aboutsummaryrefslogtreecommitdiffhomepage
path: root/tensorflow/examples/android/README.md
diff options
context:
space:
mode:
Diffstat (limited to 'tensorflow/examples/android/README.md')
-rw-r--r--tensorflow/examples/android/README.md39
1 files changed, 27 insertions, 12 deletions
diff --git a/tensorflow/examples/android/README.md b/tensorflow/examples/android/README.md
index b0465f7faa..b6556cdef4 100644
--- a/tensorflow/examples/android/README.md
+++ b/tensorflow/examples/android/README.md
@@ -1,11 +1,24 @@
# TensorFlow Android Camera Demo
-This folder contains a simple camera-based demo application utilizing TensorFlow.
+This folder contains an example application utilizing TensorFlow for Android
+devices.
## Description
-This demo uses a Google Inception model to classify camera frames in real-time,
-displaying the top results in an overlay on the camera image.
+The demos in this folder are designed to give straightforward samples of using
+TensorFlow in mobile applications. Inference is done using the Java JNI API
+exposed by `tensorflow/contrib/android`.
+
+Current samples:
+
+1. [TF Classify](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/android/src/org/tensorflow/demo/ClassifierActivity.java):
+ Uses the [Google Inception](https://arxiv.org/abs/1409.4842)
+ model to classify camera frames in real-time, displaying the top results
+ in an overlay on the camera image.
+2. [TF Detect](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/android/src/org/tensorflow/demo/DetectorActivity.java):
+ Demonstrates a model based on [Scalable Object Detection
+ using Deep Neural Networks](https://arxiv.org/abs/1312.2249) to
+ localize and track people in the camera preview in real-time.
## To build/install/run
@@ -19,9 +32,9 @@ installed on your system.
3. The Android SDK and build tools may be obtained from:
https://developer.android.com/tools/revisions/build-tools.html
-The Android entries in [`<workspace_root>/WORKSPACE`](../../../WORKSPACE#L2-L13) must be
-uncommented with the paths filled in appropriately depending on where you
-installed the NDK and SDK. Otherwise an error such as:
+The Android entries in [`<workspace_root>/WORKSPACE`](../../../WORKSPACE#L2-L13)
+must be uncommented with the paths filled in appropriately depending on where
+you installed the NDK and SDK. Otherwise an error such as:
"The external label '//external:android/sdk' is not bound to anything" will
be reported.
@@ -29,19 +42,21 @@ The TensorFlow `GraphDef` that contains the model definition and weights
is not packaged in the repo because of its size. It will be downloaded
automatically via a new_http_archive defined in WORKSPACE.
-**Optional**: If you wish to place the model in your assets manually (E.g. for
-non-Bazel builds), remove the
-`inception_5` entry in `BUILD` and download the archive yourself to the
-`assets` directory in the source tree:
+**Optional**: If you wish to place the models in your assets manually (E.g. for
+non-Bazel builds), remove the `inception_5` and `mobile_multibox` entries in
+`BUILD` and download the archives yourself to the `assets` directory in the
+source tree:
```bash
$ curl -L https://storage.googleapis.com/download.tensorflow.org/models/inception5h.zip -o /tmp/inception5h.zip
+$ curl -L https://storage.googleapis.com/download.tensorflow.org/models/mobile_multibox_v1.zip -o /tmp/mobile_multibox_v1.zip
$ unzip /tmp/inception5h.zip -d tensorflow/examples/android/assets/
+$ unzip /tmp/mobile_multibox_v1.zip -d tensorflow/examples/android/assets/
```
-The labels file describing the possible classification will also be in the
-assets directory.
+The associated label and box prior files for the models will also be extracted
+into the assets directory.
After editing your WORKSPACE file to update the SDK/NDK configuration,
you may build the APK. Run this from your workspace root: