diff options
Diffstat (limited to 'tensorflow/contrib/pi_examples/label_image/label_image.cc')
| -rw-r--r-- | tensorflow/contrib/pi_examples/label_image/label_image.cc | 41 |
1 files changed, 24 insertions, 17 deletions
diff --git a/tensorflow/contrib/pi_examples/label_image/label_image.cc b/tensorflow/contrib/pi_examples/label_image/label_image.cc index 70f32f2199..ab19398ef2 100644 --- a/tensorflow/contrib/pi_examples/label_image/label_image.cc +++ b/tensorflow/contrib/pi_examples/label_image/label_image.cc @@ -23,9 +23,10 @@ limitations under the License. // // Full build instructions are at tensorflow/contrib/pi_examples/README.md. -#include <fstream> #include <jpeglib.h> #include <setjmp.h> +#include <fstream> +#include <vector> #include "tensorflow/core/framework/graph.pb.h" #include "tensorflow/core/framework/tensor.h" @@ -297,7 +298,8 @@ int main(int argc, char* argv[]) { // 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 GoogLeNet you'll need to update these. - string image = "tensorflow/contrib/pi_examples/label_image/data/" + string image = + "tensorflow/contrib/pi_examples/label_image/data/" "grace_hopper.jpg"; string graph = "tensorflow/contrib/pi_examples/label_image/data/" @@ -313,27 +315,32 @@ int main(int argc, char* argv[]) { string output_layer = "softmax"; bool self_test = false; string root_dir = ""; - const bool parse_result = tensorflow::ParseFlags( - &argc, argv, {Flag("image", &image), // - Flag("graph", &graph), // - Flag("labels", &labels), // - Flag("input_width", &input_width), // - Flag("input_height", &input_height), // - Flag("input_mean", &input_mean), // - Flag("input_std", &input_std), // - Flag("input_layer", &input_layer), // - Flag("output_layer", &output_layer), // - Flag("self_test", &self_test), // - Flag("root_dir", &root_dir)}); + vector tensorflow::Flag > flag_list = { + Flag("image", &image, "image to be processed"), + Flag("graph", &graph, "graph to be executed"), + Flag("labels", &labels, "name of file containing labels"), + Flag("input_width", &input_width, "resize image to this width in pixels"), + Flag("input_height", &input_height, + "resize image to this height in pixels"), + Flag("input_mean", &input_mean, "scale pixel values to this mean"), + Flag("input_std", &input_std, "scale pixel values to this std deviation"), + Flag("input_layer", &input_layer, "name of input layer"), + Flag("output_layer", &output_layer, "name of output layer"), + Flag("self_test", &self_test, "run a self test"), + Flag("root_dir", &root_dir, + "interpret image and graph file names relative to this directory"), + }; + 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) << "Error parsing command-line flags."; + LOG(ERROR) << "\n" << usage; return -1; } // We need to call this to set up global state for TensorFlow. - tensorflow::port::InitMain(argv[0], &argc, &argv); + tensorflow::port::InitMain(usage, &argc, &argv); if (argc > 1) { - LOG(ERROR) << "Unknown argument " << argv[1]; + LOG(ERROR) << "Unknown argument " << argv[1] << "\n" << usage; return -1; } |