Train Dataset Means and stds

<h1>Train Dataset Means and stds</h1>
lat_mean = 39.95157130295544 

lat_std = 0.0006593704228342234

lon_mean = -75.19136178838008

lon_std = 0.0006865423903444358

<h1>Running Inference</h1>
model_path = hf_hub_download(repo_id="Latitude-Attitude/vit-gps-coordinates-predictor-with-filter", filename="vit-gps-coordinates-predictor-with-filter-3.pth") model = torch.load(model_path) model.eval()

with torch.no_grad(): for images in dataloader: images = images.to(device) outputs = model(images) preds = outputs.cpu() * torch.tensor([lat_std, lon_std]) + torch.tensor([lat_mean, lon_mean])