---
language:
- en
license: cc-by-nc-nd-4.0
task_categories:
- image-classification
- image-to-image
- object-detection
tags:
- code
- biology
dataset_info:
  features:
  - name: id
    dtype: int32
  - name: name
    dtype: string
  - name: image
    dtype: image
  - name: mask
    dtype: image
  - name: width
    dtype: uint16
  - name: height
    dtype: uint16
  - name: shapes
    sequence:
    - name: label
      dtype:
        class_label:
          names:
            '0': strawberry
    - name: type
      dtype: string
    - name: points
      sequence:
        sequence: float32
    - name: rotation
      dtype: float32
    - name: attributes
      sequence:
      - name: name
        dtype: string
      - name: text
        dtype: string
  splits:
  - name: train
    num_bytes: 127730244
    num_examples: 40
  download_size: 126412271
  dataset_size: 127730244
---
# Ripe Strawberries Detection

The dataset consists of photos of strawberries for the identification and recognition of **ripe berries**. 
The images are annotated with **bounding boxes** that accurately demarcate the location of the ripe strawberries within the image.

Each image in the dataset showcases a strawberry plantation, and includes a diverse range of *backgrounds, lighting conditions, and orientations*. The photos are captured from various *angles and distances*, providing a realistic representation of strawberries.

The dataset can be utilised for enabling advancements in *strawberry production, quality control, and greater precision in agricultural practices*.

![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F2d778d74efed2287072dc1757ff9953c%2FFrame%209.png?generation=1694156229544667&alt=media)

# Get the dataset

### This is just an example of the data

Leave a request on [**https://trainingdata.pro/data-market**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=ripe-strawberries-detection) to discuss your requirements, learn about the price and buy the dataset.

# Dataset structure
- **images** - contains of original images of strawberries
- **boxes** - includes bounding box labeling for the original images
-  **annotations.xml** -  contains coordinates of the bounding boxes and labels, created for the original photo

# Data Format

Each image from `images` folder is accompanied by an XML-annotation in the `annotations.xml` file indicating the coordinates of the bounding boxes for ripe strawberries detection. For each point, the x and y coordinates are provided. Visibility of the ripe strawberry is also provided by the attribute **occluded** (0, 1).

# Example of XML file structure
![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F88f5b20367a30de6a40961fb40ccacc6%2Fcarbon.png?generation=1694156401436654&alt=media)

# Strawberry Detection might be made in accordance with your requirements.


## [**TrainingData**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=ripe-strawberries-detection) provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets**

TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets**