Código de um painel de auto atendimento feito em Python.

Related tags

Deep LearningPainel-Auto-Atendimento
Overview

Painel de Auto-Atendimento

  • O intuito desse projeto era fazer em Python um programa que simulasse um painel de auto atendimento, no maior estilo Mac Donald's. O código foi feito 100% em live na Twitch e em breve vou postar um resumo das lives no Youtube.

  • Espero que gostem e quem se interessar pode baixar os arquivos e usar o código livremente para estudar ou replicar !

Sistema em ação!

Nessa primeira imagem eu mostro um pouco da interface inicial do programa (Quase o "Hello World").

Aqui eu demonstro o funcionamento total dele, de escolher o que vai querer à confirmação do pagamento.

  • Basicamente no programa você escolhe o que vai querer comprar, a quantidade, se vai querer adicionar outro produto ou apenas finalizar. Após finalizar você recebe seu "cupom fiscal" e após conferir todo o valor você aperta qualquer tecla e finaliza o seu atendimento.

Minhas redes sociais: Instagram Linkedin GitHub Twitch Youtube

Owner
Calebe Alves Evangelista
Estudante de programação :D
Calebe Alves Evangelista
GitHub Repository
Pytorch implementation of paper "Efficient Nearest Neighbor Language Models" (EMNLP 2021)

Pytorch implementation of paper "Efficient Nearest Neighbor Language Models" (EMNLP 2021)

Junxian He 57 Jan 01, 2023
Repository for the paper "Online Domain Adaptation for Occupancy Mapping", RSS 2020

RSS 2020 - Online Domain Adaptation for Occupancy Mapping Repository for the paper "Online Domain Adaptation for Occupancy Mapping", Robotics: Science

Anthony 26 Sep 22, 2022
Neurons Dataset API - The official dataloader and visualization tools for Neurons Datasets.

Neurons Dataset API - The official dataloader and visualization tools for Neurons Datasets. Introduction We propose our dataloader API for loading and

1 Nov 19, 2021
This repository contains implementations of all Machine Learning Algorithms from scratch in Python. Mathematics required for ML and many projects have also been included.

👏 Pre- requisites to Machine Learning

Vanshika Mishra 147 Jan 07, 2023
An index of recommendation algorithms that are based on Graph Neural Networks.

An index of recommendation algorithms that are based on Graph Neural Networks.

FIB LAB, Tsinghua University 564 Jan 07, 2023
Open source single image super-resolution toolbox containing various functionality for training a diverse number of state-of-the-art super-resolution models. Also acts as the companion code for the IEEE signal processing letters paper titled 'Improving Super-Resolution Performance using Meta-Attention Layers’.

Deep-FIR Codebase - Super Resolution Meta Attention Networks About This repository contains the main coding framework accompanying our work on meta-at

17 Jun 17, 2022
Apply our monocular depth boosting to your own network!

MergeNet - Boost Your Own Depth Boost custom or edited monocular depth maps using MergeNet Input Original result After manual editing of base You can

Computational Photography Lab @ SFU 142 Dec 17, 2022
Asymmetric metric learning for knowledge transfer

Asymmetric metric learning This is the official code that enables the reproduction of the results from our paper: Asymmetric metric learning for knowl

20 Dec 06, 2022
Degree-Quant: Quantization-Aware Training for Graph Neural Networks.

Degree-Quant This repo provides a clean re-implementation of the code associated with the paper Degree-Quant: Quantization-Aware Training for Graph Ne

35 Oct 07, 2022
Unofficial PyTorch Implementation of "DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features"

Pytorch Implementation of Deep Orthogonal Fusion of Local and Global Features (DOLG) This is the unofficial PyTorch Implementation of "DOLG: Single-St

DK 96 Jan 06, 2023
Show-attend-and-tell - TensorFlow Implementation of "Show, Attend and Tell"

Show, Attend and Tell Update (December 2, 2016) TensorFlow implementation of Show, Attend and Tell: Neural Image Caption Generation with Visual Attent

Yunjey Choi 902 Nov 29, 2022
TSIT: A Simple and Versatile Framework for Image-to-Image Translation

TSIT: A Simple and Versatile Framework for Image-to-Image Translation This repository provides the official PyTorch implementation for the following p

Liming Jiang 255 Nov 23, 2022
Analyzes your GitHub Profile and presents you with a report on how likely you are to become the next MLH Fellow!

Fellowship Prediction GitHub Profile Comparative Analysis Tool Built with BentoML Table of Contents: Features Disclaimer Technologies Used Contributin

Damir Temir 51 Dec 29, 2022
LAMDA: Label Matching Deep Domain Adaptation

LAMDA: Label Matching Deep Domain Adaptation This is the implementation of the paper LAMDA: Label Matching Deep Domain Adaptation which has been accep

Tuan Nguyen 9 Sep 06, 2022
Why Are You Weird? Infusing Interpretability in Isolation Forest for Anomaly Detection

Why, hello there! This is the supporting notebook for the research paper — Why Are You Weird? Infusing Interpretability in Isolation Forest for Anomal

2 Dec 14, 2021
OpenAi's gym environment wrapper to vectorize them with Ray

Ray Vector Environment Wrapper You would like to use Ray to vectorize your environment but you don't want to use RLLib ? You came to the right place !

Pierre TASSEL 15 Nov 10, 2022
Codes for “A Deeply Supervised Attention Metric-Based Network and an Open Aerial Image Dataset for Remote Sensing Change Detection”

DSAMNet The pytorch implementation for "A Deeply-supervised Attention Metric-based Network and an Open Aerial Image Dataset for Remote Sensing Change

Mengxi Liu 41 Dec 14, 2022
CURL: Contrastive Unsupervised Representations for Reinforcement Learning

CURL Rainbow Status: Archive (code is provided as-is, no updates expected) This is an implementation of CURL: Contrastive Unsupervised Representations

Aravind Srinivas 46 Dec 12, 2022
Extreme Dynamic Classifier Chains - XGBoost for Multi-label Classification

Extreme Dynamic Classifier Chains Classifier chains is a key technique in multi-label classification, sinceit allows to consider label dependencies ef

6 Oct 08, 2022
A PyTorch implementation of the Relational Graph Convolutional Network (RGCN).

Torch-RGCN Torch-RGCN is a PyTorch implementation of the RGCN, originally proposed by Schlichtkrull et al. in Modeling Relational Data with Graph Conv

Thiviyan Singam 66 Nov 30, 2022