Advanced computer vision saliency maps week 4 assignment ssim score

[Luca_Macis]

First of all, I wanted to thank you for the mentor job and point out that I asked the question about creating the new post or not to simplify the whole process of teaching you and learning us.
Getting back to the problem:

@Deepti_Prasad

is this the way you recalled the labels or included label with 2?

I don’t know if I understood your question well, but this is the way I’m dealing with converting the labels in augmentimages, example:

indices before one hot encoding:
[0, 1]
indices after one hot encoding:
tf.Tensor(
[[1. 0.]
 [0. 1.]], shape=(2, 2), dtype=float32)

@Deepti_Prasad

Please give detail about which activation you have used for the last dense layer in your model?

Currently I’m using softmax because I want “the sum of the probabilities adds up to 1.” I also used the sigmoid just to see if the accuracy could have improved.

@Deepti_Prasad

The most common mistake by learners in this assignment was related def do salience grader cell where the learner missed converting the image from BGR to RGB, check if you have done this.

I did this (not writing the whole because of the CoC):
tf.reverse(..., ...)

@Deepti_Prasad

The next usual mistake one can do in the below statement of def do salience grader cell
Define the expected output array by one-hot encoding the label, how have you recalled image shape in this code.

First, I expanded the dimensionality of the image as requested with tf.expand_dims where I added the batch dimension. Then I defined the expected output using the batch dimensionality of the new expanded image. That is, I used tf.one_hot and multiplied [label] by the batch size of the new expanded image, and depth set equal to the number of classes.

@Deepti_Prasad

Next let me which loss you used in GradientTape block

Categorical Cross Entropy, since dealing with 2 classes. I also tried the Binary with no improvement. Am I wrong in using them?

@Deepti_Prasad

Next create your model compile statement based on the instructions given below

Yes, I did it.

@Deepti_Prasad

The last thing you need to confirm is if you have run the Optional: Saliency Maps at 95 epochs.

Yes (but not every time), because I wanted to see if do_salience() was working as expected.

Thank you again

Regards,
Luca