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Sponsored by
APIMart
zeromodels / mask2former-swin-tiny-ade-semantic
Model's Last Updated: August 27 2026
image-segmentation
Introduction of mask2former-swin-tiny-ade-semantic
Model Details of mask2former-swin-tiny-ade-semantic
See our collection for all versions of Mask2Former.
Run Mask2Former with Keras 3: JAX, PyTorch, or TensorFlow
kerasformers/mask2former-swin-tiny-ade-semantic
Paper: Masked-attention Mask Transformer for Universal Image Segmentation (arXiv:2112.01527) · HF Papers
Mask2Former improves MaskFormer with masked attention in the transformer decoder, restricting cross-attention to predicted mask regions for sharper boundaries and stronger universal segmentation.
For more details on the model, please go to the upstream model card .
Pure-
Keras 3
conversion of
facebook/mask2former-swin-tiny-ade-semantic
for
kerasformers
. One implementation runs unmodified on
TensorFlow / Torch / JAX
.
This is a
semantic
checkpoint (
Mask2FormerUniversalSegment
) (trained for semantic; architecture is universal).
✨ Quick start
import os
os.environ["KERAS_BACKEND"] = "torch" # or "jax" / "tensorflow"
from PIL import Image
from kerasformers.models.mask2former import Mask2FormerUniversalSegment, Mask2FormerImageProcessor
model = Mask2FormerUniversalSegment.from_weights("kerasformers/mask2former-swin-tiny-ade-semantic")
processor = Mask2FormerImageProcessor.from_weights("kerasformers/mask2former-swin-tiny-ade-semantic")
image = Image.open("your_image.jpg").convert("RGB")
output = model(processor(image)["pixel_values"], training=False)
result = processor.post_process_semantic_segmentation(
output, target_size=(image.height, image.width)
)
print(result["segmentation"].shape)
Load any Mask2Former variant the same way with
from_weights("kerasformers/<variant>")
:
| Variant | Hub | Task |
|---|---|---|
mask2former-swin-tiny-coco-instance
|
kerasformers/mask2former-swin-tiny-coco-instance
|
instance |
mask2former-swin-small-coco-instance
|
kerasformers/mask2former-swin-small-coco-instance
|
instance |
mask2former-swin-base-coco-instance
|
kerasformers/mask2former-swin-base-coco-instance
|
instance |
mask2former-swin-large-coco-instance
|
kerasformers/mask2former-swin-large-coco-instance
|
instance |
mask2former-swin-tiny-coco-panoptic
|
kerasformers/mask2former-swin-tiny-coco-panoptic
|
panoptic |
mask2former-swin-tiny-ade-semantic
|
kerasformers/mask2former-swin-tiny-ade-semantic
|
semantic |
Tips
-
Set
KERAS_BACKENDbefore importing Keras / kerasformers. - The task suffix is what the checkpoint was trained for; post-process accordingly.
- See Mask2Former docs and Loading Weights .
-
Community / upstream weights:
Mask2FormerUniversalSegment.from_weights("hf:facebook/mask2former-swin-tiny-ade-semantic").
Special Thanks
A huge thank you to the Facebook AI Research Mask2Former authors for creating and releasing these models.
License: MIT.
Runs of zeromodels mask2former-swin-tiny-ade-semantic on huggingface.co
36
Total runs
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24-hour runs
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3-day runs
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30-day runs
More Information About mask2former-swin-tiny-ade-semantic huggingface.co Model
Url of mask2former-swin-tiny-ade-semantic
mask2former-swin-tiny-ade-semantic huggingface.co Url
Provider of mask2former-swin-tiny-ade-semantic huggingface.co
Other API from zeromodels
Updated:August 27 2026
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