> For the complete documentation index, see [llms.txt](https://annotate-docs.dwaste.live/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://annotate-docs.dwaste.live/example/ripe-and-unripe-tomatoes-dataset.md).

# Ripe and Unripe Tomatoes Dataset

This dataset contains annotated images of tomatoes at various stages of ripeness. It is designed to support research and development in agricultural automation, specifically for training machine learning models to distinguish between ripe and unripe tomatoes. The dataset includes annotated images created using an [annotation lab](https://github.com/sumn2u/annotate-lab), ensuring precise and accurate labeling of ripeness status.

<figure><img src="/files/KeTzyExVCgB66jwGIthl" alt=""><figcaption><p>Ripe and Unripe Dataset</p></figcaption></figure>

The dataset is available on  [Kaggle](https://www.kaggle.com/datasets/sumn2u/riped-and-unriped-tomato-dataset/). . and consists of a total of 177 images. The class distribution shows 429 ripe and 440 unripe images, with 33 images classified as mixed.

<figure><img src="/files/uVIAaSrktnsIsPXbMuYA" alt=""><figcaption><p>Class distribution of ripe and unripe images</p></figcaption></figure>

<figure><img src="/files/aFYuYxHzGqVTQL6fayCx" alt=""><figcaption><p>Image counting both ripe and unripe tomatoes</p></figcaption></figure>

Some of the annotated image samples are shown below:

<figure><img src="/files/Ti6nanrbcejpxux7nMpx" alt=""><figcaption><p>Annotated Image Samples</p></figcaption></figure>