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Neural-Hacker/hand_gesture_yolo

sourceHugging Facecc-by-nc-sa-4.0updated 3mo agoView on Hugging Face

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Model Card

Hand Gesture YOLOv8 (ONNX INT8)

Overview

This repository contains a YOLOv8 nano model trained for real-time hand gesture detection and optimized for edge and mobile devices.

The model is exported to ONNX format and quantized to INT8 for efficient on-device inference.

Model Details

—Architecture: YOLOv8n (Nano)
—Task: Hand gesture detection
—Format: ONNX
—Precision: INT8 (W8A8)
—Input size: 640 × 640
—Classes:
—hand-gestures
—left
—right
—stop
—mvefrd

Included Assets

—hand_gesture_yolo_onnx_w8a8.zip
—model.onnx
—tool_versions.yaml
—data.yaml

Each ZIP follows the Qualcomm AI Hub Community contribution guidelines.

Training Summary

—Dataset size: 330 images
—Training platform: Kaggle (NVIDIA Tesla T4)
—Framework: Ultralytics YOLOv8
—Quantization: ONNX INT8

Intended Use

—Edge AI applications
—Gesture-based interfaces
—Touchless controls
—Academic and research purposes

Limitations

—The model is trained on a small dataset and may not generalize to all lighting conditions or camera angles.
—Performance may vary depending on device and runtime.

License

This model is released under the CC BY-NC 4.0 license.

Disclaimer

Commercial use is not permitted.