metadata
library_name: transformers
pipeline_tag: image-segmentation
tags:
- vision
- image-segmentation
- dit
datasets:
- ds4sd/DocLayNet-v1.1
widget:
- src: >-
https://upload.wikimedia.org/wikipedia/commons/c/c3/LibreOffice_Writer_6.3.png
example_title: Wiki
Trained for 4 epochs.
model = BeitForSemanticSegmentation.from_pretrained("microsoft/dit-base", num_labels=11)
ds = load_dataset("ds4sd/DocLayNet-v1.1")
mask = np.zeros([11, 1025, 1025])
for b, c in zip(d["bboxes"], d["category_id"]):
b = [np.clip(int(bb), 0, 1025) for bb in b]
mask[c - 1][b[1]:b[1]+b[3], b[0]:b[0]+b[2]] = 1
mask = [cv2.resize(a, dsize=(56, 56), interpolation=cv2.INTER_AREA) for a in mask]
d["label"] = np.stack(mask)