| """RFID (reconstruction FID) via torch-fidelity. For stage-2 generation FID, | |
| use the fd_evaluator path via `evaluate_image_set`.""" | |
| from torch_fidelity import calculate_metrics | |
| from .utils import ImgArrDataset | |
| def calculate_rfid( | |
| arr1, | |
| arr2=None, | |
| bs=64, | |
| device="cuda", | |
| fid_statistics_file=None, | |
| ): | |
| arr1_ds = ImgArrDataset(arr1) | |
| if fid_statistics_file is not None: | |
| metrics_kwargs = dict( | |
| input1=arr1_ds, | |
| input2=None, | |
| fid_statistics_file=fid_statistics_file, | |
| batch_size=bs, | |
| fid=True, | |
| cuda=(device == "cuda"), | |
| ) | |
| else: | |
| if arr2 is None: | |
| raise ValueError("Either arr2 or fid_statistics_file must be provided.") | |
| arr2_ds = ImgArrDataset(arr2) | |
| metrics_kwargs = dict( | |
| input1=arr1_ds, | |
| input2=arr2_ds, | |
| batch_size=bs, | |
| fid=True, | |
| cuda=(device == "cuda"), | |
| ) | |
| metrics = calculate_metrics(**metrics_kwargs) | |
| return metrics["frechet_inception_distance"] | |