Apple Fruit Disease Detection using Image Processing in Python

PROJECT ABSTRACT:

The paramount motive of farming is to yield good crops without any disease present. The role of digital image processing along with image analysis is indispensable in the sector of agriculture. Preprogrammed awareness of plant malady and production of good plants is of substantial significance in agriculture industrialization. To prevent the loss of agricultural yield one has to recognize the malady.

Manually, detection of plants malady is quite difficult, it required huge time for analyzing the malady present on the fruit. To tame this problem, a machine learning-based approach is recommended which can evaluate the image of the fruit to detect the disease. Image processing is the method which is successfully used for the recognition of plant malady.

We have proposed and experimentally validated the significance of using CNN as a classifier for the automatic detection and classification of fruit diseases. In order to validate the proposed approach, we have considered three types of the diseases in apple; apple blotch, apple rot and apple scab.

OUTPUT VIDEO:

ALGORITHM / MODEL USED:

Inception V3 Architecture.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

System : Pentium i3 Processor.
Hard Disk : 500 GB.
Monitor : 15’’ LED.
Input Devices : Keyboard, Mouse.
Ram : 8 GB.

SOFTWARE REQUIREMENTS:

Operating System : Windows 10 / 11.
Coding Language : Python 3.8.
Web Framework : Python
Frontend : HTML, CSS, JavaScript.

Python Projects

Apple Fruit Disease Detection using Image Processing in Python