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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:

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