503 Open source projects that are alternatives of or similar to Stochastic-Quantization

Training & Quantization of embedded friendly Deep Learning / Machine Learning / Computer Vision models

Xception implemented with caffe

Evaluation of the CNN design choices performance on ImageNet-2012.

Tutorial for computer vision and machine learning in PHP 7/8 by opencv (installation + examples + documentation)

Sandbox for training deep learning networks

Open Set Recognition

A repository that shares tuning results of trained models generated by TensorFlow / Keras. Post-training quantization (Weight Quantization, Integer Quantization, Full Integer Quantization, Float16 Quantization), Quantization-aware training. TensorFlow Lite. OpenVINO. CoreML. TensorFlow.js. TF-TRT. MediaPipe. ONNX. [.tflite,.h5,.pb,saved_model,tfjs,tftrt,mlmodel,.xml/.bin, .onnx]

train resnet on imagenet from scratch with caffe

ImageNet pre-trained models with batch normalization for the Caffe framework

A collection of SOTA Image Classification Models in PyTorch

DenseNet Caffe Models, converted from https://github.com/liuzhuang13/DenseNet

Caffe Implementation of Google's MobileNets (v1 and v2)

PPL Quantization Tool (PPQ) is a powerful offline neural network quantization tool.

Caffe models (including classification, detection and segmentation) and deploy files for famouse networks

A Caffe Re-Implementation of SENet

PyTorch Project Specification.

Multiple ColorChecker Detection. This code implements a multiple colorChecker detection method, as described in the paper Fast and Robust Multiple ColorChecker Detection.

No description or website provided.

Caffe implementation for "Guided Optical Flow Learning"

Intel® Neural Compressor (formerly known as Intel® Low Precision Optimization Tool), targeting to provide unified APIs for network compression technologies, such as low precision quantization, sparsity, pruning, knowledge distillation, across different deep learning frameworks to pursue optimal inference performance.

📹 一个短视频APP视频内容安全审核的思路调研及实现汇总

XNOR-Net, CUDNN5 supported version of XNOR-Net-caffe: https://github.com/loswensiana/BWN-XNOR-caffe

Implemetation of Pyramid Scene Parsing Network in Pytorch

A small tool to dump Caffe's *.caffemodel to JSON for inspection

A Caffe Implementation of SRGAN

The SimNets Architecture's Implementation in Caffe

No description or website provided.

ImageNet model implemented using the Keras Functional API

arcface and retinaface model convert mxnet to onnx.

pytorch to caffe by onnx

No description or website provided.

Tool to evaluate deep-learning detection and segmentation models, and to create datasets

crnn.caffe

针对pytorch模型的自动化模型结构分析和修改工具集，包含自动分析模型结构的模型压缩算法库

Semantic Image Segmentation by Scale-Adaptive Networks (TIP 2019)

Transfer Learning with DCNNs (DenseNet, Inception V3, Inception-ResNet V2, VGG16) for skin lesions classification

ImageNet pre-trained SharpPeleeNet can be used in real-time Semantic Segmentation/Objects Detection

Depth Map Super-Resolution by Deep Multi-Scale Guidance, ECCV 2016

Scripts to work with LMDB + PyTorch for Imagenet training

Mxnet2Caffe_Tensor RT

State-of-the-art method for large-scale ANN search as of Oct 2016. Presented at ECCV 16.

在caffe应用到工程实现时，为了方便系统安装，需要尽可能减少软件的依赖库。 本项目以bash shell/PowerShell脚本实现将caffe依赖的所有第三方库与caffe静态编译一起，以满足全静态编译的要求。 通过本项目提供的脚本生成的caffe编译环境不需要在系统安装任何第三方库和软件，就可以自动完成caffe项目静态编译. 目前在centos6.5/ubuntu16/win7/win10上测试通过,windows上VS2013,VS2015,MinGW 5.2.0编译通过

[ECCV 2020] Scale Adaptive Network: Learning to Learn Parameterized Classification Networks for Scalable Input Images

🎯 保姆级深度学习从入门到放弃 🤪 🤪

Caffe Wide-Residual-Network (WRN) Generator

Fast Image Retrieval (FIRe) is an open source project to promote image retrieval research. It implements most of the major binary hashing methods to date, together with different popular backbone networks and public datasets.

Paper list for neural network compression techniques

VGG16 architecture with BatchNorm

Re-implementation of tripletloss function in FaceNet

PyTorch implementation of EfficientNetV2 family

73.6% GhostNet 1.0x pre-trained model on ImageNet

Pytorch implementation of "All Tokens Matter: Token Labeling for Training Better Vision Transformers"

Train faster rcnn on imagine dataset, related blog post: https://andrewliao11.github.io/object/detection/2016/07/23/detection/

Parametric Contrastive Learning (ICCV2021)

Self-distillation with Batch Knowledge Ensembling Improves ImageNet Classification

Convert image folder to lmdb, adapted from Efficient-PyTorch

The code for preparing the training data for crowd counting / segmentation algorithm.

Moore Machine Networks (MMN): Learning Finite-State Representations of Recurrent Policy Networks

Public scenarios to crowdsource experiments (such as DNN crowd-benchmarking and crowd-tuning) using Collective Knowledge Framework across diverse mobile devices provided by volunteers. Results are continuously aggregated at the open repository of knowledge:

Semantically consistent regularizer for zero-shot learning