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Price recommendation with people counting kit

by suriya Updated: Sep 9, 2021

Restaurant Business Analytics for the price, discount, etc prediction with people counting web app Innovative solution for gaining profit in standalone startup restaurants. According to many reports, the main factor that determines a restaurant's profit is the people count. So we have proposed a solution where a restaurant's past history of prices, dishes, and such factor's transaction has been taken into account and providing a recommendation for the price to be fixed for a particular day, the dish quantity to be prepared, etc. Trend analysis is much more important, for that we use tableau, which provides real-time public inference on data, here the owners can check their past transaction and analyze the trend. Use the open source, cloud APIs, or public libraries listed below in your application development based on your technology preferences, such as primary language. The below list also provides a view of the components' rating on different dimensions such as community support availability, security vulnerability, and overall quality, helping you make an informed choice for implementation and maintenance of your application. Please review the components carefully, having a no license alert or proprietary license, and use them appropriately in your applications. Please check the component page for the exact license of the component. You can also get information on the component's features, installation steps, top code snippets, and top community discussions on the component details page. The links to package managers are listed for download, where packages are readily available. Otherwise, build from the respective repositories for use in your application. You can also use the source code from the repositories in your applications based on the respective license types.

Data gathering and cleaning

Handpicked data of restaurant prices, dish count, etc, and preprocessing using pandas and NumPy would give us clean data for modelling, the data is raw, formatting for our use is the key to good accuracy.

pandasby pandas-dev

Python star image 33259 Version:v1.4.1

License: Permissive (BSD-3-Clause)

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

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pandasby pandas-dev

Python star image 33259 Version:v1.4.1 License: Permissive (BSD-3-Clause)

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
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People Counting

After done with the data, we can use the pre-trained model and tune it to do non-max suppression to get prediction only for people. And get predictions as the people count, in selected areas. Tracking is necessary to know when people come into the frame and track them till they move out, for that Dlib and OpenCV libraries are used.

Object-Detectionby sidpro-hash

Python star image 4 Version:Current

License: No License (null)

object detection using SSD Mobile Net v3

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Object-Detectionby sidpro-hash

Python star image 4 Version:Current License: No License

object detection using SSD Mobile Net v3
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tensorflowby tensorflow

C++ star image 164372 Version:v2.9.0-rc1

License: Permissive (Apache-2.0)

An Open Source Machine Learning Framework for Everyone

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tensorflowby tensorflow

C++ star image 164372 Version:v2.9.0-rc1 License: Permissive (Apache-2.0)

An Open Source Machine Learning Framework for Everyone
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opencvby opencv

C++ star image 60896 Version:4.5.5

License: Others (Non-SPDX)

Open Source Computer Vision Library

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opencvby opencv

C++ star image 60896 Version:4.5.5 License: Others (Non-SPDX)

Open Source Computer Vision Library
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dlibby davisking

C++ star image 10897 Version:v19.23

License: Permissive (BSL-1.0)

A toolkit for making real world machine learning and data analysis applications in C++

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dlibby davisking

C++ star image 10897 Version:v19.23 License: Permissive (BSL-1.0)

A toolkit for making real world machine learning and data analysis applications in C++
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Recommendation and Time series

The main idea here is to recommend prices to restaurant owners with respect to the people count for the future. So with the cleaned data, we model it using the prophet model from the Facebook research do time series analysis i.e to predict the future values and then apply dlrm a recommender system model and recommend people the right dish with respect to the past history, and recommend a price to the owners with respect to the people count.

scikit-learnby scikit-learn

Python star image 49728 Version:1.0.2

License: Permissive (BSD-3-Clause)

scikit-learn: machine learning in Python

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scikit-learnby scikit-learn

Python star image 49728 Version:1.0.2 License: Permissive (BSD-3-Clause)

scikit-learn: machine learning in Python
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recommendersby tensorflow

Python star image 1260 Version:v0.6.0

License: Permissive (Apache-2.0)

TensorFlow Recommenders is a library for building recommender system models using TensorFlow.

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recommendersby tensorflow

Python star image 1260 Version:v0.6.0 License: Permissive (Apache-2.0)

TensorFlow Recommenders is a library for building recommender system models using TensorFlow.
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prophetby facebook

Python star image 14280 Version:v1.0

License: Permissive (MIT)

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

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prophetby facebook

Python star image 14280 Version:v1.0 License: Permissive (MIT)

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
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dlrmby facebookresearch

Python star image 3086 Version:Current

License: Permissive (MIT)

An implementation of a deep learning recommendation model (DLRM)

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dlrmby facebookresearch

Python star image 3086 Version:Current License: Permissive (MIT)

An implementation of a deep learning recommendation model (DLRM)
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Deployment

The detection model(counting model) with the price recommendation model, all wrapped and connect as a single application(a web app). Streamlit is an easy-to-use deployment framework, particularly for machine learning.

streamlitby streamlit

Python star image 18692 Version:1.8.1

License: Permissive (Apache-2.0)

Streamlit — The fastest way to build data apps in Python

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streamlitby streamlit

Python star image 18692 Version:1.8.1 License: Permissive (Apache-2.0)

Streamlit — The fastest way to build data apps in Python
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Application

The above process is deployed as a web app, this repo contains the structure to be made for creating a new one, the app is deployed, check out the repo!

Business-Analytics-with-People-Counterby suriya-it19

HTML star image 1 Version:Current

License: No License (null)

Restaurant Business Analytics for price, discount etc prediction with people counting web app

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Business-Analytics-with-People-Counterby suriya-it19

HTML star image 1 Version:Current License: No License

Restaurant Business Analytics for price, discount etc prediction with people counting web app
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