fidelity --gpu 0 --fid --input1 path/to/dataset1 --input2 path/to/dataset2 除了命令行脚本外,torch-fidelity还提供了 Python API。我们可以在 Python 脚本里加入算 FID 的代码。 import torch_fidelity metrics_dict = torch_fidelity.calculate_metrics( input1='path1', input2='path2', fid=True ...
from torch_fidelity import calculate_metrics # Each input can be either a string (path to images, registered input), or a Dataset instance metrics_dict = calculate_metrics(input1, input2, cuda=True, isc=True, fid=True, kid=True, verbose=False) print(metrics_dict) # Output: # { # 'in...
Machine learning metrics for distributed, scalable PyTorch applications. - torchmetrics/src/torchmetrics/image/fid.py at master · Lightning-AI/torchmetrics
In TorchMetrics, we have for a long time provided the MetricCollection object for chaining such metrics together for an easy interface to calculate them all at once. However, in many cases, such a collection of metrics shares some of the underlying computations that have been repeated for every...
importtorch_fidelity Add the following lines at the end of epoch evaluation: wrapped_generator=torch_fidelity.GenerativeModelModuleWrapper(generator,128,'normal',0)metrics_dict=torch_fidelity.calculate_metrics(input1=wrapped_generator,input2='cifar10-train',cuda=True,isc=True,fid=True,kid=True,prc=...