chiragbhuvaneshwara/cifar10project

DNN, Simple CNN, Alex Net, VGG Net, GoogLe Net and Resnet trained on CIFAR10 dataset using PyTorch. An associated Web Application developed where an image can be uploaded and classified.

cifar10Project

The following has been achieved in this project:

1. Multiple DNN, CNN, Transfer Learning Models have been trained using PyTorch and alayzed on CIFAR 10 dataset.
2. A web application has been created using Flask where you can access the 4 models having the highest accuracy on the test set.
3. All code here has been implemented by Chirag Bhuvaneshwara.

Note: The web application has been tested only in debug mode by running it as: python Flask_Web_App.py Flask_Web_App.py is found inside CIFAR10_Flask_Web_APP directory.

Accuracy achieved:

Models	Test Accuracy
Simple DNN	42.52%
Simple CNN	81.46%
VGG19_bn Net	91.06%
Alex Net	90.05%
GoogLeNet	95.78%
ResNet34	96.42%
Inception v3	*

*=> I was unable to train because of insufficient VRAM. Probably needs 16GB of VRAM.

Screenshots from the web app:

1. Homepage:

2. Prediction Page:

Contact Me:

• Name: Chirag Bhuvaneshwara
• Email: [email protected]