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
Image morphing without reference points by applying warp maps and optimizing over them.

Differentiable Morphing Image morphing without reference points by applying warp maps and optimizing over them. Differentiable Morphing is machine lea

Alex K 380 Dec 19, 2022
SMCA replication There are no extra compiled components in SMCA DETR and package dependencies are minimal

Usage There are no extra compiled components in SMCA DETR and package dependencies are minimal, so the code is very simple to use. We provide instruct

22 May 06, 2022
SC-GlowTTS: an Efficient Zero-Shot Multi-Speaker Text-To-Speech Model

SC-GlowTTS: an Efficient Zero-Shot Multi-Speaker Text-To-Speech Model Edresson Casanova, Christopher Shulby, Eren Gölge, Nicolas Michael Müller, Frede

Edresson Casanova 92 Dec 09, 2022
Sequence-tagging using deep learning

Classification using Deep Learning Requirements PyTorch version = 1.9.1+cu111 Python version = 3.8.10 PyTorch-Lightning version = 1.4.9 Huggingface

Vineet Kumar 2 Dec 20, 2022
This is the source code for the experiments related to the paper Unsupervised Audio Source Separation Using Differentiable Parametric Source Models

Unsupervised Audio Source Separation Using Differentiable Parametric Source Models This is the source code for the experiments related to the paper Un

30 Oct 19, 2022
✂️ EyeLipCropper is a Python tool to crop eyes and mouth ROIs of the given video.

EyeLipCropper EyeLipCropper is a Python tool to crop eyes and mouth ROIs of the given video. The whole process consists of three parts: frame extracti

Zi-Han Liu 9 Oct 25, 2022
StyleGAN of All Trades: Image Manipulation withOnly Pretrained StyleGAN

StyleGAN of All Trades: Image Manipulation withOnly Pretrained StyleGAN This is the PyTorch implementation of StyleGAN of All Trades: Image Manipulati

360 Dec 28, 2022
NIMA: Neural IMage Assessment

PyTorch NIMA: Neural IMage Assessment PyTorch implementation of Neural IMage Assessment by Hossein Talebi and Peyman Milanfar. You can learn more from

Kyryl Truskovskyi 293 Dec 30, 2022
Code to reproduce the experiments from our NeurIPS 2021 paper " The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective"

Code To run: python runner.py new --save SAVE_NAME --data PATH_TO_DATA_DIR --dataset DATASET --model model_name [options] --n 1000 - train - t

Geoff Pleiss 5 Dec 12, 2022
A state of the art of new lightweight YOLO model implemented by TensorFlow 2.

CSL-YOLO: A New Lightweight Object Detection System for Edge Computing This project provides a SOTA level lightweight YOLO called "Cross-Stage Lightwe

Miles Zhang 54 Dec 21, 2022
Keras implementation of Normalizer-Free Networks and SGD - Adaptive Gradient Clipping

Keras implementation of Normalizer-Free Networks and SGD - Adaptive Gradient Clipping

Yam Peleg 63 Sep 21, 2022
[v1 (ISBI'21) + v2] MedMNIST: A Large-Scale Lightweight Benchmark for 2D and 3D Biomedical Image Classification

MedMNIST Project (Website) | Dataset (Zenodo) | Paper (arXiv) | MedMNIST v1 (ISBI'21) Jiancheng Yang, Rui Shi, Donglai Wei, Zequan Liu, Lin Zhao, Bili

683 Dec 28, 2022
Keyword2Text This repository contains the code of the paper: "A Plug-and-Play Method for Controlled Text Generation"

Keyword2Text This repository contains the code of the paper: "A Plug-and-Play Method for Controlled Text Generation", if you find this useful and use

57 Dec 27, 2022
SporeAgent: Reinforced Scene-level Plausibility for Object Pose Refinement

SporeAgent: Reinforced Scene-level Plausibility for Object Pose Refinement This repository implements the approach described in SporeAgent: Reinforced

Dominik Bauer 5 Jan 02, 2023
multimodal transformer

This repo holds the code to perform experiments with the multimodal autoregressive probabilistic model Transflower. Overview of the repo It is structu

Guillermo Valle 68 Dec 13, 2022
Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E. Evaluated on benchmark dataset Office31.

Deep-Unsupervised-Domain-Adaptation Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E.

Alan Grijalva 49 Dec 20, 2022
Bib-parser - Convenient script to parse .bib files with the ACM Digital Library like metadata

Bib Parser Convenient script to parse .bib files with the ACM Digital Library li

Mehtab Iqbal (Shahan) 1 Jan 26, 2022
Learn about quantum computing and algorithm on quantum computing

quantum_computing this repo contains everything i learn about quantum computing and algorithm on quantum computing what is aquantum computing quantum

arfy slowy 8 Dec 25, 2022
Learning nonlinear operators via DeepONet

DeepONet: Learning nonlinear operators The source code for the paper Learning nonlinear operators via DeepONet based on the universal approximation th

Lu Lu 239 Jan 02, 2023
A Factor Model for Persistence in Investment Manager Performance

Factor-Model-Manager-Performance A Factor Model for Persistence in Investment Manager Performance I apply methods and processes similar to those used

Omid Arhami 1 Dec 01, 2021