Metadata-Version: 2.1
Name: tflite-model-maker
Version: 0.2.5
Summary: TFLite Model Maker: a model customization library for on-device applications.
Home-page: http://github.com/tensorflow/examples
Author: Google LLC
Author-email: packages@tensorflow.org
License: Apache 2.0
Download-URL: https://github.com/tensorflow/examples/tags
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](https://github.com/tensorflow/examples/blob/master/tensorflow_examples/lite/model_maker/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`](https://pypi.org/project/tflite-model-maker/).
        
        ```shell
        pip install tflite-model-maker
        ```
        
        If you want to install nightly version
        [`tflite-model-maker-nightly`](https://pypi.org/project/tflite-model-maker-nightly/),
        please follow the command:
        
        ```shell
        pip install tflite-model-maker-nightly
        ```
        
        *   Clone the source code from GitHub and install.
        
        ```shell
        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](https://colab.research.google.com/github/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/tutorials/model_maker_image_classification.ipynb).
        
        1.   Load input data specific to an on-device ML app.
        
        ```python
        data = ImageClassifierDataLoader.from_folder('flower_photos/')
        ```
        
        2. Customize the TensorFlow model.
        
        ```python
        model = image_classifier.create(data)
        ```
        
        3. Evaluate the model.
        
        ```python
        loss, accuracy = model.evaluate()
        ```
        
        4.  Export to Tensorflow Lite model and label file in `export_dir`.
        
        ```python
        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.
        
        *   [Overview for TensorFlow Lite Model Maker](https://www.tensorflow.org/lite/guide/model_maker)
        *   [Colab for image classification](https://colab.research.google.com/github/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/tutorials/model_maker_image_classification.ipynb)
        *   [Colab for text classification](https://colab.research.google.com/github/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/tutorials/model_maker_text_classification.ipynb)
        *   [Colab for BERT question answer](https://colab.research.google.com/github/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/tutorials/model_maker_question_answer.ipynb)
        
Keywords: tensorflow,lite,model customization,transfer learning
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown
