I have just begun to use TensorFlow in python. I want to build a binary image classifier using CNN.
I found an example code on the internet: https://github.com/tensorflow/tensorflow/blob/r1.1/tensorflow/examples/tutorials/mnist/mnist_with_summaries.py The explanation is given here: https://www.tensorflow.org/get_started/mnist/pros This code builds a small Neural Network and uses the MNIST dataset to train and test it.
I roughly understood the working of the CNN but I didn't understand the code line by line.
I want to use the same code with my own Dataset of Images (for both training and testing). In the example the input images are converted into mx784, where m is the number of training/testing examples and 784 comes from flattened images of size 28x28 each. I have converted all my images into an array of size mx1024 using a python script and Similarly converted the ground truth into an array of size mx1. I have stored them into text file as X.txt and y.txt.
Now in the code I have changed the dimensions according to my image dimensions. However, I am confused how to feed the images into the network. Is there a way out other than going through the code line by line? I will be very grateful if you could help me out.