Unable to understand what to do with the output of im2col.py of this repo

[atifkarim]

Hello, I am trying to follow your im2col code. My intention is to do the forward pass of an RGB image without using any framework API. Right now I am using Keras.

I have started i the following way --

1/ Extract the weight from the model using layer.get_weights() 2/ Then I have appended the output of layer.get_weights() in a list named layerdic 3/ I have assigned an array conv_kernel and stored here the value of layerdic[0][0] and another array named conv_bias where I have stored layerdic[0][1]. If I am not wrong conv_kernel stores the value of kernel weight and conv_bias stores the bias value which I need for convolution. 4/ Then I have assigned an input image in X_test array and has done the convolution with your code.

My query is now ---

1/ What is the significance of out and cache and where do I need these values for the next part of forward pass? 1/ How can I do the next calculation. For example, in my case I will do the Flatten and Dense for classification. How can I approach for this purpose?

I am giving below my model:

    model = Sequential()

    model.add(Conv2D(1, (3, 3), padding='same',
                     input_shape=(3, IMG_SIZE, IMG_SIZE),
                     activation='relu'))
    model.add(Flatten())
    model.add(Dense(NUM_CLASSES, activation='softmax'))
    
    return model

model = cnn_model()

lr = 0.01
sgd = SGD(lr=lr, decay=1e-6, momentum=0.9, nesterov=True)
model.compile(loss='categorical_crossentropy',
          optimizer=sgd,
          metrics=['accuracy'])

Kindly please help me.