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-0.2.4.dev202012012228.tar.gz
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 76dd1d6f883f5ff18cc95a7ecaa1f039e8986e7ed26512dc85e3c1d9ab4d790b |
|
| MD5 | f04f7fab3f0e7af3400735efbbf06bd1 |
|
| BLAKE2b-256 | b285ea4750653105ae9189d47a9e398973145f4feaf9b0c10b64aa357a6552f0 |
Hashes for tflite_model_maker_nightly-0.2.4.dev202012012228-py3-none-any.whl
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 732f771883027f304cbc0af76bfcaf8ee1db081f63a834bb23a402b203821367 |
|
| MD5 | 8bb5ccb5895fa7860bba0ef441fc0ad6 |
|
| BLAKE2b-256 | f4c93d3c864cc5c86d6f0220ddde75896e51f91a0f9447fddf448ce88d1a8400 |
