LIONS-TIGERS Dataset

Total Images: 400 (256×256 pixels)

Classes: Lion, Tiger

Test Sample: 40 images

Features

• High-Resolution Images: Ensuring clarity for precise classification tasks. Each image in this dataset is of high resolution (256×256 pixels), providing clear and detailed visual information. This high level of detail is crucial for training accurate and reliable classification models.

• Balanced Classes: Equally distributed images between lions and tigers to ensure robust model training. The dataset is carefully curated to maintain an equal number of images for both lions and tigers. This balance is essential for training models that do not have a bias towards one class over the other, leading to fair and accurate classification performance.

Acknowledgements

We extend our gratitude to all contributors who have provided invaluable feedback and support. Your insights and suggestions have been instrumental in enhancing the quality and utility of this dataset. We welcome continued feedback to further improve and refine our offerings.

Inspiration

LIONS-TIGERS classification dataset presents a challenging binary classification task, making it an exciting project for AI enthusiasts and professionals. The complexity of differentiating between two visually similar species—lions and tigers—provides an excellent opportunity to test and enhance machine learning models. Whether you are looking to improve image recognition systems, develop new classification algorithms, or explore the nuances of wildlife identification, this dataset offers a rich and engaging challenge. It is ideal for projects aimed at advancing the accuracy and sophistication of image recognition and classification techniques.