Keras
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ASLNow!

ASLNow! is a web app designed to make learning ASL fingerspelling easy and fun! You can try it live at asl-now.vercel.app.

Demo: https://www.youtube.com/watch?v=Wi5tAxVasq8

Model

This model, trained on the isolated fingerspelling dataset is licensed under the MIT License. It will be updated frequently as more data is collected.

Format

Overview of Model

Input

21 hand landmarks, each composed of x, y and z coordinates. The x and y coordinates are normalized to [0.0, 1.0] by the image width and height, respectively. The z coordinate represents the landmark depth, with the depth at the wrist being the origin. The smaller the value, the closer the landmark is to the camera. The magnitude of z uses roughly the same scale as x.

Hand Landmarks From: https://developers.google.com/mediapipe/solutions/vision/hand_landmarker

Example:

[
  # Landmark 1
  [x, y, z],
  # Landmark 2
  [x, y, z],
  ...
  # Landmark 20
  [x, y, z]
  # Landmark 21
  [x, y, z]
]

Output

The probability of each class, where classes are defined as such:

{
    "A": 0,
    "B": 1,
    "C": 2,
    "D": 3,
    "E": 4,
    "F": 5,
    "G": 6,
    "H": 7,
    "I": 8,
    "J": 9,
    "K": 10,
    "L": 11,
    "M": 12,
    "N": 13,
    "O": 14,
    "P": 15,
    "Q": 16,
    "R": 17,
    "S": 18,
    "T": 19,
    "U": 20,
    "V": 21,
    "W": 22,
    "X": 23,
    "Y": 24,
    "Z": 25
}
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Inference API
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Dataset used to train sid220/asl-now-fingerspelling