---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy

model-index:
- name: fruit-ripeness
  results:
  - task:
      name: Image Classification
      type: image-classification
    metrics:
      - name: Accuracy
        type: accuracy
        value: 0.28518518805503845
---

# fruit-ripeness


Autogenerated by HuggingPics🤗🖼️

Create your own image classifier for **anything** by running [the demo on Google Colab](https://colab.research.google.com/github/nateraw/huggingpics/blob/main/HuggingPics.ipynb).

Report any issues with the demo at the [github repo](https://github.com/nateraw/huggingpics).


## Example Images


#### ripe apple

![ripe apple](images/ripe_apple.jpg)

#### ripe mango

![ripe mango](images/ripe_mango.jpg)

#### ripe papaya

![ripe papaya](images/ripe_papaya.jpg)

#### ripe pomegranate

![ripe pomegranate](images/ripe_pomegranate.jpg)

#### rotten apple

![rotten apple](images/rotten_apple.jpg)

#### rotten mango

![rotten mango](images/rotten_mango.jpg)

#### rotten papaya

![rotten papaya](images/rotten_papaya.jpg)

#### rotten pomegranate

![rotten pomegranate](images/rotten_pomegranate.jpg)

#### unripe apple

![unripe apple](images/unripe_apple.jpg)

#### unripe mango

![unripe mango](images/unripe_mango.jpg)

#### unripe papaya

![unripe papaya](images/unripe_papaya.jpg)

#### unripe pomegranate

![unripe pomegranate](images/unripe_pomegranate.jpg)