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_b4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GlobalWheat/GWFSS_Segformer_b4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="GlobalWheat/GWFSS_Segformer_b4")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("GlobalWheat/GWFSS_Segformer_b4") model = SegformerForSemanticSegmentation.from_pretrained("GlobalWheat/GWFSS_Segformer_b4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download class.json from GlobalWheat/GWFSS_Segformer_b4: direct link, hf CLI and curl.
- Browser
- Download file 347 Bytes
-
https://huggingface.co/GlobalWheat/GWFSS_Segformer_b4/resolve/main/class.json
- Command line
-
hf download hf://GlobalWheat/GWFSS_Segformer_b4/class.json
-
curl -L -o class.json https://huggingface.co/GlobalWheat/GWFSS_Segformer_b4/resolve/main/class.json
347 Bytes
| [ | |
| { | |
| "id": 0, | |
| "name": "background", | |
| "color": [0, 0, 0] | |
| }, | |
| { | |
| "id": 1, | |
| "name": "head", | |
| "color": [50, 255, 132] | |
| }, | |
| { | |
| "id": 2, | |
| "name": "stem", | |
| "color": [50, 132, 255] | |
| }, | |
| { | |
| "id": 3, | |
| "name": "leaf", | |
| "color": [214, 255, 50] | |
| } | |
| ] |