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-0.2.3.dev202010232146.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | e2f7282d991b0ecf76c59689ddd28dc666e61a146430cdd05d90e459fe95ff02 |
|
MD5 | b4ab0a5753af9d8ea6192a4d6ffaf019 |
|
BLAKE2b-256 | 668820c9dcc02b0826ac1a0887393470a465e6e12ebfee41140f4bf8b62862d9 |
Hashes for tflite_model_maker_nightly-0.2.3.dev202010232146-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 835ec5e1f2059bec90061e40a246fbf28504678a49451e4f8426e63033085cc1 |
|
MD5 | f1ae5b8f2d5695513897d3102dd38b88 |
|
BLAKE2b-256 | f8a7bac5f1fd2e0963a609db0644171696b78caf0dce9434f859ebce454b75c8 |