ValueError: ('Cannot warp empty image with dimensions', (0, 24)) about deep_reinforcement_learning_course HOT 2 OPEN

Hi,
I'm having the same problem, with the exception of I'm not really adapting the code (I am adapting it to newer versions of python and packages: tf.compat.v1 is a thing). I tried to get around the ValueError problem with:

if (cropped_frame[np.ix_([0, -1], [0, -1])] == np.array([0, 0], [0, 0])).all(): cropped_frame[np.ix_([0, -1], [0, -1])] = np.array([1, 1], [1, 1])

Which gave:

IndexError: index 0 is out of bounds for axis 0 with size 0

Perhaps this can be interpreted as the state passed in as a frame is an empty array (or smaller than 40 x 60, as there's potentially cropping that happens). If you come across a solution, I'm all ears!

from deep_reinforcement_learning_course.

The initial state/frame is empty. Because transform.resize upsamples, only 1 pixel is necessary (not sure if there's a reason to use more, but more complexity meant more problems for me). Trying to give an array of zeros wouldn't run: Apparently I needed a 2- or 3- tuple. Giving a 3- tuple (each pixel, in my case, is RGB) failed on normalizing, because division doesn't work with tuples. Finally got:

if np.size(cropped_frame) < 1:
# pixel = tuple(np.array([0, 0, 0], dtype='uint8'))
cropped_frame = np.array([0, 0, 0], dtype='uint8')

To work. Since you're using greyscale, depending on where you look for the empty frame, you may not need the array.

from deep_reinforcement_learning_course.