I have a numpy array batch of shape (32,5). Each element of the batch consists of a numpy array batch_elem = [s,_,_,_,_] where s = [img,val1,val2] is a 3-dimensional numpy array and _ are simply scalar values.
img is an image (numpy array) with dimensions (84,84,3)
I would like to create a numpy array with the shape (32,84,84,3). Basically I want to extract the image information within each batch and transform it into a 4-dimensional array.
I tried the following:
b = np.vstack(batch[:,0]) #this yields a b with shape (32,3), type: <class 'numpy.ndarray'>
Now I would like to access the images (first index in second dimension)
img_batch = b[:,0] # this returns an array of shape (32,), type: <class 'numpy.ndarray'>
How can I best access the image data and get a shape (32,84,84,3)?
Note:
s = b[0] #first s of the 32 in batch: shape (3,) , type: <class 'numpy.ndarray'>
Edit:
This should be a minimal example:
img = np.zeros([5,5,3])
s = np.array([img,1,1])
batch_elem = np.array([s,1,1,1,1])
batch = np.array([batch_elem for _ in range(32)])