metadata

library_name: transformers
tags: []

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Direct Use

from transformers import AutoImageProcessor
from transformers.models.detr import DetrForSegmentation

img_proc = AutoImageProcessor.from_pretrained(
    "ArkeaIAF/detr-layout-detection"
)
model = DetrForSegmentation.from_pretrained(
    "ArkeaIAF/detr-layout-detection"
)

with torch.inference_mode():
    input_ids = img_proc(img, return_tensors='pt')
    output = model(**input_ids)

threshold=0.4

segmentation_mask = img_proc.post_process_segmentation(
    out_seg,
    threshold=threshold,
    target_sizes=[img.size[::-1]]
)

bbox_pred = img_proc.post_process_object_detection(
    output,
    threshold=threshold,
    target_sizes=[img.size[::-1]]
)

Citation

@online{DeDetrLay,
  AUTHOR = {Cyrile Delestre},
  URL = {https://huggingface.co/cmarkea/detr-base-layout-detection},
  YEAR = {2024},
  KEYWORDS = {Image Processing ; Transformers ; Layout},
}