FASAL AI , FASAL means crop ....
Agriculture has always been close to me because my father, friends and people around me are connected with farming. 🌾
That personal interest motivated me to try out something as simple as:
Can we make use of AI and computer vision to solve real world problems in agriculture?
And thus began my journey to create FASAL AI.
Crop AI is an open-sourced deep learning project which takes in an image of a crop and classifies it into one of five crops:
🌾 Wheat
🌾 Rice
🌽 Maize
🍌 Banana
🍈 Guava
For the Guava, it also grades the quality of the fruit into:
A → B → C → Reject
The project is made using TensorFlow, Keras and EfficientNetB0 for image classification and is ready to be expanded upon for other agricultural solutions.
📊 Here are some results:
Crop Classification: 91.76% test accuracy
Guava Quality Grading: 78.27% test accuracy
Total Dataset: 14,194 images
Crop Classes: 5
Quality Classes: A / B / C / Reject
This project is open-sourced and hosts the trained models and an inference script.
🚀 In the future, I would like to expand upon this project and do things like:
More crop classifications
Disease detection
Quality grading for more crops
Bigger and more diverse field dataset
Camera prediction in real time
Mobile applications for agriculture
For me, this isn't just another AI project. It's an attempt to use what I'm interested in (technology) to solve a problem which effects my family and community.
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