message: Update OVIC instructions to include the detection task.
diff: @@ -97,9 +97,17 @@ filegroup(
  ...
  ```
  -* Modify `OvicClassifierTest.java` and `OvicDetectorTest.java` to test your model.
  +* For classification models, modify `OvicClassifierTest.java`:
  + * change `TEST_IMAGE_PATH` to `my_test_image.jpg`.
  -Change `TEST_IMAGE_PATH` to `my_test_image.jpg`. Change either `FLOAT_MODEL_PATH` or `QUANTIZED_MODEL_PATH` to `my_model.lite` depending on whether your model runs inference in float or [8-bit](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/quantize).
  + * change either `FLOAT_MODEL_PATH` or `QUANTIZED_MODEL_PATH` to `my_model.lite` depending on whether your model runs inference in float or [8-bit](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/quantize).
  +
  + * change `TEST_IMAGE_GROUNDTRUTH` (ImageNet class ID) to be consistent with your test image.
  +
  +* For detection models, modify `OvicDetectorTest.java`:
  + * change `TEST_IMAGE_PATH` to `my_test_image.jpg`.
  + * change `MODEL_PATH` to `my_model.lite`.
  + * change `GROUNDTRUTH` (COCO class ID) to be consistent with your test image.
  Now you can run the bazel tests to catch any runtime issues with the submission.
  @@ -115,12 +123,17 @@ Make sure that you have followed instructions in [Test your submissions](#test-y
  Modify `tensorflow/lite/java/ovic/demo/app/OvicBenchmarkerActivity.java`:
  -* Add your model to the benchmarker apk by changing `MODEL_PATH` and `TEST_IMAGE_PATH` below to your submission and test image.
  +* Add your model to the benchmarker apk by changing `modelPath` and `testImagePath` to your submission and test image.
  ```
  - private static final String TEST_IMAGE_PATH = "my_test_image.jpg";
  - private static final String MODEL_PATH = "my_model.lite";
  + if (benchmarkClassification) {
  + ...
  + testImagePath = "my_test_image.jpg";
  + modelPath = "my_model.lite";
  + } else { // Benchmarking detection.
  + ...
  ```
  +If you are adding a detection model, simply modify `modelPath` and `testImagePath` in the else block above.
  * Adjust the benchmark parameters when needed:
  