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Python library for temporal contrast American Sign Language classification.

Project description

TCASL

TCASL is a lightweight, pure Python inference engine for predicting American Sign Language (ASL) gestures using Temporal Contrast, simulating a Dynamic Vision Sensor (DVS).

Features

  • Zero-Bloat Inference: A strictly defined PyTorch wrapper built specifically for rapid prediction.
  • Temporal Contrast Processing: Built-in methods to convert standard webcam video into DVS-style event frames.
  • Auto-Formatting: Automatically center-crops and down-scales raw video arrays to the 128x128 resolution required by the network.

Installation

You can install the latest release of TCASL from PyPI using pip:

pip install TCASL

Usage in Python

Examples of how the library can be used can be found in examples/. You should not edit this code unless you read the documentation thoroughly, which is located at src/tcasl/core.py.

TCASL Project

You can find information about TCASL on the GitHub page.

Project details


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