Plant Leaf Disease Detection Machine Learning Project


Plant Leaf Disease Detection Using Machine Learning and Image Processing Project for final year students

Plant leaf infection detection Project


In this project, we first collect images of different types of infected, good, and seems to be infected plant leaves. Once the leaf dataset is prepared then, we apply an image processing algorithm to the images and predict the infected and not-infected plant leafs using Deep Learning and image processing.

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Video Demonstration Model Building

Deployment Streamlit Application

Steps Involved in Image Processing

Image Acquisition

Enhancement of image

Image Restoration

Color Image Processing



Algorithm used used

Using Deep Learning for Prediction along with Image processing such as Convolution Neural networks is mostly preferred neural network for image analysis.

Installation of the Project

Tensorflow:-Install TensorFlow in your local environment or anaconda environment using command-line by using the command:

$ pip install TensorFlow

Keras:- For detailed installation of Keras with TensorFlow read this:-

Scikit Learn:- If you are using Anaconda it is previously installed.

Pickle:- If you are using Anaconda it’s previously installed.

OpenCv:- Install OpenCV using the command –> pip install opencv-python

Note: As the dataset is large and huge, it is better to use Google Colaboratory for training the model and evaluating the model.

Source Code of Plant Leaf Disease Detection Project using Machine Learning and Image Processing

Click Here to Download the Source Code


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