Retuns tyre quality given a tyre image with about 99.3% accuracy.
See https://www.kaggle.com/code/dima806/tyre-quality-image-detection-vit for more details.
Classification report:
precision recall f1-score support
defective 1.0000 0.9854 0.9926 411
good 0.9856 1.0000 0.9928 412
accuracy 0.9927 823
macro avg 0.9928 0.9927 0.9927 823
weighted avg 0.9928 0.9927 0.9927 823
- Downloads last month
- 4
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
๐
Ask for provider support
Model tree for dima806/tyre_quality_image_detection
Base model
google/vit-base-patch16-224-in21k