Shells or Pebbles Classification
This dataset offers 4,284 images divided into two classes: shells and pebbles. It is designed to train simple binary classification models based on natural images.
Description
The dataset Shells or Pebbles Classification is a set of 4,284 images divided into two classes: “Shell” and “Pebble”. It can be used to train computer vision models that can distinguish between these two types of natural objects, for educational projects, mobile applications, or binary classification demonstrations.
What is this dataset for?
- Training binary image classification models on natural data
- Develop a mobile application for recognizing objects on the beach
- Experiment with data augmentation, fine-tuning or few-shot learning
Can it be enriched or improved?
Yes. It is possible to add new images from other beaches, to manually label subcategories, or to cross this game with other natural objects to expand the possibilities. Improvement can also be achieved through image normalization or class balancing if necessary.
🔎 In summary
🧠 Recommended for
- Beginners in computer vision
- Mobile projects
- Fun AI workshops
🔧 Compatible tools
- TensorFlow
- Keras
- PyTorch
- Google Teachable Machine
💡 Tip
Use this dataset to test AutoML algorithms or visual AI no-code tools.
Frequently Asked Questions
Is this dataset suitable for children or for educational projects?
Yes, its content is visual, easy to understand and can be used in educational activities or introductory projects.
Can we increase the dataset with photos taken by ourselves?
Yes, you can enrich the corpus with your own photos, as long as you maintain a consistent style and resolution.
Is it adapted to a real-time image recognition model?
Yes, thanks to its small size and simple classes, it is perfect for lightweight embedded applications.
