Skip to main content

Face extraction system

Project description


Python implementation of face extraction using haar-cascade classifier for frontal faces.


The requirements.txt file contains following:

1. numpy
2. opencv-python
3. opencv-utils

`[sudo] pip install -r requirements.txt`
Download the project. Unzip this zip folder.


You can install this package in two ways:

  1. PIP installation
  2. ZIP extraction
# PIP Installation

Install latest version(1.0) from the [source](
`[sudo] pip install facedet`

Then type `python3` **outside** folders' location in terminal. And type these to get output.
`>>> import facedet`
`>>> from facedet import faceext`
`>>> faceext.extract()`

By default this package reads the images (`data2.jpg`) that was already given.
# ZIP Installation

After extracting zip from the repository. Type this command  **in** file location.
`[sudo] python3 <path/to/image>` or you can select the images from data folder.

This way you can check for different images.


  1. This application is applied to Low-resoluted images. Throws an exception if high-resolution given.
  2. Loops and Conditional statements are avoided and replaced with numpy arrays to reduce Time Complexity.


This project is licensed under the MIT license.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for facedet, version 2.0
Filename, size File type Python version Upload date Hashes
Filename, size facedet-2.0-py3-none-any.whl (6.5 kB) File type Wheel Python version py3 Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page