motono0223

motono0223's Stars

• Lightning-AI/pytorch-lightning

  Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.

  Language:Python28.3k2507.1k3.4k

• matterport/Mask_RCNN

  Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

  Language:Python24.7k5822.8k11.7k

• aleju/imgaug

  Image augmentation for machine learning experiments.

  Language:Python14.4k2295172.4k

• google-research/vision_transformer

  Language:Jupyter Notebook10.3k1062071.3k

• qubvel-org/segmentation_models.pytorch

  Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.

  Language:Python9.6k816471.7k

• lukemelas/EfficientNet-PyTorch

  A PyTorch implementation of EfficientNet

  Language:Python7.9k1322961.5k

• mikel-brostrom/boxmot

  BoxMOT: pluggable SOTA tracking modules for segmentation, object detection and pose estimation models

  Language:Python6.7k601.1k1.7k

• AntixK/PyTorch-VAE

  A Collection of Variational Autoencoders (VAE) in PyTorch.

  Language:Python6.6k43851.1k

• google/automl

  Google Brain AutoML

  Language:Jupyter Notebook6.2k1518861.5k

• jmportilla/Python-for-Algorithms--Data-Structures--and-Interviews

  Files for Udemy Course on Algorithms and Data Structures

  Language:Jupyter Notebook2.5k151122.4k

• qubvel/efficientnet

  Implementation of EfficientNet model. Keras and TensorFlow Keras.

  Language:Python2.1k38115471

• nagadomi/lbpcascade_animeface

  A Face detector for anime/manga using OpenCV

  1.9k5810294

• ronghuaiyang/arcface-pytorch

  Language:Python1.7k19114392

• SwinTransformer/Swin-Transformer-Semantic-Segmentation

  This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Semantic Segmentation.

  Language:Python1.2k1291222

• abhishekkrthakur/tez

  Tez is a super-simple and lightweight Trainer for PyTorch. It also comes with many utils that you can use to tackle over 90% of deep learning projects in PyTorch.

  Language:Python1.2k1741145

• agconti/kaggle-titanic

  A tutorial for Kaggle's Titanic: Machine Learning from Disaster competition. Demonstrates basic data munging, analysis, and visualization techniques. Shows examples of supervised machine learning techniques.

  Language:Jupyter Notebook8715111676

• YutaroOgawa/pytorch_advanced

  書籍「つくりながら学ぶ! PyTorchによる発展ディープラーニング」の実装コードを配置したリポジトリです

  Language:Jupyter Notebook84421214334

• rstrudel/segmenter

  [ICCV2021] Official PyTorch implementation of Segmenter: Transformer for Semantic Segmentation

  Language:Python8402270174

• gzerveas/mvts_transformer

  Multivariate Time Series Transformer, public version

  Language:Python760368172

• faustomorales/vit-keras

  Keras implementation of ViT (Vision Transformer)

  Language:Python33883880

• ChristofHenkel/kaggle-landmark-2021-1st-place

  Language:Jupyter Notebook33618941

• 4uiiurz1/keras-arcface

  Keras implementation of ArcFace, CosFace, and SphereFace

  Language:Python282113265

• vincent-leguen/PhyDNet

  Code for our CVPR 2020 paper "Disentangling Physical Dynamics from Unknown Factors for UnsupervisedVideo Prediction"

  Language:Python17953450

• Fraser-Greenlee/transformer-vae

  A library for making Transformer Variational Autoencoders. (Extends the Huggingface/transformers library.)

  Language:Python1326312

• ashawkey/volumentations

  3D volume data augmentation package inspired by albumentations

  Language:Python795113

• agconti/KaggleAux

  A collection of statistical tools to aid Data Science competitors in Kaggle Competitions.

  Language:Python6381021

• lucidfrontier45/PyTorch-Book

  33643

• deephub-ai/torch-handle

  TorchHandle makes your PyTorch development more efficient and make you use PyTorch more comfortable

  Language:Python19205

• ChristofHenkel/hyperbolic-image-embeddings

  Supplementary code for the paper "Hyperbolic Image Embeddings".

  Language:Python5100

• ChristofHenkel/google-images-download

  Python Script to download hundreds of images from 'Google Images'. It is a ready-to-run code!

  Language:Python2101