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Cloud Control Entry Coding Challenge Submission#14

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jakobyoong wants to merge 77 commits intoej-hw:mainfrom
szejiancheng:main
Open

Cloud Control Entry Coding Challenge Submission#14
jakobyoong wants to merge 77 commits intoej-hw:mainfrom
szejiancheng:main

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@jakobyoong
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Thank you for considering Cloud Control for the Tech4City coding challenge! This documentation is meant to serve as a guide to explaining and running the Nomsters webapp, the AI powered food diary.

Overview

When users upload pictures of food, the web app will return the name of the food item in the photo. The web app is a simple to use tool that conducts image classification using AI to determine food items in a photo.

szejiancheng and others added 30 commits July 8, 2024 14:54
created db with an initialization script
Backgrounds, music, icons, all with functionality

To add:
upload picture feature
mute feature
nomsters logo
Can upload photo from computer

background change fades to average colour of next bg
music mute button
music fade feature
Added drag n drop
added placeholder picture
to do:  link analyse button to api endpoints
…ink"

This reverts commit 621c470, reversing
changes made to 9e93a5e.
updated db to include users and image blob
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codeautopilot bot commented Jul 14, 2024

PR summary

This Pull Request introduces the Nomsters web application, an AI-powered food diary that allows users to upload pictures of food and receive the name of the food item in the photo. The application includes both frontend and backend components, with functionalities such as image classification using AI, a user-friendly interface for uploading photos, viewing past history, and a simple login system.

Implications:

  • Users can easily classify food items by uploading images.
  • The application stores user data and image results in a database, allowing for persistent user sessions and history tracking.
  • The backend is built using Flask and includes endpoints for analyzing images, fetching results, and selecting preferred classifications.
  • The frontend provides an interactive UI with features like drag-and-drop image upload, background music, and a diary to view past entries.

Purpose:

  • To provide a simple and intuitive tool for users to classify food items using AI.
  • To allow users to maintain a food diary with historical data accessible across sessions.

Impact:

  • Enhances user experience with a visually appealing and functional interface.
  • Provides accurate food classification using AI, improving user engagement and utility.
  • Facilitates easy tracking of food intake over time, which can be beneficial for dietary monitoring.

Suggestion

  • Consider adding unit tests for the backend to ensure the robustness of the API endpoints.
  • Implement error handling and user feedback mechanisms in the frontend to improve user experience in case of failures.
  • Optimize the Dockerfile to reduce the image size and improve build times.
  • Enhance security measures, such as input validation and sanitization, to protect against potential vulnerabilities.

Disclaimer: This comment was entirely generated using AI. Be aware that the information provided may be incorrect.

Current plan usage: 61.43%

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4 participants