catch up to tizen_5.5 and remove unness dir

- update to tizen_5.5
- remove dirs

1 files changed, 74 insertions, 0 deletions

diff --git a/runtimes/contrib/detection/detection.cpp b/runtimes/contrib/detection/detection.cpp
new file mode 100644
index 000000000..8fe78ca57
--- /dev/null
+++ b/runtimes/contrib/detection/detection.cpp
@@ -0,0 +1,74 @@
+/*
+ * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <tensorflow/core/public/session.h>
+
+#include <iostream>
+#include <stdexcept>
+
+#include <cassert>
+#include <cstring>
+
+#include "misc/benchmark.h"
+
+#define CHECK_TF(e)                                \
+  {                                                \
+    if (!(e).ok())                                 \
+    {                                              \
+      throw std::runtime_error{"'" #e "' FAILED"}; \
+    }                                              \
+  }
+
+int main(int argc, char **argv)
+{
+  if (argc < 2)
+  {
+    std::cerr << "USAGE: " << argv[0] << " [T/F model path] [output 0] [output 1] ..." << std::endl;
+    return 255;
+  }
+
+  std::vector<std::string> output_nodes;
+
+  for (int argn = 2; argn < argc; ++argn)
+  {
+    output_nodes.emplace_back(argv[argn]);
+  }
+
+  tensorflow::Session *sess;
+
+  CHECK_TF(tensorflow::NewSession(tensorflow::SessionOptions(), &sess));
+
+  tensorflow::GraphDef graph_def;
+
+  CHECK_TF(ReadBinaryProto(tensorflow::Env::Default(), argv[1], &graph_def));
+  CHECK_TF(sess->Create(graph_def));
+
+  tensorflow::Tensor input(tensorflow::DT_FLOAT, tensorflow::TensorShape({1, 320, 320, 3}));
+  std::vector<tensorflow::Tensor> outputs;
+
+  for (uint32_t n = 0; n < 5; ++n)
+  {
+    std::chrono::milliseconds elapsed(0);
+
+    nnfw::misc::benchmark::measure(elapsed) << [&](void) {
+      CHECK_TF(sess->Run({{"input_node", input}}, output_nodes, {}, &outputs));
+    };
+
+    std::cout << "Takes " << elapsed.count() << "ms" << std::endl;
+  }
+
+  return 0;
+}