Add low VRAM mode, CPU-only mode + image pre-loading fix

[FlyingFathead]

1. Low VRAM mode implemented: Introduced the unimplemented option lingering around in streamlit_helpers.py to run the model with half-precision (float16). Allows efficient usage on GPUs with limited memory, lowering memory requirements by half. I've tested this on a RTX 3060 w/ 12GB VRAM.

2. CPU-only mode: added an option to run the model on CPUs for users without the necessary CUDA GPU hardware, though at slower speeds.

Both can be set with True/False in streamlit_helpers.py, although a more viable solution in the future would be to i.e. add a separate config.ini w/ configparser for the entire framework.

3. Image Loading Fix: Fixed an issue where the app would throw an error if an image was not loaded before model execution. The model now uses a dummy tensor until the image is loaded in. See: video_sampling.py