stylegan3/Snapshot_images.ipynb

Overview of snapshots¶

In [ ]:

In [1]:

import tabulate

In [2]:

%run ThisPlaceDoesExist.ipynb

In [3]:

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	gamma	duration	iterations	last_fid
0	00001	paris3	True	256	8.2	3 days, 10:34:26	2600	502.277
1	00002	paris3	True	256	2	5 days, 3:43:08	6560	190.346
2	00003	paris3	True	256	2	18 days, 13:01:50	25000	42.9661
3	00004	paris3	False	256	2	15 days, 16:13:20	22800	15.6691
4	00009	paris3-1024.zip	False	1024	32	0:00:00	0	549.99
5	00010	paris3-1024.zip	False	1024	32	50 days, 3:15:24	15200	33.2466
6	00011	paris3-1024.zip	False	1024	10	5 days, 18:48:04	1760	200.356
7	00014	paris3-cropped-256	False	256	8	2 days, 20:08:22	4160	20.1699
8	00016	paris3-cropped-256	False	256	8	7 days, 20:55:54	11520	16.5185

In [4]:

display(
    runs[-1].snapshots[-20].time.isoformat(),
    runs[-1].snapshots[-20].get_preview_img(7,1),
    
    runs[-1].snapshots[-5].time.isoformat(),
    runs[-1].snapshots[-5].get_preview_img(7,1),
    
    runs[-1].snapshots[-2].time.isoformat(),
    runs[-1].snapshots[-2].get_preview_img(7,1),
    
    runs[-1].snapshots[-1].time.isoformat(),
    runs[-1].snapshots[-1].get_preview_img(7,1)
)

'2022-11-23T14:38:03'

'2022-11-25T06:00:35'

'2022-11-25T13:52:48'

'2022-11-25T16:30:32'

In [32]:

# vertical_size = 256
# nth_snapshot = 5 # only show one very x snapshots (1 to show all)

# exclude_runs = [0,1]

# for i, run in enumerate(runs):
#     if i in exclude_runs:
#         continue
#     display(md(f"## {run.id}"))
#     for j, snapshot in enumerate(run.snapshots):
#         if j % nth_snapshot != 0:
#             continue
#         # if 
#         img = snapshot.get_preview_img(5,1)
#         img = img.resize((int(img.size[0] / (img.size[1]/vertical_size)), vertical_size))
#         print(f"{j}: {snapshot.iteration_str}")
#         display(img)