wharu

automatic-mixed-precision-tutorials-pytorch

Automatic Mixed Precision Tutorials using pytorch. Based on PyTorch 1.6 Official Features, implement classification codebase using custom dataset.

Awesome-Skeleton-based-Action-Recognition

Skeleton-based Action Recognition

awkward-array

Manipulate arrays of complex data structures as easily as Numpy.

branchynet

cardioML

Arnaout Lab

CenterNet-1

Object detection, 3D detection, and pose estimation using center point detection:

CenterNet-better

An easy to understand and better performance version of CenterNet

CenterNetCPP

centerNet Caffe inference CPP

kaggle-rcic-1st

1st Place Solution for Kaggle Recursion Cellular Image Classification Challenge -- https://www.kaggle.com/c/recursion-cellular-image-classification/

python-is-cool

Cool Python features for machine learning that I used to be too afraid to use

wharu/automatic-mixed-precision-tutorials-pytorch

Automatic Mixed Precision Tutorials using pytorch. Based on PyTorch 1.6 Official Features, implement classification codebase using custom dataset.

wharu/branchynet

wharu/cardioML

Arnaout Lab

wharu/CenterNet-1

Object detection, 3D detection, and pose estimation using center point detection:

wharu/CenterNet-better

An easy to understand and better performance version of CenterNet

wharu/centerX

This repo is implemented based on detectron2 and centernet

wharu/CPlusPlus

最全面的 C++ 笔记

wharu/CS-Notes

:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计

wharu/cv-detect-robot

🔥🔥🔥🔥🔥🔥yolov5+YOLOX+yolo+tensorRT+ros+deepstream+jetson+nano+TX2+NX for High-performance deployment(高性能部署)

wharu/DCNv2

Deformable Convolutional Networks v2 (DCNv2) with Pytorch 1.8+ & JIT Compilation

wharu/deep-person-reid

Torchreid: Deep learning person re-identification in PyTorch.

wharu/DeepLearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06

wharu/deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

wharu/dissect

Code for the Proceedings of the National Academy of Sciences 2020 article, "Understanding the Role of Individual Units in a Deep Neural Network"

wharu/DreamDiffusion

Implementation of “DreamDiffusion: Generating High-Quality Images from Brain EEG Signals”

wharu/hands-on-transfer-learning-with-python

Deep learning simplified by transferring prior learning using the Python deep learning ecosystem

wharu/iMoCap

dataset for ECCV 2020 "Motion Capture from Internet Videos"

wharu/JSON2YOLO

Convert JSON datasets into YOLO (darknet) format.

wharu/LeetCode

:monkey:LeetCode、剑指Offer刷题笔记（C/C++、Python3实现）

wharu/MVision

机器人视觉 移动机器人 VS-SLAM ORB-SLAM2 深度学习目标检测 yolov3 行为检测 opencv PCL 机器学习 无人驾驶

wharu/pixloc

Back to the Feature: Learning Robust Camera Localization from Pixels to Pose

wharu/PyTorch-Networks

Pytorch implementation of cnn network

wharu/PyTorch-YOLOv3

Minimal PyTorch implementation of YOLOv3

wharu/pytorch_simple_CenterNet_45

A simple pytorch implementation of CenterNet (Objects as Points)

wharu/sobot-rimulator

Autonomous mobile robot simulator.

wharu/tide

A General Toolbox for Identifying Object Detection Errors

wharu/UCAS-AOD-benchmark

A benchmark of UCAS-AOD dataset.

wharu/waymo-open-dataset

Waymo Open Dataset

wharu/Yolo-Fastest

:zap: Yolo universal target detection model combined with EfficientNet-lite, the calculation amount is only 230Mflops(0.23Bflops), and the model size is 1.3MB

wharu/yolov3

YOLOv3 in PyTorch > ONNX > CoreML > iOS