It's a powerful version of linebot

Overview

CTPS-FINAL

Linbot-sever.py

主程式

Algorithm.py

推薦演算法,媒合餐廳端資料與顧客端資料

config.ini

儲存 channel-access-token、channel-secret 資料

Preface

生活在成大將近4年,我們每天的午餐時間看著形形色色的店家,看似玲瑯滿目卻都吃膩了,中午覓食已經從期待變成壓力,每天問著「待會吃什麼?」,然後花費大量時間和心力,還是不知道要午餐吃什麼。因此我們希望運用Computational Thinking and Problem Solving 的思維,幫助大家解決這個困擾已久的問題。

Problem Definition

My target problem - 解決成大師生不知道午餐吃什麼的困擾?

Problem Decomposition

  • :成大師生
  • :午餐煩惱
  • :週一到週五 11點 ~ 14點
  • :成大周遭 1.5km 以內距離
  • constrain : 交通限制(交通工具)、店家營業時間限制、用戶人數(餐廳是否能容納)、預計等待及用餐時間

Pattern Recognition

  1. 大家通常到正餐時間才會想要吃甚麼
  2. 大家移動的距離有限,如果下午1點還有課,就會在學校附近用餐
  3. 同類型食物太頻繁吃會吃膩
  4. 學生會考慮cp值(有價格區間考量)
  5. 如果店家以人潮眾多就傾向換一間店家
  6. 會因為天氣而影響選擇(例如很熱,就會找有冷氣的餐廳)
  7. 朋友或認識的同學會一起用餐

Abstraction

(把Problem Decomposition的細項問題化)

  • 店家資料
      1. 如何取得店家資料?
      1. 如何確保店家資料即時性?
  • 用戶資料
      1. 如何取得用戶資料?
      1. 如何做到使用者優化?
  • 演算法
      1. 如何根據實際狀況設計演算法
      1. 怎麼測試演算法結果是否符合用戶需求
  • 訊息回推
      1. 用什麼管道回送推薦清單
      1. 介面如何優化
      1. 怎麼得知用戶實際使用情況

Algorithm

  • 店家資料
    • 如何取得店家資料?
      • 利用 google maps 爬蟲
      • 實地探索(地點限制在成大周圍,所以有一定可行性)
    • 如何確保店家資料即時性?
      • 設計用戶回報機制
      • 定期網路爬蟲
  • 用戶資料
    • 如何取得用戶資料?
      • 利用 linbot 與使用者溝通,取得使用者需求
    • 如何做到使用者優化?
      • 利用 richmenus 串接 linbot,藉由圖文選單輸入
  • 演算法
    • 如何根據實際狀況設計演算法
      • 找外在生活條件(例如 : 天氣很熱,那冷氣的需求權重就提高一點)
    • 怎麼測試演算法結果是否符合用戶需求
      • 請朋友實際使用,並根據意見做出修改
  • 訊息回推
    • 用什麼管道回送推薦清單
      • Linebot
    • 介面如何優化
      • 建置模板按鈕,讓畫面看起來乾淨一點
    • 怎麼得知用戶實際使用情況
      • 設計用戶評分機制
      • 根據用戶評分或意見,進行修正

Solution Proposal

final report ppt & demo

References

Human-Pose-and-Motion History

Human Pose and Motion Scientist Approach Eadweard Muybridge, The Galloping Horse Portfolio, 1887 Etienne-Jules Marey, Descent of Inclined Plane, Chron

Daito Manabe 47 Dec 16, 2022
Faster RCNN with PyTorch

Faster RCNN with PyTorch Note: I re-implemented faster rcnn in this project when I started learning PyTorch. Then I use PyTorch in all of my projects.

