---
language:
- en
license: cc-by-nc-nd-4.0
task_categories:
- image-to-image
- image-classification
- object-detection
tags:
- code
dataset_info:
  features:
  - name: id
    dtype: int32
  - name: image
    dtype: image
  - name: mask
    dtype: image
  - name: bboxes
    dtype: string
  splits:
  - name: train
    num_bytes: 5428811
    num_examples: 27
  download_size: 5391503
  dataset_size: 5428811
---

# Pigs Detection Dataset

The dataset is a collection of images along with corresponding bounding box annotations that are specifically curated for **detecting pigs' heads** in images. The dataset covers different *pig breeds, sizes, and orientations*, providing a comprehensive representation of pig appearances.

The pig detection dataset provides a valuable resource for researchers working on pig detection tasks. It offers a diverse collection of annotated images, allowing for comprehensive algorithm development, evaluation, and benchmarking, ultimately aiding in the development of accurate and robust models.

![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F4a3e82f15a9ba03a671ed899536d6df1%2Fsssss.png?generation=1691942997350634&alt=media)

# Get the Dataset

### This is just an example of the data

Contact us via **[sales@trainingdata.pro](mailto:sales@trainingdata.pro)** or leave a request on **[https://trainingdata.pro/data-market](https://trainingdata.pro/data-market?utm_source=huggingface)** to discuss your requirements, learn about the price and buy the dataset 

# Dataset structure
- **images** - contains of original images of pigs
- **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 pigs detection. For each point, the x and y coordinates are provided.

# Example of XML file structure
![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F43366efcae5881191e65f70e92ba706a%2Fcarbon.png?generation=1691942804196967&alt=media)

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

## **[TrainingData](https://trainingdata.pro/data-market?utm_source=huggingface)** 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**