Skip to content

This repository contains the code components of work carried out for analyzing the Plant Pathology 2020 dataset with the intent to find the infected and non-infeted apple tree leaves.

License

Notifications You must be signed in to change notification settings

raj-shr-git/Apple_Foliar_Disease_Detection

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

7 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Project Objectives 🏹

❄ Major crops today are plagued by a variety of diseases. Diseases in crops can occur in various parts of the plant, such as the roots, stem, but leaves are the most typical site for disease detection.

❄ It is difficult to detect and diagnose diseases because leaves have a variety of sizes, shapes, and colors.

❄ Current disease diagnosis based on human scouting is time-consuming & expensive, however, the advancements of machine learning and computer data processing helped in automatically identify diseases in crops like rice, corn, wheat, cotton & tomato.

❄ The goal of this project is to leverage computer-vision-based techniques and build a model that can:

---- ❄ Accurately classify a given image into a diseased category or a healthy leaf.

---- ❄ Accurately distinguish between many diseases, sometimes more than one on a single leaf.

---- ❄ Deal with rare classes and novel symptoms.

---- ❄ Address depth perception — angle, light, shade & age of the leaf.

About

This repository contains the code components of work carried out for analyzing the Plant Pathology 2020 dataset with the intent to find the infected and non-infeted apple tree leaves.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published