Optimization failure due to data size

Hello,
I'm trying to apply localrf on my data. I've been able to run the pre-processing commands to estimate the flow and depth maps. However, once I run the optimization script, I get this error:

```bash
Traceback (most recent call last):
File ".\localTensoRF\train.py", line 609, in
reconstruction(args)
File ".\localTensoRF\train.py", line 190, in reconstruction
test_dataset = LocalRFDataset(
File "C:\Users\Administrateur\Desktop\COLMAP-Reconstruction\NeRF\localrf\localTensoRF\dataLoader\localrf_dataset.py", line 115, in __init__
self.activate_frames(n_init_frames)
File "C:\Users\Administrateur\Desktop\COLMAP-Reconstruction\NeRF\localrf\localTensoRF\dataLoader\localrf_dataset.py", line 125, in activate_frames
self.read_meta()
File "C:\Users\Administrateur\Desktop\COLMAP-Reconstruction\NeRF\localrf\localTensoRF\dataLoader\localrf_dataset.py", line 240, in read_meta
self.all_invdepths = np.stack(all_invdepths, 0)
File "<__array_function__ internals>", line 200, in stack
File "C:\Users\Administrateur\anaconda3\envs\localrf\lib\site-packages\numpy\core\shape_base.py", line 471, in stack
return _nx.concatenate(expanded_arrays, axis=axis, out=out,
File "<__array_function__ internals>", line 200, in concatenate
numpy.core._exceptions.MemoryError: Unable to allocate 3.86 GiB for an array with shape (500, 1080, 1920) and data type float32
```