🐶 & 🐱
This is to try on basic image-classification using Tansfer Learning and CNN-(Convolutional Neural Network) for classifying cats and dogs. The dataset is taken from Microsoft cat & dog dataset
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I will read all the images and convert them to a multi-dimension array. I have seen a lot of other approaches online where people have converted the image in greyscale but for a challenge, I will be doing with RGB.
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After converting in an array, the image will be label whether Cat or Dogs.
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The arrays of the image which will be stacked on top using NumPy for giving the input to NN-(Neural Network)
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After Training of the model depending on the statics the fine-tuning of the model will be done or feature engineering for increasing the accuracy of the model
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This script file read images from the location and converts its in numpy array and saves it to.
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This file also spilts the data in train and test for each X and Y
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The file are made of function so it can be imported and used in other projects
This floder contain an sample of test data_set which is maded by Data_Preprocessing.py
V0.0.0 - Intialization of Reppo
V0.0.1 - Deciding Apporach
V0.1.0 - Made Data_precoressing.py
V0.1.1 - Made Data_Preprocessing.py in funtional/Modular manner
V0.1.2 - Added Sample Data of X_test and Y_test