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---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': test
'1': train
splits:
- name: train
num_bytes: 441562705.801
num_examples: 21159
- name: test
num_bytes: 80207072.542
num_examples: 3841
download_size: 572690049
dataset_size: 521769778.343
---
# Dataset Documentation
## Overview
This dataset is designed to support machine learning and data analysis tasks. It consists of two compressed archives: `train.tar` and `test.tar`. These archives contain data for training and testing purposes, respectively. The dataset is structured to facilitate easy integration into machine learning pipelines and other data-driven workflows.
---
## Dataset Contents
### 1. `train.tar`
The `train.tar` archive contains the training data required to build and train machine learning models. This data is typically used to teach models to recognize patterns, make predictions, or classify data points.
- **Purpose**: Training machine learning models.
- **Contents**: The archive includes multiple files (or directories) that represent the training dataset. Each file may correspond to a specific data sample, feature set, or label.
### 2. `test.tar`
The `test.tar` archive contains the testing data used to evaluate the performance of trained models. This data is separate from the training set to ensure unbiased evaluation.
- **Purpose**: Testing and validating machine learning models.
- **Contents**: Similar to the training archive, this archive includes files (or directories) that represent the testing dataset.
---
## File Structure
After extracting the `.tar` files, the dataset will have the following structure:
```
dataset/
├── train/
│ ├── file1.ext
│ ├── file2.ext
│ └── ...
└── test/
├── file1.ext
├── file2.ext
└── ...
```
- **`train/`**: Contains training data files.
- **`test/`**: Contains testing data files.
---
## How to Use the Dataset
### Step 1: Extract the Archives
To access the dataset, you need to extract the contents of the `.tar` files. Use the following commands:
```bash
tar -xvf train.tar
tar -xvf test.tar
```
This will create two directories: `train/` and `test/`.
### Step 2: Load the Data
Once extracted, you can load the data into your preferred programming environment. For example, in Python:
```python
import os
# Define paths
train_path = "train/"
test_path = "test/"
# List files in the training directory
train_files = os.listdir(train_path)
print("Training Files:", train_files)
# List files in the testing directory
test_files = os.listdir(test_path)
print("Testing Files:", test_files)
```
### Step 3: Integrate with Your Workflow
You can now use the data for training and testing machine learning models. Ensure that you preprocess the data as needed (e.g., normalization, feature extraction, etc.).
---
## Dataset Characteristics
- **Size**: The size of the dataset depends on the contents of the `train.tar` and `test.tar` archives.
- **Format**: The files within the archives may be in formats such as `.csv`, `.txt`, `.json`, or others, depending on the dataset's design.
- **Labels**: If the dataset is labeled, the labels will typically be included in the training and testing files or in a separate metadata file.
---
## Best Practices
1. **Data Splitting**: Ensure that the training and testing data are not mixed to maintain the integrity of model evaluation.
2. **Preprocessing**: Apply appropriate preprocessing steps to the data, such as cleaning, normalization, or augmentation.
3. **Version Control**: If you modify the dataset, maintain version control to track changes and ensure reproducibility.
---
## Licensing and Usage
Please review the licensing terms associated with this dataset before use. Ensure compliance with any restrictions or requirements.
---
## Citation
If you use this dataset in your research or project, please cite it as follows:
```
cat-dog. Provided by programersalar.
```
---
## Frequently Asked Questions (FAQ)
### 1. How do I extract the `.tar` files?
Use the `tar` command in a terminal or a file extraction tool that supports `.tar` archives.
### 2. What format are the data files in?
The format of the data files depends on the specific dataset. Common formats include `.csv`, `.txt`, `.json`, and others.
### 3. Can I use this dataset for commercial purposes?
Refer to the licensing section to determine whether commercial use is permitted.
---
## Support
If you encounter any issues or have questions about the dataset, please contact the dataset provider or refer to the official documentation.
---
## Acknowledgments
We would like to thank the contributors and maintainers of this dataset for their efforts in creating and sharing this resource.
---
## Change Log
- **Version 1.0**: Initial release of the dataset.
---
Thank you for using this dataset! We hope it proves valuable for your projects and research. |