Raspberry pi TensorFlow-lite Object detection How to use TensorFlow Lite object detection models on the Raspberry Pi. TensorFlow Lite is an optimized framework for deploying lightweight deep learning models on resource-constrained edge devices. TensorFlow Lite models have faster inference time and require less processing power, so they can be used to obtain faster performance in realtime applications. System Requirements Hardware · Raspberry Pi Board (4B , 3B+) · IP Camera, USB Camera or Pi Camera · SD Card 32GB · 5V DC. 2A Power Supply Software · OS Raspbien 10 ( buster ) · Python 3.7.2 · Tensorflow lite 1.14.0 · OpenCV 4.0.0 Machine Learning Model : MobileNet SSD V2 Quantised Source Code https://github.com/EdjeElectronics/TensorFlow-Lite-Object-Detection-on-Android-and-Raspberry-Pi Reference Install Tensorflow on Raspberry pi https://www.tensorflow.org/install/source_rpi Tensorflow Model Zoo https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md How to Run TensorFlow Lite Object Detection https://github.com/EdjeElectronics/TensorFlow-Lite-Object-Detection-on-Android-and-Raspberry-Pi/blob/master/Raspberry_Pi_Guide.md