Sorry for bad image.
data_dir = "C:/Users/Majid/Desktop/data/LSP"   # Loading dataset
joints_dir = pjoin(data_dir, "joints")         
mat_file = sio.loadmat(joints_dir)             # Reading joints.mat
joints = mat_file['joints']
angle = []
image_list = []
for filename in glob.glob('C:/Users/Majid/Desktop/data/LSP/images/*.jpg'): # Reading images from dataset
    im=Image.open(filename)

    image_list.append(np.asarray(im))

image_list=np.array(image_list)

then i did padding like this:
i = 0
padded = []
shifted_x = []
shifted_y = []
for x in image_list:
    fram=np.zeros((y_max, x_max,3),dtype='uint8')        # Creating a blank space with dimension of maximum x and y
    # Location each images inside of each blank space with shifting to the center
    fram[int((y_max-y_shape[i])/2):y_shape[i]+int((y_max-y_shape[i])/2), int((x_max-x_shape[i])/2):x_shape[i]+int((x_max-x_shape[i])/2)] = x
    shifted_x.append(int((x_max-x_shape[i])/2))
    shifted_y.append(int((y_max-y_shape[i])/2))
    padded.append(fram)
    i = i+1
padded = np.array(padded)
padded = padded/255

images_data=[]
for j in padded:
    image_new = transforms.functional.to_pil_image(j,mode="RGB")
    images_data.append(image_new)

now when I plot it it gave me wrong picture. I also tried to change it to CHW, but it get worse.