Image Classification
Transformers
Safetensors
English
vit
vision
biology
ecology
phenology
plants
plant-phenology
iNaturalist
Eval Results (legacy)
Instructions to use phenobase/phenovision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use phenobase/phenovision with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="phenobase/phenovision") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("phenobase/phenovision") model = AutoModelForImageClassification.from_pretrained("phenobase/phenovision", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| class,threshold,j_index,sensitivity,specificity | |
| flower,0.48,0.9062895276795253,0.9689872611744661,0.9373022665050592 | |
| fruit,0.6,0.7545785425230225,0.7735197611977522,0.9810587813252704 | |