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TensorFlow_Lite_SSD_RPi_64-bits

TensorFlow Lite SSD running at 24 FPS on a bare Raspberry Pi 4 64-OS

A fast C++ implementation of TensorFlow Lite on a bare Raspberry Pi 4 64-bit OS. Once overclocked to 1925 MHz, the app runs a whopping 24 FPS! Without any hardware accelerator, just you and your Pi.

https://arxiv.org/abs/1611.10012 Training set: COCO Size: 300x300 Frame rate V1 Lite : 28 FPS (RPi 4 @ 1925 MHz - 64 bits Bullseye OS) Frame rate V1 Lite : 17 FPS (RPi 4 @ 2000 MHz - 32 bits OS) see 32-OS Special made for a Raspberry Pi 4 see Q-engineering deep learning examples To extract and run the network in Code::Blocks $ mkdir MyDir $ cd MyDir $ wget https://github.com/Qengineering/TensorFlow_Lite_SSD_RPi_64-bits/archive/refs/heads/master.zip $ unzip -j master.zip Remove master.zip and README.md as they are no longer needed. $ rm master.zip $ rm README.md Your MyDir folder must now look like this: James.mp4 COCO_labels.txt detect.tflite TestTensorFlow_Lite.cpb MobileNetV1.cpp Run TestTensorFlow_Lite.cpb with Code::Blocks. More info or if you want to connect a camera to the app, follow the instructions at Hands-On. I fact you can run this example on any aarch64 Linux system. See the movie at: https://vimeo.com/393889226