Instructions to use mnjm/segformer-b0-voc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mnjm/segformer-b0-voc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="mnjm/segformer-b0-voc")# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("mnjm/segformer-b0-voc") model = SegformerForSemanticSegmentation.from_pretrained("mnjm/segformer-b0-voc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
segformer-bo-voc
Segormer b0 model trained from scratch on VoC 2007 and 2012 dataset using a custom training repo
Eval results can be found here
Run
from transformers import AutoImageProcessor, SegformerForSemanticSegmentation
processor = AutoImageProcessor.from_pretrained("mnjm/segformer-b0-voc")
model = SegformerForSemanticSegmentation.from_pretrained("mnjm/segformer-b0-voc")
inputs = processor(images=image, return_tensors="pt")
output = model(**inputs)
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