Watch qihangwang/AutoAugment

Unofficial implementation of the ImageNet, CIFAR 10 and SVHN Augmentation Policies learned by AutoAugment using pillow

Watch qihangwang/charts

Watch qihangwang/ludwig

Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code.

Watch qihangwang/SwiftLaTeX

SwiftLaTeX, a WYSIWYG Browser-based LaTeX Editor

Watch qihangwang/kubeflow-manifests

kubeflow国内一键安装文件

Watch qihangwang/pygalmesh

A Python frontend to CGAL's 3D mesh generators.

Watch qihangwang/learning_pytorch

learning of pytorch

Watch qihangwang/PyTorch_Semantic_Segmentation

Implement some models of RGB/RGBD semantic segmentation in PyTorch, easy to run. Such as FCN, RefineNet, PSPNet, RDFNet, 3DGNN, PointNet, DeepLab V3, DeepLab V3 plus, DenseASPP, FastFCN

Watch qihangwang/fcn

free connect your private network from anywhere

Watch qihangwang/deeplearning-classification-with-tensorflow

We realized an integrated classification project from training from scratch to predict utilizing classical networks with tensorflow, including VGG16, ResNet series. With this repository, you can train your own data and realize prediction.