Inspiration
India, with a rich heritage of floral diversity, is well-known for its medicinal plant wealth, but their identification is one of the major burning issues in Ayurvedic Pharmaceutics. Several crude drugs are being sold under the same name in the market leading to confusion and their misidentification. Even the collectors and traders are not completely aware of the exact morphological appearance or differentiating attributes of the many drugs owing to seasonal and geographical availability, and similar characteristics.
What it does
software capable of identifying different medicinal plants/ raw materials through Image Processing Using Different Machine Learning Algorithms. The Medicinal Plant Recognition and Feature Analysis project harnesses the power of machine learning to provide a user-friendly tool for plant enthusiasts, herbalists, and researchers. By accurately identifying medicinal plants and extracting their features
How we built it
The model is trained using tensorflow and opencv by using the dataset from kaggle. we have tried using flask as framework for integrating the model with web framework.
Challenges we ran into
The whole project was challenging for our team some of the aspects where we struggled most were: 1.Integrating the model with web interface
2.*Training the model correctly for obtaining suitable and correct output *
Accomplishments that we're proud of
** trained the model with about 40 plant species** achieved a good accuracy rate with the availabke datset
What we learned
1.** as a beginner in machine learning we are proud of the success we have made in the development of the project.**
- we learned the two main aspects of a macine learning model which are availibility of a good dataset and the processing of dat before training.
What's next for AyurTech
we are looking forward to train the model with a good real time collected datset from diffrent regions.
Log in or sign up for Devpost to join the conversation.