The goal of this project is to automate the recognition of plants on the basis of their leaves. The input to the system would be a picture of a leaf and the output would be the name of the plant species to which it belongs. Currently, there are thousands, if not millions of plant species around the globe, therefore, this is not an easy task. Also, many medical fields which involve plants in creating medicines can find extensive use of this classifier. It can also be a simple smart-phone application where the user will take a picture of a plant leaf and instantly know the name of the species it belongs to.
The dataset for this problem contains around 1500 binary images. Apart from this, some feature details are also provided along with the image e.g. texture and shape, for which a separate attribute vector is given for each image individually. The original dataset is hosted on University of California (UCL)'s website (https://archive.ics.uci.edu/ml/datasets/leaf). There are a total of 99 plant species to a which a leaf could belong to and there are around 15 samples taken from each species which allows us to train the model efficiently.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
This software has the following requirements:
- Python 2.7 or later!
NumPy1.11 or laterTensorFlowMatplotlib
git clone https://github.com/adl1995/leaf-classification.git
cd leaf-classification
pip install -r requirements.txt
python learn.py
Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.
- Adeel Ahmad - adl1995
This project is not under any license.