SSD-based Object Detection in PyTorch

Last update: Nov 16, 2021

Related tags

Deep Learning Mobis_Object-detection

Overview

SSD-based Object Detection in PyTorch

서강대학교 현대모비스 SW 프로그램에서 진행한 인공지능 프로젝트입니다.

Jetson nano를 이용해 pre-trained network를 fine tuning시켜 차량 및 신호등 인식을 구현하였습니다.

https://www.youtube.com/watch?v=jYsIBuAgdao

This repo implements SSD (Single Shot MultiBox Detector) in PyTorch for object detection, using MobileNet backbones. It also has out-of-box support for retraining on Google Open Images dataset.

For documentation, please refer to Object Detection portion of the Hello AI World tutorial: Re-training SSD-Mobilenet

Thanks to @qfgaohao for the upstream implementation from: https://github.com/qfgaohao/pytorch-ssd

Owner

Haneul Kim

cerulean bird so cute

GitHub Repository

This repo implements several applications of the proposed generalized Bures-Wasserstein (GBW) geometry on symmetric positive definite matrices.

GBW This repo implements several applications of the proposed generalized Bures-Wasserstein (GBW) geometry on symmetric positive definite matrices. Ap

0 Oct 22, 2021

The Unsupervised Reinforcement Learning Benchmark (URLB)

The Unsupervised Reinforcement Learning Benchmark (URLB) URLB provides a set of leading algorithms for unsupervised reinforcement learning where agent

259 Dec 26, 2022

Unofficial implementation of HiFi-GAN+ from the paper "Bandwidth Extension is All You Need" by Su, et al.

HiFi-GAN+ This project is an unoffical implementation of the HiFi-GAN+ model for audio bandwidth extension, from the paper Bandwidth Extension is All

134 Dec 30, 2022

Code for "Modeling Indirect Illumination for Inverse Rendering", CVPR 2022

Modeling Indirect Illumination for Inverse Rendering Project Page | Paper | Data Preparation Set up the python environment conda create -n invrender p

116 Jan 03, 2023

Official NumPy Implementation of Deep Networks from the Principle of Rate Reduction (2021)

Deep Networks from the Principle of Rate Reduction This repository is the official NumPy implementation of the paper Deep Networks from the Principle

49 Dec 16, 2022

PyTorch Implementation of Spatially Consistent Representation Learning(SCRL)

Spatially Consistent Representation Learning (CVPR'21) Official PyTorch implementation of Spatially Consistent Representation Learning (SCRL). This re

102 Nov 03, 2022

DuBE: Duple-balanced Ensemble Learning from Skewed Data

DuBE: Duple-balanced Ensemble Learning from Skewed Data "Towards Inter-class and Intra-class Imbalance in Class-imbalanced Learning" (IEEE ICDE 2022 S

6 Nov 12, 2022

fastgradio is a python library to quickly build and share gradio interfaces of your trained fastai models.

34 Jan 05, 2023

Implementation of DocFormer: End-to-End Transformer for Document Understanding, a multi-modal transformer based architecture for the task of Visual Document Understanding (VDU)

DocFormer - PyTorch Implementation of DocFormer: End-to-End Transformer for Document Understanding, a multi-modal transformer based architecture for t

171 Jan 06, 2023

ANEA: Distant Supervision for Low-Resource Named Entity Recognition

ANEA: Distant Supervision for Low-Resource Named Entity Recognition ANEA is a tool to automatically annotate named entities in unlabeled text based on

15 Mar 30, 2022

Clean Machine Learning, a Coding Kata

Kata: Clean Machine Learning From Dirty Code First, open the Kata in Google Colab (or else download it) You can clone this project and launch jupyter-

13 Nov 03, 2022

Code for the paper "Adapting Monolingual Models: Data can be Scarce when Language Similarity is High"

Wietse de Vries • Martijn Bartelds • Malvina Nissim • Martijn Wieling Adapting Monolingual Models: Data can be Scarce when Language Similarity is High

5 Aug 02, 2021

IJCAI2020 & IJCV 2020 :city_sunrise: Unsupervised Scene Adaptation with Memory Regularization in vivo

Seg_Uncertainty In this repo, we provide the code for the two papers, i.e., MRNet：Unsupervised Scene Adaptation with Memory Regularization in vivo, IJ

348 Jan 05, 2023

Learning to Predict Gradients for Semi-Supervised Continual Learning

Learning to Predict Gradients for Semi-Supervised Continual Learning Code for project: "Learning to Predict Gradients for Semi-Supervised Continual Le

2 Mar 05, 2022

Earthquake detection via fiber optic cables using deep learning

Earthquake detection via fiber optic cables using deep learning Author: Fantine Huot Getting started Update the submodules After cloning the repositor

4 Nov 30, 2022

Scripts and outputs related to the paper Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings.

Knowledge Graph Embeddings and Chemical Effect Prediction, 2020. Scripts and outputs related to the paper Prediction of Adverse Biological Effects of

1 Nov 01, 2021

Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation. Intel iHD GPU (iGPU) support. NVIDIA GPU (dGPU) support.

mtomo Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation.

24 Mar 02, 2022

Official PyTorch code for Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling (HCFlow, ICCV2021)

Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling (HCFlow, ICCV2021) This repository is the official P

159 Dec 30, 2022

QuakeLabeler is a Python package to create and manage your seismic training data, processes, and visualization in a single place — so you can focus on building the next big thing.

QuakeLabeler Quake Labeler was born from the need for seismologists and developers who are not AI specialists to easily, quickly, and independently bu

15 Nov 04, 2022

D2Go is a toolkit for efficient deep learning

D2Go D2Go is a production ready software system from FacebookResearch, which supports end-to-end model training and deployment for mobile platforms. W

744 Jan 04, 2023