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segAll-tamper-localiser
mymani/segAll-tamper-localiser
segAll-tamper-localiser is a image segmentation model from mymani. Use it for the image segmentation task on the model card, and read the license before you ship it in a product. The card lists the license as other.
Document-tamper localiser: given a rendered document page image, outputs a per-pixel tamper-probability logit map. SegFormer-B2 (nvidia/mit-b2 backbone) widened from 3 to 6 input channels (RGB + 3 fixed SRM high-pass…
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At a glance
- Task
- Image Segmentation
- License
- other
- Model type
- segformer
- Access
- Public
- Created
- Sep 23, 2026
- Updated
- Sep 23, 2026
- SHA
- 3f0d9088
Base models
Model card
From the Hugging Face model README
segAll tamper localiser (trained 2026-09-22)
Document-tamper localiser: given a rendered document page image, outputs a per-pixel
tamper-probability logit map. SegFormer-B2 (nvidia/mit-b2 backbone) widened from 3 to 6
input channels (RGB + 3 fixed SRM high-pass residual channels computed from luminance),
num_labels=1 binary tamper-vs-clean logit map.
Usage
from transformers import SegformerForSemanticSegmentation
model = SegformerForSemanticSegmentation.from_pretrained(
"mymani/segAll-tamper-localiser", revision="2026-09-22"
)
pixel_values must already be the 6-channel (RGB + 3 SRM residual) input described above —
see the reference wrapper linked above for the exact preprocessing.
- Task
- Image Segmentation
- Type
- segformer
- License
- other
- Created
- Sep 23, 2026
- Updated
- Sep 23, 2026