Instructions to use facebook/mask2former-swin-tiny-ade-semantic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/mask2former-swin-tiny-ade-semantic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="facebook/mask2former-swin-tiny-ade-semantic")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, Mask2FormerForUniversalSegmentation processor = AutoImageProcessor.from_pretrained("facebook/mask2former-swin-tiny-ade-semantic") model = Mask2FormerForUniversalSegmentation.from_pretrained("facebook/mask2former-swin-tiny-ade-semantic", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 538 Bytes
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"_max_size": 2048,
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"ignore_index": 255,
"image_mean": [
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],
"image_processor_type": "Mask2FormerImageProcessor",
"image_std": [
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],
"num_labels": 150,
"reduce_labels": false,
"resample": 2,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 384,
"width": 384
},
"size_divisor": 32
}
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