Edit image as tensorflow tensor python

I'll do my best to provide a reproducible example here.

I have an image:

img

This image of Aaron Eckhart is (150, 150)

My goal is to perturb a ROI of this image by doing mathematical operations on the pixels, however, the issue is that the math must be done as a tensorflow tensor because the mathematical operation to be done is to multiply the tensor by it's scaled gradient (which is also a tensor of size (row_pixels, column_pixels, 3))

So here's the process I imagine:

1. Read in image as numpy array RGB size: (1, 150, 150, 3) (1 is batch size)

   w, h = img.shape

   ret = np.empty((w, h, 3), dtype=np.uint8)

   ret[:, :, 0] = ret[:, :, 1] = ret[:, :, 2] = img

2. Make pixel values between 0 and 1

   img = (faces1 - min_pixel) / (max_pixel - min_pixel)

3. for i in range(steps):

(a) extract ROI of image this is the part I don't understand how to do

(b) calculate gradient of smaller img ROI tensor's loss

loss = utils_tf.model_loss(y, preds, mean=False)
grad, = tf.gradients(loss, x)

(c) multiply img ROI tensor by gradient of loss

scaled_grad = eps * normalized_grad
adv_img = img + scaled_grad

(d) place this newly perturbed ROI tensor back into the same positions it was in the original tensor this is the other part I don't understand how to do

This will result in an image where only some of the pixel values have been perturbed and the rest remain the same

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