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)