Project Title

Disease Detection in Rice Leaves

Project Description

In India the economic, political and social stability rely directly yet as indirectly on the annual production of rice. 37% of the rice illness is because of disease as per the review and Analysis of IRRI (International Rice Research Institute), during this consequence, the farmer watches out of crop on-time with completely opposite treatments against disease. The diseases detection and identification in massive field through automatic technique is the helpful because it reduces the work of peoples or farmers, conjointly time and value for observation and analysis of un-wellness symptoms. This report contains approach for identification detection and of rice leaf diseases by multiclass SVM. The diseases classification is done by SVM classifier and therefore the detection accuracy is improved by optimizing the info exploitation. In this proposed system, we are using image processing techniques to classify diseases & quickly diagnosis can be carried out as per disease. This approach will enhance productivity of crops. It includes several steps viz. image acquisition, image preprocessing, segmentation, features extraction.

We use the classifier trained using the knowledge base for detection and diagnosis of plant leaf diseases. To create the knowledge base we used sample images and divided it by 80% training and 20% testing. Lastly, classification technique is applied in detection the sort of plant disease.

Installation

  clone the project

Requiremnts

• numpy
• Pillow
• scikit-learn
• scikit-image

Deployment

Open cmd in the working directory and run

   pip install -r requirements.txt

To run the project run

   python Rice_Leaves_Disease_Detection_GUI.py

and test it.

Screenshots