https://github.com/victorqribeiro/deforestation

A machine learning exercise, using KNN to classify deforested areas
https://github.com/victorqribeiro/deforestation

image-analysis image-classification image-processing image-recognition knn machine-learning

Last synced: about 1 month ago
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A machine learning exercise, using KNN to classify deforested areas

• Host: GitHub
• URL: https://github.com/victorqribeiro/deforestation
• Owner: victorqribeiro
• License: mit
• Created: 2019-06-23T18:11:48.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2019-06-23T18:19:32.000Z (about 5 years ago)
• Last Synced: 2024-05-21T00:49:28.648Z (4 months ago)
• Topics: image-analysis, image-classification, image-processing, image-recognition, knn, machine-learning
• Language: Python
• Size: 10.5 MB
• Stars: 27
• Watchers: 1
• Forks: 5
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Deforestation

That time I used [KNN](https://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm) to classify deforested areas for my machine learning class.

![Result](result.png)

## About

This project was developed as an assignment for a machine learning class, where we were given a pictures from the Amazon forest and we should write a machine learning algorithm to identify possibles deforested areas, including farming areas. 

I then gather some training data, generated a histogram for every image and analysed the final image with a simple KNN (k=7) I wrote.

I was very happy with the results I got given the little code I wrote (this project is from 2017).

## How to run

```

python classify.py img/final_image.png

```