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This tutorial can be used to detect the distance from the web-cam to the human face using OpenCV and a TensorFlow trained model for face detection.

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Estimate distance from the camera for detected faces.

Tensorflow Object Detection is used to detect and track human faces in live feed.

Objective

The main objective to create this project is to provide an alert to those who use electronic devices such as smartphones and laptops so close to their eyes.Usage of such devices so close to the eyes affects the eyesight. This module monitors the distance and provides an alert if the eye-device-contact is closer.

Note

Adjust the focal length in utils/detector_utils.py, for better results.

Installation

Requirements:

1.Opencv

2.Numpy

3.imutils

4.Tensorflow

5.Python 3.6

After installing the required packages, run main.py.

Acknowledgments

Pyimagesearch - To find distance from a camera to object/marker using Python and OpenCV.

Edge Electronics - Training Tensorflow Object Detection.

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This tutorial can be used to detect the distance from the web-cam to the human face using OpenCV and a TensorFlow trained model for face detection.

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