Multiclass-image-classification-using-tensorflow

In this project we classify images on basis of their object. There are 10 objects in the dataset we are using in this project.
The data set we use in this project is called cifar10. As the name suggests it contains 10 class and 6000 images.

Models Used:

• Convolution layer
• Dense Layer
• Adam optimizer
• Dropout
• Flatten

Additional feature:

• I have also created a gui using Tkinter with which we can acces the classifier module and classify the images.
• Prediction accuracy: 68%

HOW TO USE:

• Clone the repo
• Install tensor flow on your system
• First run the cifar10_classification
• Make sure the module is saved in the correct location/Copy the location of the module
• In the gui.py while loading the module make sure the mdule location is correct
• Run the gui.py for GUI experience

Sample Image of GUI: