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In this project has been implemented an algorithm to identify the italian sign language (LIS - Lingua Italiana dei Segni) through Opencv, Mediapipe Hand Detection and a K-nn classifier.

License: GNU General Public License v3.0

Python 100.00%
mediapipe opencv opencv-python sklearn python python3 hands hands-detection machine-learning hand-detection

lis-detection's Introduction

LIS-Detection

In this project has been implemented an algorithm to detect the italian sign language (LIS - Lingua Italiana dei Segni) through Opencv, Mediapipe Hand Detection and a K-nn classifier.

๐Ÿ”จ Technologies

  • Python 3.8.13
  • Mediapipe 0.9.2.1
  • Opencv 4.6.0.66
  • Sklearn 1.1.2
  • Pickle 4.0

๐Ÿ“š Install

pip install - pip/requirements.txt

๐Ÿ“Š Dataset

Dataset was acquired using a previously created tool: acqTool

  • LIS alphabet letters were recorded (26 classes).
  • 500 vectors for each classes,
  • Vectors was normalized using the MinMaxScaler [0,1],
  • Each vector is composed by 42 features:
$$V_{i} = (x_{1}, y_{1}, ... , x_{n}, y_{n})$$

where:

  • x_{n} and x_{n} are the position in pixels,
  • (x_{n} , x_{n} ) is nth landmark on 2D image. 8

Note: only right hand was used during the acquisition. Download Here

๐Ÿšธ Classifier

The classifier chosen is K-NN ( sklearn ).

Confusion Matrix:

confusion_matrix_knn

๐Ÿš€ Launch

python hand_detection_main.py -c {classifier.pkl}

๐Ÿ“„ License

This project is released under the GNU General Public License v3.0

lis-detection's People

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