Long Chen 1.6k Dec 23, 2022
Implementation based on Paper - Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling

Implementation based on Paper - Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling

HamasKhan 3 Jul 08, 2022
Predicting Student Attentiveness using OpenCV

Predicting-Student-Attentiveness-using-OpenCV The model will predict if a student is attentive or not through facial parameter received through the st

Johann Pinto 2 Aug 20, 2022
Auto HMM: Automatic Discrete and Continous HMM including Model selection

Auto HMM: Automatic Discrete and Continous HMM including Model selection

Chess_champion 29 Dec 07, 2022
a grammar based feedback fuzzer

Nautilus NOTE: THIS IS AN OUTDATE REPOSITORY, THE CURRENT RELEASE IS AVAILABLE HERE. THIS REPO ONLY SERVES AS A REFERENCE FOR THE PAPER Nautilus is a

Chair for Sys­tems Se­cu­ri­ty 158 Dec 28, 2022
Public repo for the ICCV2021-CVAMD paper "Is it Time to Replace CNNs with Transformers for Medical Images?"

Is it Time to Replace CNNs with Transformers for Medical Images? Accepted at ICCV-2021: Workshop on Computer Vision for Automated Medical Diagnosis (C

Christos Matsoukas 80 Dec 27, 2022
Fashion Recommender System With Python

Fashion-Recommender-System Thr growing e-commerce industry presents us with a la

Omkar Gawade 2 Feb 02, 2022
Convolutional Neural Network for 3D meshes in PyTorch

MeshCNN in PyTorch SIGGRAPH 2019 [Paper] [Project Page] MeshCNN is a general-purpose deep neural network for 3D triangular meshes, which can be used f

Rana Hanocka 1.4k Jan 04, 2023
YOLOv5 in PyTorch > ONNX > CoreML > TFLite

This repository represents Ultralytics open-source research into future object detection methods, and incorporates lessons learned and best practices evolved over thousands of hours of training and e

Ultralytics 34.1k Dec 31, 2022
DeepLab is a state-of-art deep learning system for semantic image segmentation built on top of Caffe.

DeepLab Introduction DeepLab is a state-of-art deep learning system for semantic image segmentation built on top of Caffe. It combines densely-compute

Ali 234 Nov 14, 2022
PyTorchMemTracer - Depict GPU memory footprint during DNN training of PyTorch

A Memory Tracer For PyTorch OOM is a nightmare for PyTorch users. However, most

Jiarui Fang 9 Nov 14, 2022
Source code and data in paper "MDFEND: Multi-domain Fake News Detection (CIKM'21)"

MDFEND: Multi-domain Fake News Detection This is an official implementation for MDFEND: Multi-domain Fake News Detection which has been accepted by CI

Rich 40 Dec 18, 2022
This repo is about to create the Streamlit application for given ML model.

HR-Attritiion-using-Streamlit This repo is about to create the Streamlit application for given ML model. Problem Statement: Managing peoples at workpl

Pavan Giri 0 Dec 10, 2021
Tensorflow implementation of our method: "Triangle Graph Interest Network for Click-through Rate Prediction".

TGIN Tensorflow implementation of our method: "Triangle Graph Interest Network for Click-through Rate Prediction". Files in the folder dataset/ electr

Alibaba 21 Dec 21, 2022
Fast SHAP value computation for interpreting tree-based models

FastTreeSHAP FastTreeSHAP package is built based on the paper Fast TreeSHAP: Accelerating SHAP Value Computation for Trees published in NeurIPS 2021 X

LinkedIn 369 Jan 04, 2023
3 Apr 20, 2022
Official implementation of "UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspective with Transformer"

[AAAI2022] UCTransNet This repo is the official implementation of "UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspectiv

Haonan Wang 199 Jan 03, 2023
Official Pytorch implementation of the paper "Action-Conditioned 3D Human Motion Synthesis with Transformer VAE", ICCV 2021

ACTOR Official Pytorch implementation of the paper "Action-Conditioned 3D Human Motion Synthesis with Transformer VAE", ICCV 2021. Please visit our we

Mathis Petrovich 248 Dec 23, 2022
This Repo is the official CUDA implementation of ICCV 2019 Oral paper for CARAFE: Content-Aware ReAssembly of FEatures

Introduction This Repo is the official CUDA implementation of ICCV 2019 Oral paper for CARAFE: Content-Aware ReAssembly of FEatures. @inproceedings{Wa

Jiaqi Wang 42 Jan 07, 2023