Object Classification

The classifier takes a 32x32x3 pixel colour image as input and predicts what object it is from 10 given objects.

The 10 classes are:
1.airplane										
2.automobile										
3.bird										
4.cat										
5.deer										
6.dog										
7.frog										
8.horse										
9.ship										
10.truck	

A Convolutional Neural Network was used.

The CIFAR-10 Data Set contained 50,000 training and 10,000 testing images was used to train the model.
Link to data set: http://www.cs.toronto.edu/~kriz/cifar.html

The resultant accuracy score was found to be 84.9%.

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-The source code of the project is the python file "code.py"
-The Output of the python program is available in the file "output.txt"