Sign Detection 4b69a
Sign Language Detection - An Image Classification Project
The data set is a collection of images of alphabets from the American Sign Language, separated in 29 folders which represent the various classes.
The training data set contains 87,000 images which are 200x200 pixels. There are 29 classes, of which 26 are for the letters A-Z and 3 classes for SPACE, DELETE and NOTHING. These 3 classes are very helpful in real-time applications, and classification. The test data set contains a mere 28 images, to encourage the use of real-world test images.
- How to use Kaggle Datasets in Google Colab - https://medium.com/analytics-vidhya/how-to-fetch-kaggle-datasets-into-google-colab-ea682569851a
- Reference ipynb notebook - https://colab.research.google.com/drive/1c-U-fCmpcI0TAIds4_9IatzxMkcYnY8d#scrollTo=xfPP3dVf3KUg
Importing important libraries and project creation.
import os import torch import torchvision import tarfile import torch.nn as nn import numpy as np import torch.nn.functional as F from torchvision.datasets.utils import download_url from torchvision.datasets import ImageFolder from torch.utils.data import DataLoader import torchvision.transforms as tt from torch.utils.data import random_split from torchvision.utils import make_grid import matplotlib import matplotlib.pyplot as plt %matplotlib inline matplotlib.rcParams['figure.facecolor'] = '#ffffff'