A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.

Self-hosted, local only NVR and AI Computer Vision software. With features such as object detection, motion detection, face recognition and more, it gives you the power to keep an eye on your home, office or any other place you want to monitor.

Real-Time Spatio-Temporally Localized Activity Detection by Tracking Body Keypoints

Human Pose Detection on EdgeTPU

Coral issue tracker (and legacy Edge TPU API source)

Deep Learning Autonomous Car based on Raspberry Pi, SunFounder PiCar-V Kit, TensorFlow, and Google's EdgeTPU Co-Processor

Sample projects for TensorFlow Lite in C++ with delegates such as GPU, EdgeTPU, XNNPACK, NNAPI

Dual Edge TPU Adapter to use it on a system with single PCIe port on m.2 A/B/E/M slot

This script converts the ONNX/OpenVINO IR model to Tensorflow's saved_model, tflite, h5, tfjs, tftrt(TensorRT), CoreML, EdgeTPU, ONNX and pb. PyTorch (NCHW) -> ONNX (NCHW) -> OpenVINO (NCHW) -> openvino2tensorflow -> Tensorflow/Keras (NHWC/NCHW) -> TFLite (NHWC/NCHW). And the conversion from .pb to saved_model and from saved_model to .pb and from .pb to .tflite and saved_model to .tflite and saved_model to onnx. Support for building environments with Docker. It is possible to directly access the host PC GUI and the camera to verify the operation. NVIDIA GPU (dGPU) support. Intel iHD GPU (iGPU) support.

Generate saved_model, tfjs, tf-trt, EdgeTPU, CoreML, quantized tflite, ONNX, OpenVINO, Myriad Inference Engine blob and .pb from .tflite. Support for building environments with Docker. It is possible to directly access the host PC GUI and the camera to verify the operation. NVIDIA GPU (dGPU) support. Intel iHD GPU (iGPU) support. Supports inverse quantization of INT8 quantization model.

Neuralet is an open-source platform for edge deep learning models on edge TPU, Jetson Nano, and more.

JeVois smart machine vision framework

Adds support to Frigate NVR to run YOLO v9 object detection models on Google Coral TPU hardware

TensorFlow Lite, Coral Edge TPU samples (Python/C++, Raspberry Pi/Windows/Linux).

Minimal-dependency Yolov5 and Yolov8 export and inference demonstration for the Google Coral EdgeTPU

Cat with prey detection on Raspberry Pi. Lock cat pet flap if prey is detected. Object detection implemented in TFLite with ImageNet v1 SSD. Inference on EdgeTPU (Google Coral USB). Stores images on AWS S3 and sends notifications to iOS device.

EdgeTPU support for other platforms, specifically Raspberry Pi Zero

Enabling tinygrad compatibility with the Google Edge TPU

WHENet - ONNX, OpenVINO, TFLite, TensorRT, EdgeTPU, CoreML, TFJS, YOLOv4/YOLOv4-tiny-3L

Low power smart camera (3D printed) based on the Raspberry Pi Zero W and Google Coral EdgeTPU

ROS package for Coral Edge TPU USB Accelerator

Motion transfer booth for a 1 hour everybody dance now video generation using EdgeTPU and Tensorflow 2.0

This repo contains the colab for my ssdlite mobiledet model retrain tutorial

TensorFlow Lite Erlang bindings with optional EdgeTPU support.

Docker with Raspbian, SSH and the Coral USB Edge TPU libraries.

Neuralet edge deep learning models library. Neuralet is an open-source platform for edge deep learning models on GPU, TPU, and more.

Experimental Kubernetes Device Plugin for Coral Edge TPU

This project is developed for smart aquaculture. We use a camera to capture pictures of fishes in the tank. A deep neural network (MobileNet) is applied to recognize the images to identify the situation of fishes in the tank. EdgeTPU is used for edge computing. We also monitor the water quality by some environmental sensors. All the information is integrated into a website constructed by Laravel, and a Linebot is used to deliver information on mobile phones.Four undergraduate students develop this project from the Department of Management Information Systems (MIS), National Pingtung University of Science and Technology (NPUST), Taiwan.

minimal example with native build instructions

Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation. Intel iHD GPU (iGPU) support. NVIDIA GPU (dGPU) support.