license: mit
datasets:
- sid220/asl-now-fingerspelling
language:
- en
metrics:
- accuracy
library_name: keras
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
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.
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
}