泰迪歪

> Many thanks for your help. I have packed some qualitative experiment results and the images of my quantitative experiment (if you needed) in the following Baidu Yun link. Thank...

> @oldrive What‘s your detailed setting for your reproduction. config: celeba-hq.yaml checkpoint: checkpoint_128_celeba-hq.pt compute_fid_script: use fid.py in stargan2 to compute fid between fake_images and real_images realism fid of L: fake_images...

The result of the realism_fid as follows: Group 1: realism_fid_latent_0: 31.692982996524883 realism_fid_latent_1: 31.671476972145367 realism_fid_latent_2: 31.620433186098698 realism_fid_latent_3: 31.629911284997206 realism_fid_latent_4: 31.73387679777522 realism_fid_reference_0: 32.591734278849 realism_fid_reference_1: 32.215290934387426 realism_fid_reference_2: 32.18949934088806 realism_fid_reference_3: 32.287988762946526 realism_fid_reference_4: 32.304219580808336 realism_fid_latent_average:...

> What's the command you used when you calculate the FID? Just like this: latent_fid_value = calculate_fid_given_paths([real_path, fake_latent_path[i]], args.img_size, args.batch_size)

> The "args.img_size" is set to be 128, right? right. parser.add_argument('--img_size', type=int, default=128, help='image resolution')

> What about the qualitative results. the results have replied in above mention.

> I mean the visual results. Oh, I misunderstand your means. some results of realism_latent_0 are here    some results of realism_reference_0 are here ![0...

> I mean the visual results. Every image in a fold has a different style of bangs.

> The visual results seems normal. Please change the image size used in FID to 256 or 224. I don't quite remember the setting here, since that the inception network...

> The visual results seems normal. Please change the image size used in FID to 256 or 224. I don't quite remember the setting here, since that the inception network...