datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
wood_surface_defectsKodytek P, Bodzas A and Bilik P. A large-scale image dataset of wood surface defects for automated vision-based quality control processes [version 2; peer review: 2 approved]. F1000Research 2022, 10:581 (https://doi.org/10.12688/f1000research.52903.2)
Bounding boxes only, semantic maps
All images are 2800 x 1024 pixels (width x height)
Images compressed using
PIL.Image.Image.save(
format="JPEG",
optimize=True,
quality=50,
)
Bounding boxes converted to YOLO format.
TODO: loader… See the full description on the dataset page: https://huggingface.co/datasets/iluvvatar/wood_surface_defects.wood_surface_defectsKodytek P, Bodzas A and Bilik P. A large-scale image dataset of wood surface defects for automated vision-based quality control processes [version 2; peer review: 2 approved]. F1000Research 2022, 10:581 (https://doi.org/10.12688/f1000research.52903.2)
Bounding boxes only, semantic maps
All images are 2800 x 1024 pixels (width x height)
Images compressed using
PIL.Image.Image.save(
format="JPEG",
optimize=True,
quality=50,
)
Bounding boxes converted to YOLO format.
TODO: loader… See the full description on the dataset page: https://huggingface.co/datasets/ema1995/wood_surface_defects.wood_surface_defectsKodytek P, Bodzas A and Bilik P. A large-scale image dataset of wood surface defects for automated vision-based quality control processes [version 2; peer review: 2 approved]. F1000Research 2022, 10:581 (https://doi.org/10.12688/f1000research.52903.2)
Bounding boxes only, semantic maps
All images are 2800 x 1024 pixels (width x height)
Images compressed using
PIL.Image.Image.save(
format="JPEG",
optimize=True,
quality=50,
)
Bounding boxes converted to YOLO format.
TODO: loader… See the full description on the dataset page: https://huggingface.co/datasets/zhanwushen/wood_surface_defects.wood_surface_defectsKodytek P, Bodzas A and Bilik P. A large-scale image dataset of wood surface defects for automated vision-based quality control processes [version 2; peer review: 2 approved]. F1000Research 2022, 10:581 (https://doi.org/10.12688/f1000research.52903.2)
Bounding boxes only, semantic maps
All images are 2800 x 1024 pixels (width x height)
Images compressed using
PIL.Image.Image.save(
format="JPEG",
optimize=True,
quality=50,
)
Bounding boxes converted to YOLO format.
TODO: loader… See the full description on the dataset page: https://huggingface.co/datasets/Meshal777/wood_surface_defects.