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Image Classifier

This repository contains the scripts to develop a image classifier in PyTorch.

Usage

Utils.py

Utils provides functions for following list of activites.

Data preparation

This python script provides the neccessary functions for preparing the dataset by doing the following operations

  • Builds a PyTorch Dataset using downloaded MNIST dataset
  • DataLoader which includes data transformation

Plotting

  • provides function for plotting a x number of images from a batch.

Performance

  • provides utils function to calculate the accuracy of the model based on the prediction and actuals of target values.

Model.ipynb

This script helps us create a PyTorch convolution model with following architecture and it has the functions for training and testing the script. Also helps us with plotting the performance curves.

----------------------------------------------------------------
        Layer (type)               Output Shape         Param #
================================================================
            Conv2d-1           [-1, 32, 26, 26]             320
            Conv2d-2           [-1, 64, 24, 24]          18,496
            Conv2d-3          [-1, 128, 10, 10]          73,856
            Conv2d-4            [-1, 256, 8, 8]         295,168
            Linear-5                   [-1, 50]         204,850
            Linear-6                   [-1, 10]             510
================================================================
Total params: 593,200
Trainable params: 593,200
Non-trainable params: 0
----------------------------------------------------------------
Input size (MB): 0.00
Forward/backward pass size (MB): 0.67
Params size (MB): 2.26
Estimated Total Size (MB): 2.94
----------------------------------------------------------------

S5.ipynb

This notebooks high level scripts to build the overall pipeline tofor building the Image classifier and render visualizations of images and model performance.