Pinned Repositories
AI-Expert-Roadmap
Roadmap to becoming an Artificial Intelligence Expert in 2020
build-tools
necessary build tools for the archiconda distribution
caffe
Caffe: a fast open framework for deep learning.
darknet
YOLOv4v / Scaled-YOLOv4 - Neural Networks for Object Detection (Windows and Linux version of Darknet )
Deep-Learning-Tensorflow2
基于Tensorflow2的深度学习开源书籍
Face_Recognition_with_jetson_TX2
Tensorflow implementation of Face Verification and Recognition using th on-board camera of TX2
Gesture-Classification-in-Real-Time
Gesture classification in real time using a CNN, dedicated for Antmicro's TX2/TX2i Deep Learning Kit.
IntelligentEdgeHOL
The IntelligentEdgeHOL walks through the process of deploying an IoT Edge module to an Nvidia Jetson Nano device to allow for detection of objects in YouTube videos, RTSP streams, or an attached web cam
jetracer
An autonomous AI racecar using NVIDIA Jetson Nano
yolov4-tiny-tensorrt
Got 100fps on TX2. Got 500fps on GeForce GTX 1660 Ti. Implement yolov4-tiny-tensorrt layer by layer using TensorRT API. If the project is useful to you, please Star it.
wuzhishiwo's Repositories
wuzhishiwo/yolov4-tiny-tensorrt
Got 100fps on TX2. Got 500fps on GeForce GTX 1660 Ti. Implement yolov4-tiny-tensorrt layer by layer using TensorRT API. If the project is useful to you, please Star it.
wuzhishiwo/AI-Expert-Roadmap
Roadmap to becoming an Artificial Intelligence Expert in 2020
wuzhishiwo/caffe
Caffe: a fast open framework for deep learning.
wuzhishiwo/darknet
YOLOv4v / Scaled-YOLOv4 - Neural Networks for Object Detection (Windows and Linux version of Darknet )
wuzhishiwo/Deep-Learning-Tensorflow2
基于Tensorflow2的深度学习开源书籍
wuzhishiwo/Gesture-Classification-in-Real-Time
Gesture classification in real time using a CNN, dedicated for Antmicro's TX2/TX2i Deep Learning Kit.
wuzhishiwo/IntelligentEdgeHOL
The IntelligentEdgeHOL walks through the process of deploying an IoT Edge module to an Nvidia Jetson Nano device to allow for detection of objects in YouTube videos, RTSP streams, or an attached web cam
wuzhishiwo/jetracer
An autonomous AI racecar using NVIDIA Jetson Nano
wuzhishiwo/jetson-inference
Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.
wuzhishiwo/keras_onnx_tx2
Deploy trained yolo3 on TX2 for multi-stream video processing
wuzhishiwo/learngit
wuzhishiwo/ncnn
ncnn is a high-performance neural network inference framework optimized for the mobile platform
wuzhishiwo/onnx-tensorrt
ONNX-TensorRT: TensorRT backend for ONNX
wuzhishiwo/ORB_SLAM3
ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM
wuzhishiwo/PPG-Synthesis
PPGSynth: An innovative toolbox for synthesizing regular and irregular photoplethysmography waveforms
wuzhishiwo/Python-100-Days
Python - 100天从新手到大师
wuzhishiwo/Ros
机器人操作系统ROS 语音识别 语义理解 视觉控制 gazebo仿真 雷达建图导航
wuzhishiwo/ros_basic_tutorials
ROS基础精讲系列视频课程
wuzhishiwo/Tengine
Tengine is a lite, high performance, modular inference engine for embedded device
wuzhishiwo/tensorflow-yolov3
🔥 TensorFlow Code for technical report: "YOLOv3: An Incremental Improvement"
wuzhishiwo/TensorRT
TensorRT is a C++ library for high performance inference on NVIDIA GPUs and deep learning accelerators.
wuzhishiwo/tensorrt-yolov4
based on CaoWGG/TensorRT-YOLOv4, this branch made few changes to support tensorrt-7.1.0, cuda-10.2 and cudnn-8.0, which runs on a tx2 board with jetpack4.4dp installed.
wuzhishiwo/tensorrt_demos
TensorRT YOLOv4, YOLOv3, SSD, MTCNN, and GoogLeNet
wuzhishiwo/tensorrtx
Implementation of popular deep learning networks with TensorRT network definition API
wuzhishiwo/test
learning git and github
wuzhishiwo/tf_to_trt_image_classification
Image classification with NVIDIA TensorRT from TensorFlow models.
wuzhishiwo/tf_trt_models
TensorFlow object detection models accelerated with NVIDIA TensorRT (TF-TRT)
wuzhishiwo/vilib
CUDA Visual Library by RPG
wuzhishiwo/yolo-tensorrt
Support Yolov5s,m,l,x .darknet -> tensorrt. Yolov4 Yolov3 use raw darknet *.weights and *.cfg fils. If the wrapper is useful to you,please Star it.
wuzhishiwo/yolov5
YOLOv5 in PyTorch > ONNX > CoreML > iOS