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README.md

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-license: cc-by-nc-nd-4.0
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+---
+license: cc-by-nc-nd-4.0
+task_categories:
+- object-detection
+- video-classification
+tags:
+- video
+- sign language
+- recognition
+- gesture
+- machine learning
+- computer vision
+- deep learning
+size_categories:
+- 1K<n<10K
+---
+# Gesture Recognition Dataset for computer vision tasks
+Dataset consists of **10,000+** videos featuring individuals demonstrating **5** distinct hand gestures: "one," "four," "small," "fist," and "me." It helps researchers study **gesture recognition**, especially for **sign language** and **gesture-controlled devices**. The dataset features a wide array of individuals demonstrating gestures, which allows for the analysis of differences in hand shapes, sizes, and movements among various people.
+
+By showcasing different individuals performing the gestures, the videos enable robust training of **machine learning** models and **deep learning techniques**.  - **[Get the data](https://unidata.pro/datasets/gesture-recognition/?utm_source=huggingface&utm_medium=cpc&utm_campaign=gesture-recognition)**
+
+# Example of the data
+![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F22059654%2F3f0ae02b231b9ca3243f76d43ec97ccf%2FFrame%20180.png?generation=1733948170826295&alt=media)
+Each video is recorded under optimal lighting conditions and at a high resolution, ensuring clear visibility of the hand movements. Researchers can utilize this dataset to enhance their understanding of gesture recognition applications and improve the performance of recognition methods
+# 💵 Buy the Dataset: This is a limited preview of the data. To access the full dataset, please contact us at [https://unidata.pro](https://unidata.pro/datasets/gesture-recognition/?utm_source=huggingface&utm_medium=cpc&utm_campaign=gesture-recognition) to discuss your requirements and pricing options.
+This dataset is particularly valuable for developing and testing recognition algorithms and classification methods in hand-gesture recognition (HGR) systems. Developers and researchers can advance their capabilities in pattern recognition and explore new recognition systems that can be applied in various fields, including human-computer interaction and virtual reality.
+
+# 🌐 [UniData](https://unidata.pro/datasets/gesture-recognition/?utm_source=huggingface&utm_medium=cpc&utm_campaign=gesture-recognition) provides high-quality datasets, content moderation, data collection and annotation for your AI/ML projects