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.
- Install a prebuilt pip package:
tflite-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.
- Load input data specific to an on-device ML app.
data = ImageClassifierDataLoader.from_folder('flower_photos/')
- Customize the TensorFlow model.
model = image_classifier.create(data)
- Evaluate the model.
loss, accuracy = model.evaluate()
- 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.
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
Hashes for tflite-model-maker-nightly-0.2.6.dev202103152244.tar.gz
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | b3f77615cf31d96b995d3f02a0c6c3a9568d9170f96e5a115aed4e3c13be6514 |
|
| MD5 | 058975330033f183ccd232d7224bd276 |
|
| BLAKE2b-256 | 01a2b5aab3366bcead2bf4064ca01731177c6ed384d1b0ef38ceff2db78b6eba |
Hashes for tflite_model_maker_nightly-0.2.6.dev202103152244-py3-none-any.whl
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 7edc19787451bfa451d86320e2553f4cd1f2fa8023cf4e1cedb23d381909dabe |
|
| MD5 | a92f979f5193f4fe0d89b46d40e679d0 |
|
| BLAKE2b-256 | 2df891b89436e813c0198df9eb70dc55d63a606e7b9a442c9df57daa593a12ca |
