From d1c10789ba464de49eccb1495f5ac8afa30ff45e Mon Sep 17 00:00:00 2001
From: wang-xinyu <wangxinyu_es@163.com>
Date: Tue, 7 Apr 2020 13:11:10 +0000
Subject: [PATCH] retina fpn

---
 retinaface/README.md      |  3 +++
 retinaface/retina_r50.cpp | 34 +++++++++++++---------------------
 2 files changed, 16 insertions(+), 21 deletions(-)
 create mode 100644 retinaface/README.md

diff --git a/retinaface/README.md b/retinaface/README.md
new file mode 100644
index 0000000..1618b2d
--- /dev/null
+++ b/retinaface/README.md
@@ -0,0 +1,3 @@
+# RetinaFace
+
+still working in progress
diff --git a/retinaface/retina_r50.cpp b/retinaface/retina_r50.cpp
index df7ce34..3651133 100644
--- a/retinaface/retina_r50.cpp
+++ b/retinaface/retina_r50.cpp
@@ -13,12 +13,12 @@
 #include <opencv2/opencv.hpp>
 
 //#define USE_FP16  // comment out this if want to use FP32
-#define DEVICE 1  // GPU id
+#define DEVICE 0  // GPU id
 
 // stuff we know about the network and the input/output blobs
 static const int INPUT_H = 384;  // 
 static const int INPUT_W = 640;
-static const int OUTPUT_SIZE = 256 * 24 * 40;
+static const int OUTPUT_SIZE = 256 * 48 * 80;
 const char* INPUT_BLOB_NAME = "data";
 const char* OUTPUT_BLOB_NAME = "prob";
 
@@ -324,28 +324,20 @@ ICudaEngine* createEngine(unsigned int maxBatchSize, IBuilder* builder, DataType
     up3->setNbGroups(256);
     weightMap["up3"] = deconvwts;
 
-    IElementWiseLayer* ew1 = network->addElementWise(*output2->getOutput(0), *up3->getOutput(0), ElementWiseOperation::kSUM);
-    assert(ew1);
+    output2 = network->addElementWise(*output2->getOutput(0), *up3->getOutput(0), ElementWiseOperation::kSUM);
+    output2 = conv_bn_relu(network, weightMap, *output2->getOutput(0), 256, 3, 1, 1, true, "fpn.merge2");
 
-    Dims dims = ew1->getOutput(0)->getDimensions();
-    std::cout << ew1->getOutput(0)->getName() << " dims";
-    for (int i = 0; i < dims.nbDims; i++) {
-        std::cout << dims.d[i] << "-" << (int)dims.type[i] << "   ";
-    }
-    std::cout << std::endl;
+    IDeconvolutionLayer* up2 = network->addDeconvolution(*output2->getOutput(0), 256, DimsHW{2, 2}, deconvwts, emptywts);
+    assert(up2);
+    up2->setStride(DimsHW{2, 2});
+    up2->setNbGroups(256);
+    output1 = network->addElementWise(*output1->getOutput(0), *up2->getOutput(0), ElementWiseOperation::kSUM);
+    output1 = conv_bn_relu(network, weightMap, *output1->getOutput(0), 256, 3, 1, 1, true, "fpn.merge1");
 
-    //output2 = conv_bn_relu(network, weightMap, *ew1->getOutput(0), 256, 3, 1, 1, true, "fpn.merge2");
-
-    //IDeconvolutionLayer* up2 = network->addDeconvolution(*output2->getOutput(0), 256, DimsHW{2, 2}, deconvwts, emptywts);
-    //assert(up2);
-    //up2->setStride(DimsHW{2, 2});
-    //up2->setNbGroups(256);
-    //output1 = network->addElementWise(*output1->getOutput(0), *up2->getOutput(0), ElementWiseOperation::kSUM);
-    //output1 = conv_bn_relu(network, weightMap, *output1->getOutput(0), 256, 3, 1, 1, true, "fpn.merge1");
-
-    ew1->getOutput(0)->setName(OUTPUT_BLOB_NAME);
+    // ------------- SSH ---------------
+    output1->getOutput(0)->setName(OUTPUT_BLOB_NAME);
     std::cout << "set name out" << std::endl;
-    network->markOutput(*ew1->getOutput(0));
+    network->markOutput(*output1->getOutput(0));
 
     // Build engine
     builder->setMaxBatchSize(maxBatchSize);