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def create_video_from_images(images_folder, output_video, fps=10, duration=6):
    images = sorted(os.listdir(images_folder))

    # create path to the input images
    img_path = os.path.join(images_folder, images[0])
    
    # load image
    frame = cv2.imread(img_path)
    # extract dimensions of the image
    height, width, channels = frame.shape

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import cv2 # (OpenCV) version - 4.7.0
import os

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# predict next token
def predict(net, tkn, h=None):
         
  # tensor inputs
  x = np.array([[token2int[tkn]]])
  inputs = torch.from_numpy(x)
  
  # push to GPU
  inputs = inputs.cuda()

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def train(net, epochs=10, batch_size=32, lr=0.001, clip=1, print_every=32):
    
    # optimizer
    opt = torch.optim.Adam(net.parameters(), lr=lr)
    
    # loss
    criterion = nn.CrossEntropyLoss()
    
    # push model to GPU
    net.cuda()

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# instantiate the model
net = WordLSTM()

# push the model to GPU (avoid it if you are not using the GPU)
net.cuda()

print(net)

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class WordLSTM(nn.Module):
    
    def __init__(self, n_hidden=256, n_layers=4, drop_prob=0.3, lr=0.001):
        super().__init__()

        self.drop_prob = drop_prob
        self.n_layers = n_layers
        self.n_hidden = n_hidden
        self.lr = lr
        

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def get_batches(arr_x, arr_y, batch_size):
         
    # iterate through the arrays
    prv = 0
    for n in range(batch_size, arr_x.shape[0], batch_size):
      x = arr_x[prv:n,:]
      y = arr_y[prv:n,:]
      prv = n
      yield x, y

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def get_integer_seq(seq):
  return [token2int[w] for w in seq.split()]

# convert text sequences to integer sequences
x_int = [get_integer_seq(i) for i in x]
y_int = [get_integer_seq(i) for i in y]

# convert lists to numpy arrays
x_int = np.array(x_int)
y_int = np.array(y_int)

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# create integer-to-token mapping
int2token = {}
cnt = 0

for w in set(" ".join(movie_plots).split()):
  int2token[cnt] = w
  cnt+= 1

# create token-to-integer mapping
token2int = {t: i for i, t in int2token.items()}

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# create inputs and targets (x and y)
x = []
y = []

for s in seqs:
  x.append(" ".join(s.split()[:-1]))
  y.append(" ".join(s.split()[1:]))