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| author |  Andrew Selle <aselle@andyselle.com> | 2017-11-14 11:45:24 -0800 |
|---|---|---|
| committer | Andrew Selle <aselle@andyselle.com> | 2017-11-14 11:46:21 -0800 |
| commit | fdf82fc5c26c848749b16e860925b92ed2d3d727 (patch) | |
| tree | 56a7a6fd1924a4e9654bdebc0fbf8b526a6b32f1 | |
| parent | 7be5ab5ddbfd7d81ffd7e2022633908a14a52ff1 (diff) | |
Comment about python2 compatibility issue
| -rw-r--r-- | tensorflow/contrib/lite/README.md | 5 |
1 files changed, 5 insertions, 0 deletions
diff --git a/tensorflow/contrib/lite/README.md b/tensorflow/contrib/lite/README.md index b173936f5b..0c511f753a 100644 --- a/tensorflow/contrib/lite/README.md +++ b/tensorflow/contrib/lite/README.md @@ -77,6 +77,11 @@ Run bazel with the following command to build the demo. Build the demo app: bazel build --cxxopt='--std=c++11' //tensorflow/contrib/lite/java/demo/app/src/main:TfLiteCameraDemo +### Note + +Currently, we only support building the Android demo app within a Python 2 +environment (due to a Bazel bug). + ### More about the demo The demo is resizing each camera image frame to (224 width * 224 height) to match the quantized Mobilenet model being used. The resized image is converted into a ByteBuffer row by row of size 1 * 224 * 224 * 3 bytes, where 1 is the number of images in a batch 224 * 224 is the width and height of the image 3 bytes represents three colors of a pixel. This demo uses the TensorFlow Lite Java inference API for models which take a single input and provide a single output. This outputs a two-dimensional array, with the first dimension being the category index and the second dimension being the confidence of classification. The Mobilenet model has 1001 unique categories and the app sorts the probabilities of all the categories and displays the top three. The Mobilenet quantized model is bundled within the assets directory of the app. |