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,buffer_lower,buffer_upper,equivocal_lower,equivocal_upper,accuracy_cutoff,method | |
| flower,0.48,0.32499999999999996,0.385,0.15500000000000003,0.865,0.8,overall_accuracy | |
| fruit,0.6,0.40499999999999997,0.30500000000000005,0.195,0.905,0.8,overall_accuracy | |