Download Project Document/Synopsis
Computer Vision is a field of study that helps to develop techniques to recognize images and displays. It has different features like image recognition, object detection and image creation, etc. We can detect objects present in an image like a human face, animal face, eyes, etc. We can use OpenCV to detect objects present in an image. OpenCV has many pre-trained models based on its features.
Our Leaf Detection System detects leaves from the image using Convolutional Neural Network (CNN) and OpenCV. It will also detect the type of leaf once it detects whether the image contains an image that is been provided.
In this system, the user will need to register first to log in to the system. With the credentials, they can log in to the system. The system will detect the leaf and the leaf type from an uploaded image. The user will just need to upload an image which contains a leaf in it.
This system will automatically detect the leaf from the image and once it finds the leaf it will further detect which type of leaf it is. The user will also be able to see the accuracy score.
The front-end involves Html, CSS, and JavaScript and the back-end involves Python. The framework used is Django and the database is MySQL. Here, we have implemented the OpenCV and CNN library. The dataset has been extracted from Kaggle.
Advantages
- It is easy to maintain.
- It is user-friendly.
- The system can easily detect the leaf from the image.
- It will also detect which type of leaf it is.
- The user can also be able to see the accuracy score.