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About the developer

loicmarie
143 Stars 102 Forks MIT License 19 Commits 23 Opened issues

Description

Simple sign language alphabet recognizer using Python, openCV and tensorflow for training Inception model (CNN classifier).

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SLR Alphabet Recognizer

This project is a sign language alphabet recognizer using Python, openCV and tensorflow for training InceptionV3 model, a convolutional neural network model for classification.

The framework used for the CNN implementation can be found here:

Simple transfer learning with an Inception V3 architecture model by xuetsing

The project contains the dataset (1Go). If you are only interested in code, you better copy/paste the few files than cloning the entire project.

You can find the demo here

Demo

Requirements

This project uses python 3.5 and the PIP following packages: * opencv * tensorflow * matplotlib * numpy

See requirements.txt and Dockerfile for versions and required APT packages

Using Docker

docker build -t hands-classifier .
docker run -it hands-classifier bash

Install using PIP

pip3 install -r requirements.txt

Training

To train the model, use the following command (see framework github link for more command options):

python3 train.py \
  --bottleneck_dir=logs/bottlenecks \
  --how_many_training_steps=2000 \
  --model_dir=inception \
  --summaries_dir=logs/training_summaries/basic \
  --output_graph=logs/trained_graph.pb \
  --output_labels=logs/trained_labels.txt \
  --image_dir=./dataset
If you're using the provided dataset, it may take up to three hours.

Classifying

To test classification, use the following command:

python3 classify.py path/to/image.jpg

Using webcam (demo)

To use webcam, use the following command:

python3 classify_webcam.py
Your hand must be inside the rectangle. Keep position to write word, see demo for deletions.

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