Image Segmentation
Transformers
TensorBoard
Safetensors
segformer
semantic-segmentation
vision
ecology
Instructions to use restor/tcd-segformer-mit-b5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use restor/tcd-segformer-mit-b5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="restor/tcd-segformer-mit-b5")# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("restor/tcd-segformer-mit-b5") model = SegformerForSemanticSegmentation.from_pretrained("restor/tcd-segformer-mit-b5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download val_multiclassf1score_tree.png from restor/tcd-segformer-mit-b5: direct link, hf CLI and curl.
- Browser
- Download file 63.7 kB
-
https://huggingface.co/restor/tcd-segformer-mit-b5/resolve/main/val_multiclassf1score_tree.png
- Command line
-
hf download hf://restor/tcd-segformer-mit-b5/val_multiclassf1score_tree.png
-
curl -L -o val_multiclassf1score_tree.png https://huggingface.co/restor/tcd-segformer-mit-b5/resolve/main/val_multiclassf1score_tree.png
63.7 kB
