Detectron2-FC a fast construction platform of neural network algorithm based on detectron2

Overview

What is Detectron2-FC

Detectron2-FC a fast construction platform of neural network algorithm based on detectron2. We have been working hard in two directions:

1)Quickly build complex deep learning network algorithm for training and prediction;

2)It can quickly build deep learning algorithms for almost all tasks.

Fortunately, detectron2 points out the direction for us. It builds a very convenient algorithm building platform based on pytorch, which can quickly reproduce the latest algorithms. However, detectron2 can only build algorithms with few tasks such as target detection and segmentation. For example, simple image classification cannot find convenience on detectron2. Therefore, on the basis of detectron2, we continue to enrich the functions of detectron2 to make it suitable for image classification, prediction, meta learning and other tasks.

Installation tutorial

See https://detectron2.readthedocs.io/en/latest/tutorials/install.html. The construction environment is as follows:

Ubuntu20.04

CUDA10.1

Pytorch1.8.1

Existing examples

Image classification

Icron-water:https://github.com/dongdongdong1217/Detectron2-FC/tree/main/tools#readme

Object detection and image segmentation

Detectron2's own algorithm see: https://github.com/facebookresearch/detectron2/blob/main/MODEL_ZOO.md

Few-shot object detection

Owner
董晋宗
Bug engineer
董晋宗
Official code for ICCV2021 paper "M3D-VTON: A Monocular-to-3D Virtual Try-on Network"

M3D-VTON: A Monocular-to-3D Virtual Try-On Network Official code for ICCV2021 paper "M3D-VTON: A Monocular-to-3D Virtual Try-on Network" Paper | Suppl

109 Dec 29, 2022
Meta Representation Transformation for Low-resource Cross-lingual Learning

MetaXL: Meta Representation Transformation for Low-resource Cross-lingual Learning This repo hosts the code for MetaXL, published at NAACL 2021. [Meta

Microsoft 36 Aug 17, 2022
This is code of book "Learn Deep Learning with PyTorch"

深度学习入门之PyTorch Learn Deep Learning with PyTorch 非常感谢您能够购买此书,这个github repository包含有深度学习入门之PyTorch的实例代码。由于本人水平有限,在写此书的时候参考了一些网上的资料,在这里对他们表示敬意。由于深度学习的技术在

Xingyu Liao 2.5k Jan 04, 2023
A machine learning library for spiking neural networks. Supports training with both torch and jax pipelines, and deployment to neuromorphic hardware.

Rockpool Rockpool is a Python package for developing signal processing applications with spiking neural networks. Rockpool allows you to build network

SynSense 21 Dec 14, 2022
A numpy-based implementation of RANSAC for fundamental matrix and homography estimation. The degeneracy updating and local optimization components are included and optional.

Description A numpy-based implementation of RANSAC for fundamental matrix and homography estimation. The degeneracy updating and local optimization co

AoxiangFan 9 Nov 10, 2022
A tool to visualise the results of AlphaFold2 and inspect the quality of structural predictions

AlphaFold Analyser This program produces high quality visualisations of predicted structures produced by AlphaFold. These visualisations allow the use

Oliver Powell 3 Nov 13, 2022
DSEE: Dually Sparsity-embedded Efficient Tuning of Pre-trained Language Models

DSEE Codes for [Preprint] DSEE: Dually Sparsity-embedded Efficient Tuning of Pre-trained Language Models Xuxi Chen, Tianlong Chen, Yu Cheng, Weizhu Ch

VITA 4 Dec 27, 2021
The source code of the paper "SHGNN: Structure-Aware Heterogeneous Graph Neural Network"

SHGNN: Structure-Aware Heterogeneous Graph Neural Network The source code and dataset of the paper: SHGNN: Structure-Aware Heterogeneous Graph Neural

Wentao Xu 7 Nov 13, 2022
Stochastic Extragradient: General Analysis and Improved Rates

Stochastic Extragradient: General Analysis and Improved Rates This repository is the official implementation of the paper "Stochastic Extragradient: G

Hugo Berard 4 Nov 11, 2022
Implementation of the method described in the Speech Resynthesis from Discrete Disentangled Self-Supervised Representations.

Speech Resynthesis from Discrete Disentangled Self-Supervised Representations Implementation of the method described in the Speech Resynthesis from Di

4 Mar 11, 2022
A resource for learning about ML, DL, PyTorch and TensorFlow. Feedback always appreciated :)

A resource for learning about ML, DL, PyTorch and TensorFlow. Feedback always appreciated :)

Aladdin Persson 4.7k Jan 08, 2023
A tensorflow model that predicts if the image is of a cat or of a dog.

Quick intro Hello and thank you for your interest in my project! This is the backend part of a two-repo application. The other part can be found here

Tudor Matei 0 Mar 08, 2022
CLIP (Contrastive Language–Image Pre-training) for Italian

Italian CLIP CLIP (Radford et al., 2021) is a multimodal model that can learn to represent images and text jointly in the same space. In this project,

Italian CLIP 114 Dec 29, 2022
NeurIPS workshop paper 'Counter-Strike Deathmatch with Large-Scale Behavioural Cloning'

Counter-Strike Deathmatch with Large-Scale Behavioural Cloning Tim Pearce, Jun Zhu Offline RL workshop, NeurIPS 2021 Paper: https://arxiv.org/abs/2104

Tim Pearce 169 Dec 26, 2022
Use deep learning, genetic programming and other methods to predict stock and market movements

StockPredictions Use classic tricks, neural networks, deep learning, genetic programming and other methods to predict stock and market movements. Both

Linda MacPhee-Cobb 386 Jan 03, 2023
Code release for our paper, "SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo"

SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo Thomas Kollar, Michael Laskey, Kevin Stone, Brijen Thananjeyan

68 Dec 14, 2022
Sound and Cost-effective Fuzzing of Stripped Binaries by Incremental and Stochastic Rewriting

StochFuzz: A New Solution for Binary-only Fuzzing StochFuzz is a (probabilistically) sound and cost-effective fuzzing technique for stripped binaries.

Zhuo Zhang 164 Dec 05, 2022
Offical code for the paper: "Growing 3D Artefacts and Functional Machines with Neural Cellular Automata" https://arxiv.org/abs/2103.08737

Growing 3D Artefacts and Functional Machines with Neural Cellular Automata Video of more results: https://www.youtube.com/watch?v=-EzztzKoPeo Requirem

Robotics Evolution and Art Lab 51 Jan 01, 2023
Semi-SDP Semi-supervised parser for semantic dependency parsing.

Semi-SDP Semi-supervised parser for semantic dependency parsing. This repo contains the code used for the semi-supervised semantic dependency parser i

12 Sep 17, 2021
ICLR 2021 i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning

Introduction PyTorch code for the ICLR 2021 paper [i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning]. @inproceedings{lee2021i

Kibok Lee 68 Nov 27, 2022