Skip to content

Flower Image Classification project using convolutional neural networks (CNN) in TensorFlow. The trained model can classify flower images into 5 categories with high accuracy. GUI application built using tkinter to demonstrate the model's prediction capabilities.

Notifications You must be signed in to change notification settings

mishrababhishek/flower_image_classification

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Flower Image Classification

This is a simple project that uses a convolutional neural network (CNN) to classify images of flowers into different categories. The project consists of two Python files:

  • model_trainer.py: This file contains the code to train the CNN model using the flower images.
  • app.py: This file contains a GUI application that allows the user to select an image of a flower and get a prediction of the flower's category.

Dataset

The dataset used in this project contains images of five different types of flowers:

  • Daisy
  • Dandelion
  • Rose
  • Sunflower
  • Tulip

The images are stored in the flowers directory, which is organized into subdirectories for each flower type.

Training the Model

To train the model, simply run the model_trainer.py file. The script will load the images from the flowers directory, preprocess them, and train the CNN model using TensorFlow. The trained model will be saved to a file named flower_classifier.

Running the Application

To run the GUI application, simply run the app.py file. The application will open a window that allows the user to select an image of a flower. Once the user selects an image, the application will preprocess the image, make a prediction using the trained CNN model, and display the predicted flower category.

Requirements

This project requires the following Python packages:

  • TensorFlow
  • Pillow
  • tkinter

To install these packages, you can use pip:

pip install tensorflow pillow tkinter

Conclusion

This is a simple project that demonstrates how to use a CNN to classify images of flowers. The project can be easily extended to include other types of images or to improve the accuracy of the model.

About

Flower Image Classification project using convolutional neural networks (CNN) in TensorFlow. The trained model can classify flower images into 5 categories with high accuracy. GUI application built using tkinter to demonstrate the model's prediction capabilities.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published