Nidan

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  Landing Page

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  Features of Nidan

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  Types of analysis

The problem NIDAN solves

We aim to provide a simple user friendly application of crop disease detection for corn , grapes and apple using deep learning model.

we also provide farmers with a one stop application where they can know about the soil , fertilizers and crops for cultivation. It also recommens them a sutiable crop they can cultivate according to the conditions

Challenges we ran into

Getting proper, reliable data can be a huge barrier faced before training data set

Once we get the data set, it may happen that the data has some irrelevant inputs that aren't useful, so the next step will be to remove unnecessary data

there are chances where the data set is biased, and will give only one type of result after it's trained. So before training, we'll have to make it unbiased by adding or removing or making some legitimate changes in the data se The other problem that can be faced is in the integration of Flask with the frontend and backend, this is an important aspect of the project since because of this integration the project will be able to work

Built With

• colab
• css
• django
• html
• javascript
• jupyter
• python