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diff --git a/tensorflow/examples/wav_to_spectrogram/main.cc b/tensorflow/examples/wav_to_spectrogram/main.cc
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+++ b/tensorflow/examples/wav_to_spectrogram/main.cc
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+/* Copyright 2017 The TensorFlow Authors. 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/examples/wav_to_spectrogram/wav_to_spectrogram.h"
+
+#include "tensorflow/core/lib/core/errors.h"
+#include "tensorflow/core/platform/init_main.h"
+#include "tensorflow/core/util/command_line_flags.h"
+
+int main(int argc, char* argv[]) {
+  // These are the command-line flags the program can understand.
+  // They define where the graph and input data is located, and what kind of
+  // input the model expects. If you train your own model, or use something
+  // other than inception_v3, then you'll need to update these.
+  tensorflow::string input_wav =
+      "tensorflow/core/kernels/spectrogram_test_data/short_test_segment.wav";
+  tensorflow::int32 window_size = 256;
+  tensorflow::int32 stride = 128;
+  float brightness = 64.0f;
+  tensorflow::string output_image = "spectrogram.png";
+  std::vector<tensorflow::Flag> flag_list = {
+      tensorflow::Flag("input_wav", &input_wav, "audio file to load"),
+      tensorflow::Flag("window_size", &window_size,
+                       "frequency sample window width"),
+      tensorflow::Flag("stride", &stride,
+                       "how far apart to place frequency windows"),
+      tensorflow::Flag("brightness", &brightness,
+                       "controls how bright the output image is"),
+      tensorflow::Flag("output_image", &output_image,
+                       "where to save the spectrogram image to"),
+  };
+  tensorflow::string usage = tensorflow::Flags::Usage(argv[0], flag_list);
+  const bool parse_result = tensorflow::Flags::Parse(&argc, argv, flag_list);
+  if (!parse_result) {
+    LOG(ERROR) << usage;
+    return -1;
+  }
+
+  // We need to call this to set up global state for TensorFlow.
+  tensorflow::port::InitMain(argv[0], &argc, &argv);
+  if (argc > 1) {
+    LOG(ERROR) << "Unknown argument " << argv[1] << "\n" << usage;
+    return -1;
+  }
+
+  tensorflow::Status wav_status = WavToSpectrogram(
+      input_wav, window_size, stride, brightness, output_image);
+  if (!wav_status.ok()) {
+    LOG(ERROR) << "WavToSpectrogram failed with " << wav_status;
+    return -1;
+  }
+
+  return 0;
+}