This project focuses on identifying medicinal herbs using deep learning techniques. The model is trained on images of various medicinal plants to classify them accurately. The goal is to provide an efficient and automated way to recognize medicinal herbs, which can be useful for researchers, herbalists, and the general public.
- Image-based Identification: Uses deep learning models to classify medicinal herbs.
- Dataset Processing: Preprocessing techniques applied to ensure high model accuracy.
- Deep Learning Model: Trained using MobileNet DL V3
- User Interface: A simple UI for users to upload images and get predictions.
- Deep Learning Framework: TensorFlow / PyTorch
- Programming Language: Python
- Libraries:
- OpenCV for image preprocessing
- NumPy & Pandas for data handling
- Matplotlib/Seaborn for visualization
- Scikit-learn for evaluation metrics
- Dataset: Custom dataset of medicinal herbs (collected or sourced from online repositories)
- Clone the repository:
git clone https://github.com/sreenaddh/medicinal-herb-identification.git cd medicinal-herb-identification