650 Open source projects that are alternatives of or similar to Selecsls Pytorch

Nearly Perfect & Easily Understandable PyTorch Implementation of SKNet

Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.

Autoencoder trained on ImageNet Using Torch 7

Training Low-bits DNNs with Stochastic Quantization

No description or website provided.

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

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

Pytorch implementation of "Compact Global Descriptor for Neural Networks" (CGD).

Group Fisher Pruning for Practical Network Compression(ICML2021)

FasterAI: A repository for making smaller and faster models with the FastAI library.

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.

PyTorch implementation of EfficientNetV2 family

A package to make do Network Slimming a little easier

Bottleneck Transformers for Visual Recognition

DroNet: Efficient convolutional neural network detector for Real-Time UAV applications

ImageNet model implemented using the Keras Functional API

No description or website provided.

Scripts to work with LMDB + PyTorch for Imagenet training

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

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

Implement of Dynamic Model Pruning with Feedback with pytorch

73.6% GhostNet 1.0x pre-trained model on ImageNet

Parametric Contrastive Learning (ICCV2021)

Neural network model repository for highly sparse and sparse-quantized models with matching sparsification recipes

A research library for pytorch-based neural network pruning, compression, and more.

[ICLR 2021] "GANs Can Play Lottery Too" by Xuxi Chen, Zhenyu Zhang, Yongduo Sui, Tianlong Chen

Learning both Weights and Connections for Efficient Neural Networks https://arxiv.org/abs/1506.02626

latest version of original laguna source, with a handful fixes for modern compilers and systems

Prunable nn layers for pytorch.

Xception implemented with caffe

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

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.

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/

iOS efficient AOP Library using C++ and libffi

Self-distillation with Batch Knowledge Ensembling Improves ImageNet Classification

Java Implementation of EXI

🤖 Cozmo the Robot recognizes objects with TensorFlow

An Innovative, Fast Transpiler for ECMAScript 2015 and later

A PyTorch implementation of the iterative pruning method described in Han et. al. (2015)

A simple, extensible and efficient programming language based on C and Python

JSON parser for mIRC

[IEEE Access] "Head Network Distillation: Splitting Distilled Deep Neural Networks for Resource-constrained Edge Computing Systems" and [ACM MobiCom HotEdgeVideo 2019] "Distilled Split Deep Neural Networks for Edge-assisted Real-time Systems"

custom implementation alexnet with tensorflow

Fast OpenGL Mathematics (GLM) for Python

Nested Hierarchical Transformer https://arxiv.org/pdf/2105.12723.pdf

EfficientNetV2 implementation using PyTorch

(CVPR 2021, Oral) Dynamic Slimmable Network

End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow

DAWNBench: An End-to-End Deep Learning Benchmark and Competition