Preprocesses a common canvas dataset (you can easily edit this to change to the CC-BY, CC-BY-SA, CC-BY-NC, CC-BY-ND, CC-BY-NC-ND, or CC-BY-NC-SA datasets, CC-BY by default).
Requires the whole dataset to be downloaded
First it reorganises to remove the 10 top layer folders, then since we resize all images to the same pixel count, we remove the resolutions folders, only keeping the aspect ratio folders.
Folder structure goes from:
0
least_dim_range=256-512
aspect_ratio_bucket=1-1
00001.parquet
00002.parquet
...
12345.parquet
aspect_ratio_bucket=1-2
...
aspect_ratio_bucket=19-13
least_dim_range=512-768
...
least_dim_range=2048-4096
1
...
...
9
...
to
aspect_ratio_bucket=1-1
00001.parquet
00002.parquet
...
12345.parquet
aspect_ratio_bucket=1-2
...
aspect_ratio_bucket=19-13
43 commits
Python
95.8%
Jupyter Notebook
4.2%
Preprocesses a common canvas dataset (you can easily edit this to change to the CC-BY, CC-BY-SA, CC-BY-NC, CC-BY-ND, CC-BY-NC-ND, or CC-BY-NC-SA datasets, CC-BY by default).
Requires the whole dataset to be downloaded
First it reorganises to remove the 10 top layer folders, then since we resize all images to the same pixel count, we remove the resolutions folders, only keeping the aspect ratio folders.
Folder structure goes from:
0
least_dim_range=256-512
aspect_ratio_bucket=1-1
00001.parquet
00002.parquet
...
12345.parquet
aspect_ratio_bucket=1-2
...
aspect_ratio_bucket=19-13
least_dim_range=512-768
...
least_dim_range=2048-4096
1
...
...
9
...
to
aspect_ratio_bucket=1-1
00001.parquet
00002.parquet
...
12345.parquet
aspect_ratio_bucket=1-2
...
aspect_ratio_bucket=19-13
43 commits
Python
95.8%
Jupyter Notebook
4.2%