There are 2 key elements in the main export directory. Your model in TFLite format (.tflite) and signature.json which contains information about your Lobe project. With these, you are ready to use your model! If you want to see an example of how to use this model, there are instructions below for running a quick test script.
signature.json is created by Lobe and contains information about the model such as label names and the image size and shape the model expects.
tflite_example.py is a simple script to quickly test your exported model. It takes a path to an image on your file system, prepares the image and returns the predicted class and confidence level.
requirements.txt is where the Python libraries and version information required to run the script are found.
You will need Python 3.6 and the path to an image on your machine to test.
Create a virtual environment
python -m venv tflite-venv
Activate the virtual environment
macOS source tflite-venv/bin/activate
Windows tflite-venv/Scripts/activate
Install the the dependencies for the example
python -m pip install --upgrade pip && pip install -r requirements.txt
Pip with the requirements.txt file should install the Tensorflow Lite runtime appropriate to your OS version if you are on Windows, Mac, or Linux.
Please double check to make sure that tflite_runtime was installed via pip. If you have a different Linux distribution (such as Raspberry Pi),
or find that the runtime was not installed from pip, then please install the appropriate Tensorflow Lite runtime wheel based on your OS and Python version.
For example, if you are on Windows 10 with Python 3.6:
pip install https://dl.google.com/coral/python/tflite_runtime-2.1.0.post1-cp36-cp36m-win_amd64.whl
Finally, run the example and see the model output
python tflite_example.py path/to/image/for/testing
If you see the error "OSError: image file is truncated", you may need to add the following lines the sample code due to an issue with PIL (Python Image Library)
from PIL import ImageFile
ImageFile.LOAD_TRUNCATED_IMAGES = True