karansondh / bee-classifictaion

Classifier that predicts bee species from images. We have used Support Vector Machine(SVM) model. It can predict different bee species with an accuracy of 68%.

Bee Classification Model🐝

A model that can automatically detect honey bees and bumble bees in images. Can a machine distinguish between a honey bee and a bumble bee? Being able to identify bee species from images, while challenging, would allow researchers to more quickly and effectively collect field data. In this project, you will use the Python image library Pillow to load and manipulate image data, then build a model to identify honey bees and bumble bees given an image of these insects.

Project Tasks📌

1. Import Python libraries
2. Display image of each bee type
3. Image manipulation with rgb2gray
4. Histogram of oriented gradients
5. Create image features and flatten into a single row
6. Loop over images to preprocess
7. Split into train and test sets
8. Scale training and test features
9. Perform PCA
10. Train and score our model
11. ROC curve + AUC

Installation and execution🎉

Install the following packages before running if not installed already- pip3 install scikit-image, pip3 install pillow and pip3 install scikit-learn After the installation of above packages the code can be executed by simply running all cells in the Jupyter Notebook.