stylegan3/Snapshot_images.ipynb
2023-01-12 15:53:19 +01:00

11 KiB

Overview of snapshots

In [1]:
%run ThisPlaceDoesExist.ipynb
In [3]:
import tabulate
tabulate.tabulate([{"idx": i, **run.get_summary()} for i, run in enumerate(runs)], tablefmt='html', headers="keys", colalign=("left","left"))
Out[3]:
idx nr dataset conditional resolution gammaduration iterations last_fid
0 00001paris3 True 256 8.23 days, 10:34:26 2600 502.277
1 00002paris3 True 256 2 5 days, 3:43:08 6560 190.346
2 00003paris3 True 256 2 18 days, 13:01:50 25000 42.9661
3 00004paris3 False 256 2 15 days, 16:13:20 22800 15.6691
4 00009paris3-1024.zip False 1024 32 0:00:00 0 549.99
5 00010paris3-1024.zip False 1024 32 50 days, 3:15:24 15200 33.2466
6 00011paris3-1024.zip False 1024 10 5 days, 18:48:04 1760 200.356
7 00014paris3-cropped-256 False 256 8 2 days, 20:08:22 4160 20.1699
8 00016paris3-cropped-256 False 256 8 12 days, 16:48:33 18560 18.1838
9 00022VLoD-cropped2048-scaled1024False 1024 32 0:00:00 0 539.38
10 00023VLoD-cropped2048-scaled1024False 1024 32 1 day, 13:17:19 480 201.189
11 00024VLoD-cropped2048-scaled1024False 1024 32 13 days, 1:04:11 4000 65.2584
12 00025VLoD-cropped2048-scaled1024False 1024 16 19 days, 8:47:32 5920 391.724
In [ ]:
print(len(runs[-1].snapshots))
display(
    runs[8].snapshots[-80].time.isoformat(),
    runs[8].snapshots[-80].get_preview_img(7,1),
    runs[8].snapshots[-30].time.isoformat(),
    runs[8].snapshots[-30].get_preview_img(7,1),
    
    runs[8].snapshots[-20].time.isoformat(),
    runs[8].snapshots[-20].get_preview_img(7,1),
    
    runs[8].snapshots[-5].time.isoformat(),
    runs[8].snapshots[-5].get_preview_img(7,1),
    
    runs[8].snapshots[-2].time.isoformat(),
    runs[8].snapshots[-2].get_preview_img(7,1),
    
    runs[8].snapshots[-1].time.isoformat(),
    runs[8].snapshots[-1].get_preview_img(7,3)
)
In [ ]:
runs[-1].snapshots[-5].get_preview_img(7,2)