Katsuya Hyodo's Projects
Real-time Object Detection for Streaming Perception, CVPR 2022
A very simple tool to swap connections between output and input variables in an ONNX graph. Simple Variable Switch for ONNX.
SwinIR: Image Restoration Using Swin Transformer (official repository)
UbuntuへのTBB(Intel Threading Building Blocks)導入用debパッケージ保管庫
RaspberryPi3へのTBB(Intel Threading Building Blocks)導入用debパッケージ保管庫
An Open Source Machine Learning Framework for Everyone
Prebuilt binary with Tensorflow Lite enabled. For RaspberryPi / Jetson Nano. Support for custom operations in MediaPipe. XNNPACK, XNNPACK Multi-Threads, FlexDelegate.
TensorFlow implementation of ENet (Support for GPU/CPU mode, slimming of meta file and pb file generation) I added a correspondence to CPU mode and Freeze Graph, RaspberryPi correspondence to kwotsin/TensorFlow-ENet. Tensorflow 1.11.0
Tensorflow v1.11.0 and Python3.x compatible of ENet. GPU/CPU.
TensorFlow for Arm
Prebuilt binary for TensorFlowLite's standalone installer. For RaspberryPi. A very lightweight installer. I provide a FlexDelegate, MediaPipe Custom OP and XNNPACK enabled binary.
This is a repository for checking the operation of Flex Delegate of Tensorflow.
Implementation of UNet by Tensorflow Lite. Semantic segmentation without using GPU with RaspberryPi + Python. In order to maximize the learning efficiency of the model, this learns only the "Person" class of VOC2012. And Comparison with ENet.
TensorFlow models accelerated with NVIDIA TensorRT
This tool displays tflite signatures and rewrites the input/output OP name to the name of the signature. There is no need to install TensorFlow or TFLite.
Convert tflite to JSON and make it editable in the IDE. It also converts the edited JSON back to tflite binary.
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.
GPU accelerated deep learning inference applications using TensorflowLite GPUDelegate / TensorRT
Challenge the marginal performance of YoloV2 + Neural Compute Stick + RaspberryPi YoloV2+Neural Compute Stick(NCS)+Raspberry Piの限界性能に挑戦
TopFormer: Token Pyramid Transformer for Mobile Semantic Segmentation, CVPR2022
PyTorch-based implementations of short-time Fourier transform
Edge TPU Accelerator / Multi-TPU + MobileNet-SSD v2 + Python + Async + LattePandaAlpha/RaspberryPi3/LaptopPC
Edge TPU Accelerator / Multi-TPU / Multi-Model + Posenet/DeeplabV3/MobileNet-SSD + Python + Sync / Async + LaptopPC / RaspberryPi
Tensorflow implementation of CNN described in https://arxiv.org/abs/1806.09594
Official Pytorch Code for the paper TransWeather
TVM build and run test environment
PyTorch implementation for "A Wavelet-based Dual-stream Network for Underwater Image Enhancement", ICASSP, 2022.
Repository for URDF parsing code