def eval_fvd(self, imageloader, storyloader, testloader, stage=1):
output_score_filename = os.path.join(self.save_dir, 'fvd_score.csv')
save_dir = os.path.join(self.save_dir, 'epoch') # tmep file for save the iamges
models = os.listdir(self.model_dir)
with open(output_score_filename, 'a') as f:
f.write('epoch,fvd\n')
for epoch in range(121, 0, -1):
if 'netG_epoch_{}.pth'.format(epoch) in models:
print('Evaluating epoch {}'.format(epoch))
netG = self.load_network_stageI(self.output_dir, load_ckpt=epoch)
inference_samples(netG, testloader, save_dir)
fvd_value = self.calculate_fvd(save_dir, epoch=epoch, num_of_video=272) #288)
with open(output_score_filename, 'a') as f:
f.write('{},{}\n'.format(epoch, fvd_value))
def inference(self, imageloader, storyloader, testloader, stage=1):
netG = self.load_network_stageI(self.output_dir, load_ckpt=self.load_ckpt)
inference_samples(netG, testloader, save_dir)