TensorFlow: conv improvements, label_image example, and

a few other changes.

Changes:
- Some improvements to convolution by using 32-bit indices by
  @benoitsteiner. Not all calls converted yet.  Also some
  improvements to pooling as well by @benoitsteiner.

- Improvements to sparse matmul CPU implementation by Ashish

- Some fixes to warnings by @vrv

- Doc fixes to padding by @Yangqing

- Some improvements to Tensor wrappers by Eider

- Speed up of matrix inverse on CPU by Rasmus

- Add an example of doing image inference from a pre-trained model
  by @petewarden.

- fixed formula in mnist example by nodir

- Updates to event accumulator by Cassandra

- Slight changes to tensor c api by @mrry

- Handling of strings in listdiff by Phil

- Fix negative fraction-of-queue-full stats by Frank

- Type-checking improvement to importer by Yaroslav

- logdir recursive search for Tensorboard by @danmane

- Session.run() checks for empty graph by Manoj

Base CL: 108013706

1 files changed, 49 insertions, 0 deletions

diff --git a/tensorflow/examples/label_image/README.md b/tensorflow/examples/label_image/README.md
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+# Tensorflow C++ Image Recognition Demo
+
+This example shows how you can load a pre-trained TensorFlow network and use it
+to recognize objects in images.
+
+## Description
+
+This demo uses a Google Inception model to classify image files that are passed
+in on the command line. See
+[`googlenet_labels.txt`](data/googlenet_labels.txt)
+for the possible classifications, which are the 1,000 categories used in the
+Imagenet competition.
+
+## To build/install/run
+
+As long as you've managed to build the main TensorFlow framework, you should
+have everything you need to run this example installed already.
+
+To build it, run this command:
+
+```bash
+$ bazel build tensorflow/examples/label_image/...
+```
+
+That should build a binary executable that you can then run like this:
+
+```bash
+$ bazel-bin/tensorflow/examples/label_image/label_image
+```
+
+This uses the default example image that ships with the framework, and should
+output something similar to this:
+
+```
+I tensorflow/examples/label_image/main.cc:200] military uniform (866): 0.902268
+I tensorflow/examples/label_image/main.cc:200] bow tie (817): 0.05407
+I tensorflow/examples/label_image/main.cc:200] suit (794): 0.0113195
+I tensorflow/examples/label_image/main.cc:200] bulletproof vest (833): 0.0100269
+I tensorflow/examples/label_image/main.cc:200] bearskin (849): 0.00649746
+```
+In this case, we're using the default image of Admiral Grace Hopper, and you can
+see the network correctly spots she's wearing a military uniform, with a high
+score of 0.9.
+
+Next, try it out on your own images by supplying the --image= argument, e.g.
+
+```bash
+$ bazel-bin/tensorflow/examples/label_image/label_image --image=my_image.png
+```