The purpose of the project is to detect plant disease and diagnose the same. The procedure is to detect plant disease by digital video. Dataset consist a collection of plant disease images. The system must be already trained with collected dataset. The converted image frame process with DL system using DCNN (Deep Convolutional Neural Network). To gain the crop yield on agriculture, system classify particular disease and report diagnosis to the user. Result of our project is system classifies whether the plant is affected or not. On our own we will research about implementing the system in a drone, which flies in a specific pattern to cover the whole field. We hope that this will enable our system to produce more accuracy
this project has 2 parts. they are image/video based detection (ROI by opencv) and recognition of disease in affected plant (ie. paddy) classify by input and tell results with report to user.it runs under flask web framework. dataset were collected by own camera field images.it was challenging project for me. it helps farmer to moniter thier field.
run file 'app.py; in "image recognition" folder run file 'object_detection_video.py' or 'object_detection_video.py' in "object detection" folder
here are some of the project screenshots:
Prakash A – @iamprakash13 - ptan022@gmail.com
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Copyright (c) 2019 Prakash A
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