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.
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
Hashes for tflite-model-maker-nightly-0.2.5.dev202101132237.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | ec5d692a1927db9a096277e829f5df9a7daee66f204826a07bcbc70b57ba637b |
|
MD5 | 870b406d97c84d812042ae0ad6cbc1c1 |
|
BLAKE2b-256 | 47ee28233aafc81fefc1e99692c583156856095772c3758ccabced6ace0673b9 |
Hashes for tflite_model_maker_nightly-0.2.5.dev202101132237-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | f9aa34b48e26146fbc11c912b1397a893d3a26a6bf4dcd55776b277878184de0 |
|
MD5 | ae09bc961a03eb719512c2fd58330e81 |
|
BLAKE2b-256 | 2f59a9f0e8df7da9e948449ac836f3d88ed5b84a4f81969c92a957c74838bdcf |