|
--- |
|
tags: |
|
- vision |
|
- image-classification |
|
datasets: |
|
- Kaludi/data-food-classification |
|
widget: |
|
- src: https://kristineskitchenblog.com/wp-content/uploads/2021/04/apple-pie-1200-square-592-2.jpg |
|
example_title: Apple Pie |
|
- src: https://upload.wikimedia.org/wikipedia/commons/d/da/Strawberry_ice_cream_cone_%285076899310%29.jpg |
|
example_title: Ice Cream |
|
- src: https://cdn.britannica.com/52/128652-050-14AD19CA/Maki-zushi.jpg |
|
example_title: Sushi |
|
co2_eq_emissions: |
|
emissions: 2.7745203231331614 |
|
--- |
|
|
|
# Food Classification |
|
|
|
This is a Food Image Classifier model that has been trained by [Kaludi](https://huggingface.co/Kaludi) to recognize 7 different types of popular foods, including **apple pie**, **falafel**, **french toast**, **ice cream**, **ramen**, **sushi**, and **tiramisu**. It can accurately classify an image of food into one of these categories by analyzing its visual features. This model can be used by food bloggers, restaurants, and recipe websites to quickly categorize and sort their food images, making it easier to manage their content and provide a better user experience. |
|
|
|
### Gradio |
|
|
|
Tis model supports a [Gradio](https://github.com/gradio-app/gradio) Web UI to run the data-food-classification model: |
|
[](https://huggingface.co/spaces/Kaludi/Food-Classification_App) |
|
|
|
|
|
## Validation Metrics |
|
|
|
- Loss: 0.094 |
|
- Accuracy: 0.977 |
|
- Macro F1: 0.977 |
|
- Micro F1: 0.977 |
|
- Weighted F1: 0.977 |
|
- Macro Precision: 0.978 |
|
- Micro Precision: 0.977 |
|
- Weighted Precision: 0.978 |
|
- Macro Recall: 0.977 |
|
- Micro Recall: 0.977 |
|
- Weighted Recall: 0.977 |
