Hi FearlessMailbox
You can try using cv2.normalize:
frame = cv2.normalize(frame, None, 0, 255, cv2.NORM_MINMAX, dtype=cv2.CV_8UC1)
note that you are mostly getting disparity of 0 (outside threshold) and only a few values inside. You essentially have to scale those values to [0-255] and leave the outsize values 0 (stretching only the inner part where you are getting detections). One very idiotic way to do this is to move all 0 values to the lowest disparity value of the window you are looking at. This will ensure only the inner part gets normalized to 0-255.
It would be best to write a function that would ignore values outside the threshold and only stretch the inner part.
Hope it points you in the right direction,
Jaka