---
language:
- en
license: cc-by-nc-nd-4.0
task_categories:
- image-to-image
- image-classification
- object-detection
tags:
- biology
- farm animal
- Object Detection
- cows
- animal recognition
dataset_info:
  features:
  - name: id
    dtype: int32
  - name: image
    dtype: image
  - name: mask
    dtype: image
  - name: bboxes
    dtype: string
  splits:
  - name: train
    num_bytes: 184108240
    num_examples: 51
  download_size: 183666433
  dataset_size: 184108240
size_categories:
- 1K<n<10K
---

# Cows Object Detection Dataset

The dataset is a collection of images along with corresponding bounding box annotations that are specifically curated for **detecting cows** in images. The dataset covers different *cows breeds, sizes, and orientations*, providing a comprehensive representation of cows appearances and positions. Additionally, the visibility of each cow is presented in the .xml file.

# 💴 For Commercial Usage: To discuss your requirements, learn about the price and buy the dataset, leave a request on **[our website](https://unidata.pro/datasets/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=cows-detection-dataset)** to buy the dataset

The cow detection dataset 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%2Fc1495731b6dff54b97ba132fc8d36fd9%2FMacBook%20Air%20-%201.png?generation=1692031830924617&alt=media)

# Dataset structure
- **images** - contains of original images of cows
- **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 cows detection. For each point, the x and y coordinates are provided. Visibility of the cow is also provided by the label **is_visible** (true, false).

# Example of XML file structure
![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F7a0f0bd6a019e945074361896d27ee90%2Fcarbon%20(1).png?generation=1692032268744062&alt=media)

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

# 💴 Buy the Dataset: This is just an example of the data. Leave a request on **[our website](https://unidata.pro/datasets/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=cows-detection-dataset)** to discuss your requirements, learn about the price and buy the dataset
Leave a request on [our website](https://unidata.pro/datasets/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=ocr-receipts-text-detection) to discuss your requirements, learn about the price and buy the dataset.

## [Our Team](https://unidata.pro/datasets/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=cows-detection-dataset) provides high-quality data annotation tailored to your needs


*keywords: farm animal, animal recognition, farm animal detection, image-based recognition, farmers, “on-farm” data, cows detection, cow images dataset, object detection, deep learning, computer vision, animal contacts, images dataset, agriculture, multiple animal pose estimation, cattle detection, identification, posture recognition, cattle images, individual beef cattle, cattle ranch, dairy cattle, farming, bounding boxes*