🤖 Project template for your next awesome AI project. 🦾

Related tags

Deep Learningmachine-learningnatural-language-processingaicomputer-visiondeep-learningbest-practicesproject-templateartificial-intelligencesoftware-engineeringpython-templatepytorch-template
Overview

🤖 AI Awesome Project Template

👋 Template author

You may want to adjust badge links in a README.md file.

ci-testing Open In Collab Code style: black license

💎 Installation with pip

Installation is as simple as running:

pip install git+https://github.com/wiktorlazarski/ai-awesome-project-template

⚙️ Setup for development

Before setting up a project, make sure that the setup.py script has all setup parameters adjusted and change an ai_awesome directory name to your project name. Also, if you want to use conda environment, you may want to change its name in a conda_env.yml file. Then, follow the instruction:

# Clone repo
git clone https://github.com/wiktorlazarski/ai-awesome-project-template.git

# Go to repo directory
cd ai-awesome-project-template

# (Optional) Create virtual environment
python -m venv venv
source ./venv/bin/activate

# Install project in editable mode
pip install -e .

# (Optional but recommended) Install pre-commit hooks to preserve code format consistency
pre-commit install

🐍 Setup for development with Anaconda or Miniconda

Before setting up a project, make sure that the setup.py script has all setup parameters adjusted and change an ai_awesome directory name to your project name. Additionally, you may want to change a default (ai_awesome_env) conda environment name in a conda_env.yml file. Then, follow the instruction:

# Clone repo
git clone https://github.com/wiktorlazarski/ai-awesome-project-template.git

# Go to repo directory
cd ai-awesome-project-template

# Create and activate conda environment
conda env create -f ./conda_env.yml
conda activate ai_awesome_env

# (Optional but recommended) Install pre-commit hooks to preserve code format consistency
pre-commit install

🤗 Happy coding !

Owner
Wiktor Łazarski
🤖👨‍🎓 AI engineer and AI student at Warsaw University of Technology
Wiktor Łazarski
GitHub Repository
Semi-supervised Transfer Learning for Image Rain Removal. In CVPR 2019.

Semi-supervised Transfer Learning for Image Rain Removal This package contains the Python implementation of "Semi-supervised Transfer Learning for Ima

Wei Wei 59 Dec 26, 2022
Official implementation of NeurIPS 2021 paper "Contextual Similarity Aggregation with Self-attention for Visual Re-ranking"

CSA: Contextual Similarity Aggregation with Self-attention for Visual Re-ranking PyTorch training code for CSA (Contextual Similarity Aggregation). We

Hui Wu 19 Oct 21, 2022
Code and results accompanying our paper titled Mixture Proportion Estimation and PU Learning: A Modern Approach at Neurips 2021 (Spotlight)

Mixture Proportion Estimation and PU Learning: A Modern Approach This repository is the official implementation of Mixture Proportion Estimation and P

Approximately Correct Machine Intelligence (ACMI) Lab 23 Dec 28, 2022
Deep Reinforcement Learning for Keras.

Deep Reinforcement Learning for Keras What is it? keras-rl implements some state-of-the art deep reinforcement learning algorithms in Python and seaml

Keras-RL 0 Dec 15, 2022
(CVPR 2022 - oral) Multi-View Depth Estimation by Fusing Single-View Depth Probability with Multi-View Geometry

Multi-View Depth Estimation by Fusing Single-View Depth Probability with Multi-View Geometry Official implementation of the paper Multi-View Depth Est

Bae, Gwangbin 138 Dec 28, 2022
Emotion classification of online comments based on RNN

emotion_classification Emotion classification of online comments based on RNN, the accuracy of the model in the test set reaches 99% data: Large Movie

1 Nov 23, 2021
Keras udrl - Keras implementation of Upside Down Reinforcement Learning

keras_udrl Keras implementation of Upside Down Reinforcement Learning This is me

Eder Santana 7 Jan 24, 2022
Towards Flexible Blind JPEG Artifacts Removal (FBCNN, ICCV 2021)

Towards Flexible Blind JPEG Artifacts Removal (FBCNN, ICCV 2021)

Jiaxi Jiang 282 Jan 02, 2023
Code base for reproducing results of I.Schubert, D.Driess, O.Oguz, and M.Toussaint: Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics. NeurIPS (2021)

Learning to Execute (L2E) Official code base for completely reproducing all results reported in I.Schubert, D.Driess, O.Oguz, and M.Toussaint: Learnin

3 May 18, 2022
The fastai deep learning library

Welcome to fastai fastai simplifies training fast and accurate neural nets using modern best practices Important: This documentation covers fastai v2,

fast.ai 23.2k Jan 07, 2023
Instance Semantic Segmentation List

Instance Semantic Segmentation List This repository contains lists of state-or-art instance semantic segmentation works. Papers and resources are list

bighead 87 Mar 06, 2022
Pytorch implementation of PCT: Point Cloud Transformer

PCT: Point Cloud Transformer This is a Pytorch implementation of PCT: Point Cloud Transformer.

Yi_Zhang 265 Dec 22, 2022
A Fast Sequence Transducer Implementation with PyTorch Bindings

transducer A Fast Sequence Transducer Implementation with PyTorch Bindings. The corresponding publication is Sequence Transduction with Recurrent Neur

Awni Hannun 184 Dec 18, 2022
Pytorch Implementation of "Diagonal Attention and Style-based GAN for Content-Style disentanglement in image generation and translation" (ICCV 2021)

DiagonalGAN Official Pytorch Implementation of "Diagonal Attention and Style-based GAN for Content-Style Disentanglement in Image Generation and Trans

32 Dec 06, 2022
Distance-Ratio-Based Formulation for Metric Learning

Distance-Ratio-Based Formulation for Metric Learning Environment Python3 Pytorch (http://pytorch.org/) (version 1.6.0+cu101) json tqdm Preparing datas

Hyeongji Kim 1 Dec 07, 2022
A simple PyTorch Implementation of Generative Adversarial Networks, focusing on anime face drawing.

AnimeGAN A simple PyTorch Implementation of Generative Adversarial Networks, focusing on anime face drawing. Randomly Generated Images The images are

Jie Lei 雷杰 1.2k Jan 03, 2023
The official implementation of the IEEE S&P`22 paper "SoK: How Robust is Deep Neural Network Image Classification Watermarking".

Watermark-Robustness-Toolbox - Official PyTorch Implementation This repository contains the official PyTorch implementation of the following paper to

49 Dec 19, 2022
The official implementation of Equalization Loss v1 & v2 (CVPR 2020, 2021) based on MMDetection.

The Equalization Losses for Long-tailed Object Detection and Instance Segmentation This repo is official implementation CVPR 2021 paper: Equalization

Jingru Tan 129 Dec 16, 2022
FedScale: Benchmarking Model and System Performance of Federated Learning

FedScale: Benchmarking Model and System Performance of Federated Learning (Paper) This repository contains scripts and instructions of building FedSca

268 Jan 01, 2023
Location-Sensitive Visual Recognition with Cross-IOU Loss

The trained models are temporarily unavailable, but you can train the code using reasonable computational resource. Location-Sensitive Visual Recognit

Kaiwen Duan 146 Dec 25, 2022