From 5687062d10f1090f44fad24bf7b93a14e924af21 Mon Sep 17 00:00:00 2001 From: MediaPipe Team Date: Thu, 20 Jun 2019 08:11:11 -0700 Subject: [PATCH] Project import generated by Copybara. PiperOrigin-RevId: 254198377 --- mediapipe/docs/framework_concepts.md | 2 +- mediapipe/docs/media_sequence.md | 4 ++-- mediapipe/util/sequence/README.md | 2 -- mediapipe/util/tflite/operations/BUILD | 1 + 4 files changed, 4 insertions(+), 5 deletions(-) diff --git a/mediapipe/docs/framework_concepts.md b/mediapipe/docs/framework_concepts.md index 34aa429e8..5facb283c 100644 --- a/mediapipe/docs/framework_concepts.md +++ b/mediapipe/docs/framework_concepts.md @@ -117,7 +117,7 @@ combination of tag name and index number. You can see some examples of input and output identifiers in the example below. `SomeAudioVideoCalculator` identifies its video output by tag and its audio outputs by the combination of tag and index. The input with tag `VIDEO` is connected to the stream named -`video_stream`. The inputs with tag `AUDIO` and indices `0` and `1` are +`video_stream`. The outputs with tag `AUDIO` and indices `0` and `1` are connected to the streams named `audio_left` and `audio_right`. `SomeAudioCalculator` identifies its audio inputs by index only (no tag needed). diff --git a/mediapipe/docs/media_sequence.md b/mediapipe/docs/media_sequence.md index 2b737d684..adcd473f9 100644 --- a/mediapipe/docs/media_sequence.md +++ b/mediapipe/docs/media_sequence.md @@ -20,7 +20,7 @@ process new data sets, in the [documentation](https://github.com/google/mediapip 1. Checkout mediapipe repository ```bash - git clone https://github.com/google/mediapipe/mediapipe + git clone https://github.com/google/mediapipe.git cd mediapipe ``` @@ -115,7 +115,7 @@ python -m mediapipe.examples.desktop.media_sequence.demo_dataset \ ### Preparing your own data set The process for preparing your own data set is described in the [MediaSequence -documentation](https://github.com/google/mediapipe/tree/master/mediapipe/util/sequence/README.md). +documentation](https://github.com/google/mediapipe/blob/master/mediapipe/util/sequence/README.md). The Python code for Charades can easily be modified to process most annotations, but the MediaPipe processing warrants further discussion. MediaSequence uses MediaPipe graphs to extract features related to the metadata or previously diff --git a/mediapipe/util/sequence/README.md b/mediapipe/util/sequence/README.md index b9e87b8b5..1d80ce60f 100644 --- a/mediapipe/util/sequence/README.md +++ b/mediapipe/util/sequence/README.md @@ -6,8 +6,6 @@ prototypes used in MediaSequence for storing multimedia data in SequenceExamples. Finally, the documentation will describe the specific keys for storing specific types of data. -[TOC] - ## Overview of MediaSequence for machine learning The goal of MediaSequence is to provide a tool for transforming annotations of diff --git a/mediapipe/util/tflite/operations/BUILD b/mediapipe/util/tflite/operations/BUILD index b7eccc7e1..3515716ab 100644 --- a/mediapipe/util/tflite/operations/BUILD +++ b/mediapipe/util/tflite/operations/BUILD @@ -54,5 +54,6 @@ cc_library( "@org_tensorflow//tensorflow/lite/kernels:padding", "@org_tensorflow//tensorflow/lite/kernels/internal:tensor", "@org_tensorflow//tensorflow/lite/kernels/internal:tensor_utils", + "@org_tensorflow//tensorflow/lite/kernels/internal:types", ], )