Bugzz lightyears: To Semantic Segmentation and Bug-yond!

Dataset Title: Bugzz lightyears: To Semantic Segmentation and Bug-yond! Description: This dataset comprises a collection of real and robotic toy bugs designed for a small-scale semantic segmentation project. Each bug has been captured six times from various angles, ensuring comprehensive coverage of their features and details. The dataset serves as a valuable resource for exploring semantic segmentation techniques and evaluating machine learning models. Dataset Details: Images: Each bug is represented by six images taken from different perspectives, facilitating robust segmentation and analysis. Segmentation: The dataset has been meticulously segmented using Label Studio in conjunction with the SAM (Segment Anything Model), enabling precise delineation of each bug from the background. Diversity: The collection includes a variety of bugs, both real and robotic, providing a unique blend for training and testing segmentation models. Usage: This toy dataset is ideal for researchers and developers interested in: Experimenting with semantic segmentation algorithms. Developing and refining computer vision models for object detection and segmentation. Educational purposes in machine learning and computer vision courses. License: This dataset is made available under [specify license type, e.g., CC BY 4.0], allowing for both academic and commercial use, with proper attribution to the creator.