Web application that detects and counts the number of roses using an artificial intelligence model.

AI rose counting system web application

Web application that recognizes and counts the number of red roses using an artificial intelligence model.
Explore the docs »

About The Project

This is a web application that recognizes and counts the number of red roses using artificial intelligence. The user can upload an image or take a picture with the camera. Once the image is processed, the application will display on screen the number of roses found and the average accuracy. The user can also download the resulting image, or generate and download a report.

This web application was developed by Leo, Mike, Carlos and Juan, students at Yachay Tech University.

(back to top)

Built With

• HTML
• CSS
• JavaScript
• Python
• Django
• Bootstrap
• TensorFlow
• ReportLab

OS Suported

• Microsoft Windows: 10, 11
• Lunix: Ubuntu 20.04

(back to top)

Getting Started

Prerequisites

• Python (3.8.8 recomended)

  Download Python

Important (for Windows only)

1. Make sure to add Python to path during Python installation

2. Make sure to disable path length limit during Python installation

Windows

• Latest pip

  pip install --upgrade pip

• Numpy

  pip install numpy

• Django

  pip install Django

• TensorFlow

  pip install tensorflow

• OpenCV

  pip install opencv-python

• ReportLab

  pip install reportlab

• Pillow

  pip install pillow

Linux

• Upgrade Repositories

  sudo apt-get upgrade -y

• Pip for Python3

  sudo apt install python3-pip

• Upgrade Pip for Python3

  sudo pip3 install --upgrade pip

• Django

  sudo pip3 install django

• TensorFlow

  sudo pip3 install tensorflow

• OpenCV

  sudo pip3 install opencv-python

• ReportLab

  sudo pip3 install reportlab

• Pillow

  sudo pip3 install pillow

Installation

Windows

1. Clone the repo

   git clone https://github.com/Leo-Thomas/AI-based-red-rose-counting-webapp.git

2. Inside "AI-based-red-rose-counting-webapp" directory, open a terminal and initialize the server

   python manage.py runserver

3. Open the generated link in the browser

   Starting development server at **http://127.0.0.1:8000/**

(back to top)

Linux

1. Clone the repo

sudo git clone https://github.com/Leo-Thomas/AI-based-red-rose-counting-webapp.git

2. Inside "AI-based-red-rose-counting-webapp" directory, open a terminal as administrator and initialize the server

sudo python3 manage.py runserver

3. Open the generated link in the browser

Starting development server at **http://127.0.0.1:8000/**

(back to top)

Usage

Counting by uploading a file

• Click the "Choose file" button

• Select the file you want to process and upload it

• Once the file is loaded, click the "Count" button to start counting.

• A waiting screen will be displayed while your image is being processed. (You can cancel the process at any time by clicking the "Cancel" button.)

• After a few seconds, the original image will be displayed on the screen together with the image with the rose detection. Also, the number of roses found and the average accuracy will be displayed in the results panel.

• If you wish, you can download the resulting image by clicking on the "Download Image" button.

• You can also generate a report of the count by clicking on the "Generate report" button, which will take you to a new window.

• In the new window, you can download the report by clicking on the "Download report" button.

• Finally, you can go to the home page to process another image

(back to top)

Counting using the camera

• Click on the "Camera" button

• Give permissions to access your camera

• Then, a box with the image of your camera will be displayed.

• Place the desired image in front of the lens and press the "Shoot" button to capture it. (You can click the "Shoot" button as many times as you wish until you capture the right image.)

• Once the image is captured, click on the "Count" button to start counting.

• A waiting screen will be displayed while your image is being processed. (You can cancel the process at any time by clicking the "Cancel" button.)

• After a few seconds, the original image will be displayed on the screen together with the image with the rose detection. Also, the number of roses found and the average accuracy will be displayed in the results panel.

• If you wish, you can download the resulting image by clicking on the "Download Image" button.

• You can also generate a report of the count by clicking on the "Generate report" button, which will take you to a new window.

• In the new window, you can download the report by clicking on the "Download report" button.

• Finally, you can go to the home page to process another image

(back to top)

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/NewFeature)
3. Commit your Changes (git commit -m 'Add some NewFeature')
4. Push to the Branch (git push origin feature/NewFeature)
5. Open a Pull Request

(back to top)

License

Distributed under the GNU General Public License v3.0. See LICENSE for more information.

(back to top)

Contact

Leo Ramos - LinkedIn - [email protected]

Mike Bermeo - LinkedIn - [email protected]

Juan Brito - LinkedIn - [email protected]

Carlos Macancela - LinkedIn - [email protected]

Project Link: https://github.com/Leo-Thomas/AI-Rose-counting-system-web-app

(back to top)

Acknowledgments

• IBM MAX Object Detector
• TFJS Object Detection
• Piotr Płoński
• Towards Data Science

(back to top)