Returns fast food type based on an image with about 98% accuracy.
See https://www.kaggle.com/code/dima806/fast-food-image-detection-vit for more details.
Classification report:
precision recall f1-score support
Burger 0.9466 0.9750 0.9606 400
Taco 0.9578 0.9650 0.9614 400
Baked Potato 0.9827 0.9925 0.9876 400
Hot Dog 0.9872 0.9698 0.9784 397
Pizza 0.9875 0.9875 0.9875 400
Sandwich 0.9724 0.9724 0.9724 399
Fries 0.9748 0.9675 0.9711 400
Donut 0.9827 1.0000 0.9913 397
Crispy Chicken 0.9822 0.9650 0.9735 400
Taquito 0.9923 0.9700 0.9810 400
accuracy 0.9765 3993
macro avg 0.9766 0.9765 0.9765 3993
weighted avg 0.9766 0.9765 0.9765 3993
- Downloads last month
- 21
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for dima806/fast_food_image_detection
Base model
google/vit-base-patch16-224-in21k