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|
project_path: /lite/_project.yaml
book_path: /lite/_book.yaml
description: <!--no description-->
landing_page:
custom_css_path: /site-assets/css/style.css
rows:
- heading: TensorFlow Lite is for mobile and embedded devices.
description: >
<p style="max-width: 75%;">
TensorFlow Lite is the official solution for running machine learning
models on mobile and embedded devices. It enables on‑device machine
learning inference with low latency and a small binary size on Android,
iOS, and other operating systems.
</p>
<style>
.tfo-landing-row-heading {
padding-top: 0 !important;
}
.tfo-landing-row-heading h2 {
margin-top: 0 !important;
}
.tfo-landing-row-heading-list ol, .tfo-landing-row-heading-list ul {
margin-top: 0;
}
</style>
- classname: tfo-landing-row-heading tfo-landing-row-heading-list
heading: Many benefits
description: >
On-device ML inference is difficult because of the many constraints—TensorFlow Lite can solve these:
items:
- list:
- heading: Performance
description: >
TF Lite is fast with no noticeable accuracy loss—see the <a href="./performance">metrics</a>.
icon:
icon_name: lens
foreground: theme
- heading: Portability
description: >
<a href="https://developer.android.com/ndk/guides/neuralnetworks/" class="external">Android</a>,
iOS, and more specialized IoT devices.
icon:
icon_name: lens
foreground: theme
- list:
- heading: Low latency
description: >
Optimized float- and fixed-point CPU kernels, op‑fusing, and more.
icon:
icon_name: lens
foreground: theme
- heading: Acceleration
description: >
Integration with GPU and internal/external accelerators.
icon:
icon_name: lens
foreground: theme
- list:
- heading: Small model size
description: >
Controlled dependencies, <a href="https://medium.com/tensorflow/introducing-the-model-optimization-toolkit-for-tensorflow-254aca1ba0a3" class="external">quantization</a>,
and op registration.
icon:
icon_name: lens
foreground: theme
- heading: Tooling
description: >
Conversion, compression, benchmarking, power-consumption, and more.
icon:
icon_name: lens
foreground: theme
- classname: devsite-landing-row-logos tfo-landing-row-heading
heading: Companies using TensorFlow Lite
items:
- custom_image:
path: ./images/landing-page/photos_logo.png
path: https://www.photos.google.com
- custom_image:
path: ./images/landing-page/gboard_logo.png
path: https://play.google.com/store/apps/details?id=com.google.android.inputmethod.latin&hl=en_US
- custom_image:
path: ./images/landing-page/gmail_logo.png
path: https://www.google.com/gmail/
- custom_image:
path: ./images/landing-page/assistant_logo.png
path: https://assistant.google.com/
- classname: devsite-landing-row-logos
items:
- custom_image:
path: ./images/landing-page/vsco_logo.png
path: https://vsco.co
- custom_image:
path: ./images/landing-page/shazam_logo.png
path: https://www.shazam.com/
- custom_image:
path: ./images/landing-page/nest_logo.png
path: https://nest.com/
- custom_image:
path: ./images/landing-page/loseit_logo.png
path: https://www.loseit.com/
- classname: devsite-landing-row-no-image-background devsite-landing-row-67
background: grey
items:
- description: >
<em>“TensorFlow Lite helped us introduce machine learning and AI into our
app in an easy and streamlined way. We could reduce the size of our
models while keeping the accuracy high. This helped us create an amazing
fishing experience for our users by allowing them to identify any fish
species with just a photo.”</em>
image_path: ./images/landing-page/fishbrain_logo_big.png
- heading: How it works
items:
- heading: Build
icon:
icon_name: build
description: >
Build a new model or retrain an existing one, such as using transfer learning.
buttons:
- label: Read the developer guide
path: /lite/devguide
classname: button button-primary tfo-button-primary
- heading: Convert
icon:
icon_name: autorenew
description: >
Convert a TensorFlow model into a compressed flat buffer with the
TensorFlow Lite Optimizing Converter (TOCO).
buttons:
- label: Read the TOCO guide
path: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/lite/toco/g3doc/python_api.md
classname: button button-primary tfo-button-primary
- heading: Deploy
icon:
icon_name: bolt
description: >
Take the compressed <code>.tflite</code> file and load it into a mobile
or embedded device.<br/>
See the <a href="#build-your-first-tensorflow-lite-app">tutorials below</a> to build an app.
