Skip to main content

TFLite Model Maker: a model customization library for on-device applications.

Project description

TFLite Model Maker

Overview

The TFLite Model Maker library simplifies the process of adapting and converting a TensorFlow neural-network model to particular input data when deploying this model for on-device ML applications.

Requirements

  • Refer to requirements.txt for dependent libraries that're needed to use the library and run the demo code.

Installation

There are two ways to install Model Maker.

pip install tflite-model-maker

If you want to install nightly version tflite-model-maker-nightly, please follow the command:

pip install tflite-model-maker-nightly
  • Clone the source code from GitHub and install.
git clone https://github.com/tensorflow/examples
cd examples/tensorflow_examples/lite/model_maker/pip_package
pip install -e .

End-to-End Example

For instance, it could have an end-to-end image classification example that utilizes this library with just 4 lines of code, each of which representing one step of the overall process. For more detail, you could refer to Colab for image classification.

  1. Load input data specific to an on-device ML app.
data = ImageClassifierDataLoader.from_folder('flower_photos/')
  1. Customize the TensorFlow model.
model = image_classifier.create(data)
  1. Evaluate the model.
loss, accuracy = model.evaluate()
  1. Export to Tensorflow Lite model and label file in export_dir.
model.export(export_dir='/tmp/')

Notebook

Currently, we support image classification, text classification and question answer tasks. Meanwhile, we provide demo code for each of them in demo folder.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

Built Distribution

File details

Details for the file tflite-model-maker-nightly-0.2.5.dev202101202243.tar.gz.

File metadata

  • Download URL: tflite-model-maker-nightly-0.2.5.dev202101202243.tar.gz
  • Upload date:
  • Size: 291.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/51.3.3 requests-toolbelt/0.9.1 tqdm/4.56.0 CPython/3.7.9

File hashes

Hashes for tflite-model-maker-nightly-0.2.5.dev202101202243.tar.gz
Algorithm Hash digest
SHA256 9a0d6621ed671e89bbf6037aba5b430d93b573d5ac17888169bad5b0604df36c
MD5 97fef095a565594bb9d00363d8e9854c
BLAKE2b-256 f37a54722664ea81328958f904a2a038ca35f893fb5219cab3b1e6089b0f4c69

See more details on using hashes here.

File details

Details for the file tflite_model_maker_nightly-0.2.5.dev202101202243-py3-none-any.whl.

File metadata

File hashes

Hashes for tflite_model_maker_nightly-0.2.5.dev202101202243-py3-none-any.whl
Algorithm Hash digest
SHA256 0932198c95a452e165f200cdceaa00979cc30d1ecab61989f9bb45247e2afd24
MD5 23eb1689c41998447d74958b2842ebed
BLAKE2b-256 711306f1d1a66e5f72b6224e05b007ec735998125c1219b57527fc11c25ad138

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page