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Merge pull request #17384 from dkurt:efficientdet

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Alexander Alekhin
2020-05-28 22:48:52 +00:00
parent 407cc5f1b6 d9bada9867
commit 319db07b6b
5 changed files with 302 additions and 8 deletions
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modules/dnn/test/test_tf_importer.cpp
+33
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@@ -1128,4 +1128,37 @@ TEST_P(Test_TensorFlow_nets, Mask_RCNN)
expectNoFallbacks(net);
}
TEST_P(Test_TensorFlow_nets, EfficientDet)
{
if (target != DNN_TARGET_CPU)
{
if (target == DNN_TARGET_OPENCL_FP16) applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL_FP16);
if (target == DNN_TARGET_OPENCL) applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL);
if (target == DNN_TARGET_MYRIAD) applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_MYRIAD);
}
checkBackend();
std::string proto = findDataFile("dnn/efficientdet-d0.pbtxt");
std::string model = findDataFile("dnn/efficientdet-d0.pb");
Net net = readNetFromTensorflow(model, proto);
Mat img = imread(findDataFile("dnn/dog416.png"));
Mat blob = blobFromImage(img, 1.0/255, Size(512, 512), Scalar(123.675, 116.28, 103.53));
net.setPreferableBackend(backend);
net.setPreferableTarget(target);
net.setInput(blob);
// Output has shape 1x1xNx7 where N - number of detections.
// An every detection is a vector of values [id, classId, confidence, left, top, right, bottom]
Mat out = net.forward();
// References are from test for TensorFlow model.
Mat ref = (Mat_<float>(3, 7) << 0, 1, 0.8437444, 0.153996080160141, 0.20534580945968628, 0.7463544607162476, 0.7414066195487976,
0, 17, 0.8245924, 0.16657517850399017, 0.3996818959712982, 0.4111558794975281, 0.9306337833404541,
0, 7, 0.8039304, 0.6118435263633728, 0.13175517320632935, 0.9065558314323425, 0.2943994700908661);
double scoreDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 4e-3 : 1e-5;
double iouDiff = (target == DNN_TARGET_OPENCL_FP16 || target == DNN_TARGET_MYRIAD) ? 2e-3 : 1e-4;
normAssertDetections(ref, out, "", 0.5, scoreDiff, iouDiff);
expectNoFallbacksFromIE(net);
}
}