Variable counts of images across user-defined categories are generated by this library to create custom computer vision datasets. It automates the scraping and organization of web images into labeled directory structures for training deep learning models.
Use Cases
- Build a custom image classification dataset by using search queries to define class labels.
- Collect a large volume of visual data for pre-training computer vision models.
- Gather specific image sets for fine-tuning models on niche or rare object categories.
Strengths
- Automates the collection of images from web sources based on user-defined queries.
- Organizes downloaded files into a directory structure suitable for image classification tasks.
- Facilitates the creation of custom datasets for deep learning model training.