Dados coletados e programas desenvolvidos no processo de iniciação científica

Related tags

Deep LearningIniciacao_cientifica_FAPESP_2020-14845-6
Overview

Iniciacao_cientifica_FAPESP_2020-14845-6

Dados coletados e programas desenvolvidos no processo de iniciação científica Os arquivos .py são os programas utilizados no processamento Para você poder rodar os programas e eles funcionarem você deve ter pastas com nomes específicos. Os nomes das pastas podem ser identificados analisando os códigos disponibilizados. A pasta workingprepos possui os arquivos de coordenadas 3D já todo processado que foram os utilizados para gerar os resultados apresentados no projeto A pasta working3d são os dados reconstruidos com 144 saltos, ou seja, já tiveram 10 saltos excluidos mas ainda seriam excluidos mais 20 Já a pasta arquivoscalib possui os dados utilizados para as 6 calibrações utilizadas na coleta

Qualquer dúvida contatar: [email protected]

GIF_defesa

Owner
GitHub Repository
quantize aware training package for NCNN on pytorch

ncnnqat ncnnqat is a quantize aware training package for NCNN on pytorch. Table of Contents ncnnqat Table of Contents Installation Usage Code Examples

62 Nov 23, 2022
Most popular metrics used to evaluate object detection algorithms.

Most popular metrics used to evaluate object detection algorithms.

Rafael Padilla 4.4k Dec 25, 2022
A forwarding MPI implementation that can use any other MPI implementation via an MPI ABI

MPItrampoline MPI wrapper library: MPI trampoline library: MPI integration tests: MPI is the de-facto standard for inter-node communication on HPC sys

Erik Schnetter 31 Dec 22, 2022
Look Who’s Talking: Active Speaker Detection in the Wild

Look Who's Talking: Active Speaker Detection in the Wild Dependencies pip install -r requirements.txt In addition to the Python dependencies, ffmpeg

Clova AI Research 60 Dec 08, 2022
Heterogeneous Deep Graph Infomax

Heterogeneous-Deep-Graph-Infomax Parameter Setting: HDGI-A: Node-level dimension: 16 Attention head: 4 Semantic-level attention vector: 8 learning rat

52 Oct 31, 2022
Implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"

SinGAN This is an unofficial implementation of SinGAN from someone who's been sitting right next to SinGAN's creator for almost five years. Please ref

35 Nov 10, 2022
Self Driving RC Car Code

Derp Learning Derp Learning is a Python package that collects data, trains models, and then controls an RC car for track racing. Hardware You will nee

Not Karol 39 Dec 07, 2022
This is the official pytorch implementation of the BoxEL for the description logic EL++

BoxEL: Box EL++ Embedding This is the official pytorch implementation of the BoxEL for the description logic EL++. BoxEL++ is a geometric approach bas

1 Nov 03, 2022
.NET bindings for the Pytorch engine

TorchSharp TorchSharp is a .NET library that provides access to the library that powers PyTorch. It is a work in progress, but already provides a .NET

Matteo Interlandi 17 Aug 30, 2021
Improved Fitness Optimization Landscapes for Sequence Design

ReLSO Improved Fitness Optimization Landscapes for Sequence Design Description Citation How to run Training models Original data source Description In

Krishnaswamy Lab 44 Dec 20, 2022
RobustVideoMatting and background composing in one model by using onnxruntime.

RVM_onnx_compose RobustVideoMatting and background composing in one model by using onnxruntime. Usage pip install -r requirements.txt python infer_cam

Quantum Liu 4 Apr 07, 2022
Train/evaluate a Keras model, get metrics streamed to a dashboard in your browser.

Hera Train/evaluate a Keras model, get metrics streamed to a dashboard in your browser. Setting up Step 1. Plant the spy Install the package pip

Keplr 495 Dec 10, 2022
Code for Max-Margin Contrastive Learning - AAAI 2022

Max-Margin Contrastive Learning This is a pytorch implementation for the paper Max-Margin Contrastive Learning accepted to AAAI 2022. This repository

Anshul Shah 12 Oct 22, 2022
PyTorch implementation of neural style transfer algorithm

neural-style-pt This is a PyTorch implementation of the paper A Neural Algorithm of Artistic Style by Leon A. Gatys, Alexander S. Ecker, and Matthias

770 Jan 02, 2023
Unofficial implementation of Fast-SCNN: Fast Semantic Segmentation Network

Fast-SCNN: Fast Semantic Segmentation Network Unofficial implementation of the model architecture of Fast-SCNN. Real-time Semantic Segmentation and mo

Philip Popien 69 Aug 11, 2022
Code for our paper: Online Variational Filtering and Parameter Learning

Variational Filtering To run phi learning on linear gaussian (Fig1a) python linear_gaussian_phi_learning.py To run phi and theta learning on linear g

16 Aug 14, 2022
TensorFlow Implementation of Unsupervised Cross-Domain Image Generation

Domain Transfer Network (DTN) TensorFlow implementation of Unsupervised Cross-Domain Image Generation. Requirements Python 2.7 TensorFlow 0.12 Pickle

Yunjey Choi 864 Dec 30, 2022
Implementation for Panoptic-PolarNet (CVPR 2021)

Panoptic-PolarNet This is the official implementation of Panoptic-PolarNet. [ArXiv paper] Introduction Panoptic-PolarNet is a fast and robust LiDAR po

Zixiang Zhou 126 Jan 01, 2023
Code for Domain Adaptive Video Segmentation via Temporal Consistency Regularization in ICCV 2021

Domain Adaptive Video Segmentation via Temporal Consistency Regularization Updates 08/2021: check out our domain adaptation for sematic segmentation p

36 Dec 12, 2022
Google Landmark Recogntion and Retrieval 2021 Solutions

Google Landmark Recogntion and Retrieval 2021 Solutions In this repository you can find solution and code for Google Landmark Recognition 2021 and Goo

Vadim Timakin 5 Nov 25, 2022