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Faster-RCNN models support

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This commit is contained in:
Dmitry Kurtaev
2017-12-13 19:06:30 +03:00
parent 84535a60f2
commit 08112f3821
12 changed files with 2420 additions and 501 deletions
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modules/dnn/test/test_layers.cpp
+23
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@@ -576,4 +576,27 @@ TEST(Layer_Test_ROIPooling, Accuracy)
normAssert(out, ref);
}
TEST(Layer_Test_FasterRCNN_Proposal, Accuracy)
{
Net net = readNetFromCaffe(_tf("net_faster_rcnn_proposal.prototxt"));
Mat scores = blobFromNPY(_tf("net_faster_rcnn_proposal.scores.npy"));
Mat deltas = blobFromNPY(_tf("net_faster_rcnn_proposal.deltas.npy"));
Mat imInfo = (Mat_<float>(1, 3) << 600, 800, 1.6f);
Mat ref = blobFromNPY(_tf("net_faster_rcnn_proposal.npy"));
net.setInput(scores, "rpn_cls_prob_reshape");
net.setInput(deltas, "rpn_bbox_pred");
net.setInput(imInfo, "im_info");
Mat out = net.forward();
const int numDets = ref.size[0];
EXPECT_LE(numDets, out.size[0]);
normAssert(out.rowRange(0, numDets), ref);
if (numDets < out.size[0])
EXPECT_EQ(countNonZero(out.rowRange(numDets, out.size[0])), 0);
}
}