README.md

---
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 Object Detection dataset

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.

# 💴 For Commercial Usage: To discuss your requirements, learn about the price and buy the dataset, leave a request on **[TrainingData](https://trainingdata.pro/datasets?utm_source=huggingface&utm_medium=cpc&utm_campaign=ripe-strawberries-detection)** to buy the dataset

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)

# 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.

# 💴 Buy the Dataset: This is just an example of the data. Leave a request on **[https://trainingdata.pro/datasets](https://trainingdata.pro/datasets?utm_source=huggingface&utm_medium=cpc&utm_campaign=ripe-strawberries-detection)** to discuss your requirements, learn about the price and buy the dataset

## **[TrainingData](https://trainingdata.pro/datasets?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**

*keywords: strawberry harvesting, ripeness, strawberry classification, mature strawberries, unripe, raw, overripe, detection system, harvestation stages, pluck strawberries, strawberry identification, berries, plantations, agriculture, mature fruit, greenhouse strawberries,  recognition accuracy, flowers, software development, image dataset, segmentation, object detection, bounding boxes*