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.本数据集包含26000张图像与300段视频，涵盖对应英文字母（A-Z）的美国手语（American Sign Language, ASL）手势，以及“你好”“谢谢”“抱歉”“是”“否”五类常用手势。该数据集分为26个文件夹，每个文件夹以对应字母命名，内部包含多组图像样本，以确保手部姿态、光照条件以及个体手部差异带来的样本多样性。与之类似，该动态数据集包含31个文件夹，每个手势对应10段样本视频，每个文件夹内还存储有视频拆解出的独立帧，格式为.jpg（JPEG）。该数据集收录的手势覆盖范围广泛，适用于手语识别、计算机视觉以及基于深度学习的分类任务等机器学习应用场景。当使用基于长短期记忆网络（Long Short-Term Memory, LSTM）的模型进行评估时，该数据集在手语识别任务中取得了较高的准确率，证明其在序列手势学习场景中具备优异的应用效果。