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), ...
#人脸识别#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, o...
Real-Time Spatio-Temporally Localized Activity Detection by Tracking Body Keypoints
#计算机科学#Deep Learning Autonomous Car based on Raspberry Pi, SunFounder PiCar-V Kit, TensorFlow, and Google's EdgeTPU Co-Processor
#计算机科学#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) -> openvi...
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 ...
#计算机科学#Neuralet is an open-source platform for edge deep learning models on edge TPU, Jetson Nano, and more.
TensorFlow Lite, Coral Edge TPU samples (Python/C++, Raspberry Pi/Windows/Linux).
#计算机科学#Minimal-dependency Yolov5 and Yolov8 export and inference demonstration for the Google Coral EdgeTPU
WHENet - ONNX, OpenVINO, TFLite, TensorRT, EdgeTPU, CoreML, TFJS, YOLOv4/YOLOv4-tiny-3L
#人脸识别#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
Docker with Raspbian, SSH and the Coral USB Edge TPU libraries.
#计算机科学#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
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.