Minimum VRAM for GPU?

[arbenede]

What is the minimum amount of memory that will allow me to run CameraHMR? I am getting this error with an RTX 4060 that has 8 GB of VRAM:

~/projects/CameraHMR$ python demo.py --image_folder demo_images --output_folder output_images 
/home/arrigo/anaconda3/envs/camerahmr/lib/python3.10/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers
  warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning)
Traceback (most recent call last):
  File "/home/arrigo/projects/CameraHMR/demo.py", line 21, in <module>
    main()
  File "/home/arrigo/projects/CameraHMR/demo.py", line 17, in main
    estimator = HumanMeshEstimator()
  File "/home/arrigo/projects/CameraHMR/mesh_estimator.py", line 50, in __init__
    self.model = self.init_model()
  File "/home/arrigo/projects/CameraHMR/mesh_estimator.py", line 64, in init_model
    model = CameraHMR.load_from_checkpoint(CHECKPOINT_PATH, strict=False)
  File "/home/arrigo/anaconda3/envs/camerahmr/lib/python3.10/site-packages/pytorch_lightning/core/module.py", line 1531, in load_from_checkpoint
    loaded = _load_from_checkpoint(
  File "/home/arrigo/anaconda3/envs/camerahmr/lib/python3.10/site-packages/pytorch_lightning/core/saving.py", line 60, in _load_from_checkpoint
    checkpoint = pl_load(checkpoint_path, map_location=map_location)
  File "/home/arrigo/anaconda3/envs/camerahmr/lib/python3.10/site-packages/lightning_fabric/utilities/cloud_io.py", line 51, in _load
    return torch.load(f, map_location=map_location)  # type: ignore[arg-type]
  File "/home/arrigo/anaconda3/envs/camerahmr/lib/python3.10/site-packages/torch/serialization.py", line 809, in load
    return _load(opened_zipfile, map_location, pickle_module, **pickle_load_args)
  File "/home/arrigo/anaconda3/envs/camerahmr/lib/python3.10/site-packages/torch/serialization.py", line 1172, in _load
    result = unpickler.load()
  File "/home/arrigo/anaconda3/envs/camerahmr/lib/python3.10/pickle.py", line 1213, in load
    dispatch[key[0]](self)
  File "/home/arrigo/anaconda3/envs/camerahmr/lib/python3.10/pickle.py", line 1254, in load_binpersid
    self.append(self.persistent_load(pid))
  File "/home/arrigo/anaconda3/envs/camerahmr/lib/python3.10/site-packages/torch/serialization.py", line 1142, in persistent_load
    typed_storage = load_tensor(dtype, nbytes, key, _maybe_decode_ascii(location))
  File "/home/arrigo/anaconda3/envs/camerahmr/lib/python3.10/site-packages/torch/serialization.py", line 1116, in load_tensor
    wrap_storage=restore_location(storage, location),
  File "/home/arrigo/anaconda3/envs/camerahmr/lib/python3.10/site-packages/torch/serialization.py", line 217, in default_restore_location
    result = fn(storage, location)
  File "/home/arrigo/anaconda3/envs/camerahmr/lib/python3.10/site-packages/torch/serialization.py", line 187, in _cuda_deserialize
    return obj.cuda(device)
  File "/home/arrigo/anaconda3/envs/camerahmr/lib/python3.10/site-packages/torch/_utils.py", line 81, in _cuda
    untyped_storage = torch.UntypedStorage(
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 26.00 MiB (GPU 0; 7.75 GiB total capacity; 6.89 GiB already allocated; 27.50 MiB free; 7.04 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF