TrainingDataPro/plantations_segmentation

---
license: cc-by-nd-4.0
task_categories:
- image-segmentation
- image-classification
- image-feature-extraction
- image-to-image
language:
- en
tags:
- biology
- code
- not-for-all-audiences
dataset_info:
features:
- name: image_id
dtype: int32
- name: image
dtype: image
- name: class_segmentation
dtype: image
- name: object_segmentation
dtype: image
- name: shapes
dtype: string
splits:
- name: train
num_bytes: 48297698
num_examples: 13
download_size: 48362120
dataset_size: 48297698
---

# Plantations Segmentation Object Detection dataset
The dataset consist of aerial photography of agricultural plantations with crops such as cabbage and zucchini. The dataset addresses agricultural tasks such as plant detection and counting, health assessment, and irrigation planning.

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


# Dataset structure
- **Plantations_Segmentation** - contains of original plantation images (folder **img**) and file with annotations (.xml)
- **Object_Segmentation** - includes object segmentation masks for the original images
- **Class_Segmentation** - includes class segmentation masks for the original images

# Types of segmentation
The dataset includes two types of segmentation:
- **Class Segmentation** - objects corresponding to one class are identified
- **Object Segmentation** - all objects are identified separately

# Data Format

Each image from `img` folder is accompanied by an XML-annotation in the `annotations.xml` file indicating the coordinates of the polygons. For each point, the x and y coordinates are provided.

# Example of XML file structure
.png?generation=1686129907313187&alt=media)

# Plantation segmentation 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/agriculture-data-labeling?utm_source=kaggle&utm_medium=cpc&utm_campaign=plantations-segmentation)** to discuss your requirements, learn about the price and buy the dataset

## [**TrainingData**](https://trainingdata.pro/datasets/agriculture-data-labeling?utm_source=kaggle&utm_medium=cpc&utm_campaign=plantations-segmentation) 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: agricultural tasks dataset, image segmentation dataset, plantations images dataset, plantations segmentation dataset, land cover dataset, agricultural products dataset, semantic segmentation dataset, agriculture dataset, agricultural data, object detection dataset, plants segmentation dataset, plant detection, plant recognition*

原始信息汇总

数据集概述

数据集名称

• Plantations Segmentation Object Detection dataset

数据集内容

• 包含农业种植园的航空摄影图像，如卷心菜和西葫芦。
• 用于农业任务，如植物检测和计数、健康评估和灌溉规划。

数据集结构

• Plantations_Segmentation：包含原始种植园图像（文件夹 img）和带有注释的文件（.xml）。
• Object_Segmentation：包含原始图像的对象分割掩码。
• Class_Segmentation：包含原始图像的类别分割掩码。

数据集特征

• image_id：数据类型为 int32。
• image：数据类型为图像。
• class_segmentation：数据类型为图像。
• object_segmentation：数据类型为图像。
• shapes：数据类型为字符串。

分割

• train：包含13个示例，总字节数为48297698。

数据格式

• 每张图像都伴随有一个annotations.xml文件，其中包含多边形的坐标。

许可证

• cc-by-nd-4.0

任务类别

• 图像分割
• 图像分类
• 图像特征提取
• 图像到图像转换

语言

• 英语

标签

• 生物学
• 代码
• 不适合所有观众

数据集大小

• 下载大小：48362120字节
• 数据集大小：48297698字节