Code base for Object detection on CIFAR10 using Pytorch

This repo is the internal engine for our Object detection projects on CIFAR10 using Pytorch. Lets take a look at the components:

model

Here you can find code structure for all the models that we have used. Following is the list, for now:

• Resnet18
• custom_resnet

utils

Home for code related to processing and augmentation of images. Current residents:

• gradcam.py

  Gradcam code to visually understand parts of the image that our model is focusing on.

  Reference: Kazuto Nakashima

• utils.py

  Contains following processes:

  • Mean and Standard Deviation calculation
  • Image Transformation
  • Downloading the Dataset
  • Dataloaders
  • Display sample images from the dataset
  • Plot loss and accuracy graphs
  • Seeding
  • Display images that were misclassified

• lr_finder.py

  Calculate the best max_lr parameter for OneCycleLR.

main.py

You can find all the major orchestration code here. Currently available:

• train
• test
• main

This repo is constantly being updated based on all the new and intersting Computer Vision tasks we do. Do visit again!

Contributors

Abhiram Gurijala
Arijit Ganguly
Rohin Sequeira