SignAlphaSet

This dataset comprises 26,000 images & 300 videos representing American Sign Language (ASL) hand gestures corresponding to the English alphabet (A-Z) & 5 gestures such as "Hello", "Thank You", "Sorry", "Yes" & "No". The dataset is organized into 26 folders, each labeled with a corresponding letter, containing multiple image samples to ensure variability in hand positioning, lighting, and individual hand differences. Similarly, the dynamic dataset contains 31 folders with 10 sample videos of each gesture, each folder also contains separate frames of the video in .jpg format. The images capture diverse hand gestures, making the dataset suitable for machine learning applications such as sign language recognition, computer vision, and deep learning-based classification tasks. When evaluated using an LSTM-based model, the dataset achieved high accuracy in sign recognition, demonstrating its effectiveness in sequential gesture learning.