Image Segmentation
Transformers
Safetensors
segformer
scientific
research
agricultural research
wheat
segmentation
crop phenotyping
global wheat
crop
plant
canopy
field
Instructions to use GlobalWheat/GWFSS_Segformer_b0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GlobalWheat/GWFSS_Segformer_b0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="GlobalWheat/GWFSS_Segformer_b0")# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("GlobalWheat/GWFSS_Segformer_b0") model = SegformerForSemanticSegmentation.from_pretrained("GlobalWheat/GWFSS_Segformer_b0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -31,7 +31,7 @@ import torch, torch.nn.functional as F
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from PIL import Image
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import numpy as np
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repo = "GlobalWheat/GWFSS_model_v1.
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processor = AutoImageProcessor.from_pretrained(repo)
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model = SegformerForSemanticSegmentation.from_pretrained(repo).eval()
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from PIL import Image
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import numpy as np
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repo = "GlobalWheat/GWFSS_model_v1.0"
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processor = AutoImageProcessor.from_pretrained(repo)
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model = SegformerForSemanticSegmentation.from_pretrained(repo).eval()
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