST_TAG_MEMORY_2GB,
#else
(target == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_1GB : CV_TEST_TAG_MEMORY_2GB),
CV_TEST_TAG_MEMORY_2GB,
#endif
CV_TEST_TAG_LONG,
CV_TEST_TAG_DEBUG_VERYLONG
@@ -1034,7 +1034,7 @@ TEST_P(Test_Int8_nets, FasterRCNN_vgg16)
0, 7, 0.997022, 481.841, 92.3218, 722.685, 175.953,
0, 12, 0.993028, 133.221, 189.377, 350.994, 563.166);
float confThreshold = 0.8, scoreDiff = 0.024, iouDiff = 0.35;
float confThreshold = 0.8, scoreDiff = 0.048, iouDiff = 0.35;
testFaster(net, ref, confThreshold, scoreDiff, iouDiff);
}
@@ -1084,7 +1084,7 @@ TEST_P(Test_Int8_nets, RFCN)
Mat ref = (Mat_<float>(2, 7) << 0, 7, 0.991359, 491.822, 81.1668, 702.573, 178.234,
0, 12, 0.94786, 132.093, 223.903, 338.077, 566.16);
float confThreshold = 0.8, scoreDiff = 0.017, iouDiff = 0.11;
float confThreshold = 0.8, scoreDiff = 0.15, iouDiff = 0.11;
testFaster(net, ref, confThreshold, scoreDiff, iouDiff);
}
@@ -1114,7 +1114,7 @@ TEST_P(Test_Int8_nets, YoloVoc)
std::string config_file = "yolo-voc.cfg";
std::string weights_file = "yolo-voc.weights";
double scoreDiff = 0.1, iouDiff = 0.3;
double scoreDiff = 0.12, iouDiff = 0.3;
{
SCOPED_TRACE("batch size 1");
testDarknetModel(config_file, weights_file, ref.rowRange(0, 3), scoreDiff, iouDiff);