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.
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Python 38499 Version:v2.0.2 License: Permissive (BSD-3-Clause)
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 detection using SSD Mobile Net v3
Python 4 Version:Current License: No License
An Open Source Machine Learning Framework for Everyone
C++ 175043 Version:v2.13.0-rc0 License: Permissive (Apache-2.0)
A toolkit for making real world machine learning and data analysis applications in C++
C++ 11985 Version:v19.24.2 License: Permissive (BSL-1.0)
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-learn: machine learning in Python
Python 54399 Version:1.2.2 License: Permissive (BSD-3-Clause)
TensorFlow Recommenders is a library for building recommender system models using TensorFlow.
Python 1575 Version:v0.7.3 License: Permissive (Apache-2.0)
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
Python 15918 Version:v1.1.3-patched License: Permissive (MIT)
An implementation of a deep learning recommendation model (DLRM)
Python 3416 Version:Current License: Permissive (MIT)
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.
Streamlit — A faster way to build and share data apps.
Python 24943 Version:1.22.0 License: Permissive (Apache-2.0)
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!
Restaurant Business Analytics for price, discount etc prediction with people counting web app
HTML 1 Version:Current License: No License