SHUNFENG66's repositories
v2ray-core
A platform for building proxies to bypass network restrictions.
pedestrian-attribute-recognition-pytorch
A simple baseline for pedestrian attribute recognition in surveillance scenarios
pretrained-models.pytorch
Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.
Person_reID_baseline_pytorch
Pytorch implement of Person re-identification baseline. Tutorial 👉https://github.com/layumi/Person_reID_baseline_pytorch/tree/master/tutorial
MMdnn
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
imgclsmob
Sandbox for training large-scale image classification networks for embedded systems
glow
Compiler for Neural Network hardware accelerators
DANet
Dual Attention Network for Scene Segmentation
MnasNet-caffe
A caffe implementation of Mnasnet: MnasNet: Platform-Aware Neural Architecture Search for Mobile.
caffe-1
Caffe: a fast open framework for deep learning.
caffe
This fork of BVLC/Caffe is dedicated to improving performance of this deep learning framework when running on CPU, in particular Intel® Xeon processors (HSW+) and Intel® Xeon Phi processors
DALI
A library containing both highly optimized building blocks and an execution engine for data pre-processing in deep learning applications
tensorflow
Computation using data flow graphs for scalable machine learning
MXNet-Gluon-SyncBN
MXNet Gluon Synchronized Batch Normalization Preview
abu
阿布量化交易系统(股票，期权，期货，比特币，机器学习) 基于python的开源量化交易，量化投资架构
ZQCNN-v0.0
一个测试版
mini-caffe
Minimal runtime core of Caffe, Forward only, GPU support and Memory efficiency.
VehicleKeyPointData
Annotations of key point location and vehicle orientation for VeRi-776 dataset. ICCV'17
cnn-models
ImageNet pre-trained models with batch normalization for the Caffe framework
softmaxfocalloss
the loss function in Aritcal ‘Focal Loss for Dense Object Detection‘’
MCNet
Learning a multi-center convolutional network for unconstrained face alignment
tripletloss
face-recongnition facenet triplet-loss
Dense-Landmark-Detection
Learning Deep Representation from Coarse to Fine for Face Alignment