- heading: Build your first TensorFlow Lite app
background: grey
items:
- classname: tfo-landing-row-item-inset-white
heading: Get started
description: >
<ul>
<li>Beginner: <a href="https://codelabs.developers.google.com/codelabs/tensorflow-for-poets/" class="external">TensorFlow for Poets</a></li>
<li>Beginner: <a href="https://codelabs.developers.google.com/codelabs/tensorflow-for-poets-2-tflite/" class="external">TensorFlow for Poets 2: Android</a></li>
<li>Beginner: <a href="https://codelabs.developers.google.com/codelabs/tensorflow-for-poets-2-ios/" class="external">TensorFlow for Poets 2: iOS </a></li>
<li>Intermediate: <a href="https://medium.com/tensorflow/training-and-serving-a-realtime-mobile-object-detector-in-30-minutes-with-cloud-tpus-b78971cf1193" class="external">Object detection tutorial</a>
</ul>
- classname: tfo-landing-row-item-inset-white
heading: Share your TensorFlow Lite story
description: >
We love to hear what you're working on—it may even get highlighted on
our social media! <a href="https://groups.google.com/a/tensorflow.org/forum/#!forum/discuss" class="external">Tell us</a>.
- classname: devsite-landing-row-no-image-background devsite-landing-row-67
items:
- description: >
<p>
<em>“The release of TensorFlow Lite has allowed us to deploy an engaging
real-time experience to our users that eliminates the requirement
for a data connection. TensorFlow Lite’s ability to compress and
optimize the TensorFlow graph for mobile deployment has been
transformative in expanding the capabilities of Snap It.</em>
</p>
<p>
<em>Through TensorFlow Lite, our users can now enjoy a state of the
art, computer-vision-based food logging experience without worrying
about signal strength. We look forward to future collaborations
with the TensorFlow Lite team.”</em>
</p>
image_path: ./images/landing-page/loseit_logo_big.png
- classname: devsite-landing-row-cards
background: grey
heading: Updates
items:
- heading: Introducing the Model Optimization Toolkit
image_path: /ecosystem/images/tf-logo-card-16x9.png
path: https://medium.com/tensorflow/introducing-the-model-optimization-toolkit-for-tensorflow-254aca1ba0a3
buttons:
- label: Read on TensorFlow blog
path: https://medium.com/tensorflow/introducing-the-model-optimization-toolkit-for-tensorflow-254aca1ba0a3
- heading: East Africa Cassava App
image_path: ./images/landing-page/detect_crop_disease_in_africa.png
path: https://heartbeat.fritz.ai/community-spotlight-nuru-a-mobile-app-by-plantvillage-to-detect-crop-disease-in-africa-28d142bf63d5
buttons:
- label: Read more
path: https://heartbeat.fritz.ai/community-spotlight-nuru-a-mobile-app-by-plantvillage-to-detect-crop-disease-in-africa-28d142bf63d5
- heading: Using TensorFlow Lite on Android
image_path: /ecosystem/images/tf-logo-card-16x9.png
path: https://medium.com/tensorflow/using-tensorflow-lite-on-android-9bbc9cb7d69d
buttons:
- label: Read on TensorFlow blog
path: https://medium.com/tensorflow/using-tensorflow-lite-on-android-9bbc9cb7d69d
- classname: devsite-landing-row-cards
background: grey
items:
- heading: TensorFlow Lite at the Dev Summit
youtube_id: FAMfy7izB6A
buttons:
- label: Watch the video
path: https://www.youtube.com/watch?v=FAMfy7izB6A
- heading: TensorFlow Lite on GitHub
image_path: /ecosystem/images/github-card-16x9.png
path: https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite
buttons:
- label: View on GitHub
path: https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite
- classname: devsite-landing-row-item-hidden
|
