TensorFlow Lite Code Samples

This page provides a collection of TensorFlow Lite code samples that showcase different capabilities and applications of the TensorFlow Lite library. Whether you are new to TensorFlow Lite or looking to expand your knowledge, these examples can serve as a valuable resource.

Getting Started

Here's a simple example of a TensorFlow Lite model in action:

import tensorflow as tf

# Load the model
interpreter = tf.lite.Interpreter(model_content=model_content)

# Allocate tensors.
interpreter.allocate_tensors()

# Get input and output tensors.
input_details = interpreter.get_input_details()
output_details = interpreter.get_output_details()

# Test the model on random input data.
input_data = np.array(np.random.random_sample(input_details[0]['shape']), dtype=np.float32)
interpreter.set_tensor(input_details[0]['index'], input_data)

interpreter.invoke()

tensors = interpreter.get_tensor(output_details[0]['index'])
print("Output:", tensors)

Advanced Usage

For more advanced usage, you might want to explore the following topics:

• TensorFlow Lite Model Optimization
• TensorFlow Lite Interpreter

Resources

• TensorFlow Lite Documentation
• TensorFlow Lite GitHub Repository

TensorFlow Lite Logo