Projectworlds > Blog > Machine Learning Projects With Source Code > Forest wildfire detection from satellite images using Deep Learning

Forest wildfire detection from satellite images using Deep Learning

Posted on June 20, 2022January 21, 2024 by Yugesh Verma

Buy Now ₹1501

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In this project, we detect forest wildfire from given satellite images.I have used CNN, with a training dataset of 2000 images.

Model training

Refer to the research.ipynb jupyter notebook to know the steps taken for model development and algorithm.

Datasets Link :- https://www.kaggle.com/datasets/washingtongold/wildfire-satellite-data

Technology Used:-

We have developed this project using the below technology
HTML : Page layout has been designed in HTML
CSS : CSS has been used for all the desigining part
JavaScript : All the validation task and animations has been developed by JavaScript
Python : All the business logic has been implemented in Python

Supported Operating System

We can configure this project on following operating system.
Windows : This project can easily be configured on windows operating system. For running this project on Windows system, you will have to install
Python 3.7, PIP, Flask.
Linux : We can run this project also on all versions of Linux operating systemMac : We can also easily configured this project on Mac operating system.

Installing and running this app:

Requirements: Use pip install to download following packages
Tensorflow and Keras
Flask
WSGI server (see the error message when running Flask app, and install all specified packages)
running the app:
run command: python app.py in the project folder
Once the server starts, open browser, the app runs on http://127.0.0.1:5000/
"test satellite images" folder contains some satellite images that you can upload to check the working of this application.

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