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Python Script for 'tracking' number of hours you spend before the Computer. Built using dlib's state-of-the-art face recognition built with deep learning

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Time Sheet

Python Script for 'tracking' number of hours you spend before the Computer. You can also download the time sheet at the end in multiple formats!

Contents

This is a command line python program to track the number of work hours that you spend before the System/ Computer with webcam enabled using face recognition. You can also invoke this script from another python file.

This is a small and ready-to-run program. There are two dependencies that will get installed when you install this repo. 1. open-cv 2. facerecognition

Built using dlib's state-of-the-art face recognition built with deep learning.

This program is compatible with both the versions of python - 2.x and 3.x (recommended). It is a download-and-run program with no changes to the file. You will just have to specify parameters through the command line.

You can use one of the below methods to download and use this repository.

Using pip

$ pip install time_sheet

Manually using CLI

$ git clone https://github.com/NoSkillGuy/time_sheet.git
$ cd time_sheet && sudo python setup.py install

Manually using UI

Go to the repo on github ==> Click on 'Clone or Download' ==> Click on 'Download ZIP' and save it on your local disk.

If installed via pip or using CLI, use the following command:

$ timesheet [Arguments...]

If downloaded via the UI, unzip the file downloaded, go to the 'time_sheet' directory and use one of the below commands:

$ python3 time_sheet.py [Arguments...]
OR
$ python time_sheet.py [Arguments...]

If you would want to use this library from another python file, you could use it as shown below:

from time_sheet import time_sheet

response = time_sheet.timesheet()
response.capture({<Arguments...>})
Argument Short hand Description
config_file cf

You can pass the arguments inside a config file. This is an alternative to passing arguments on the command line directly.

Please refer to the config file format below

  • If 'config_file' argument is present, the program will use the config file and command line arguments will be discarded
  • Config file can only be in JSON format
  • Please refrain from passing invalid arguments from config file. Refer to the below arguments list
known_images_path kip

Specify the known images path. This path should contain images only from these whitelisted formats (jpg, png, gif, bmp). The name of the person is syntactically drawn from the filename without the extension. Default known_images_path - 'images/' Example:

  • If the file name is Steve Jobs.png, then the name derived is Steve Jobs
  • If the file name is Elon Musk.png, then the name derived is Elon Musk
download_path dp This is the place where all your time_sheet downloads will be located. The path will be auto created if the given download_path doesn't exist. Default download path - downloads/
download_format df

Denotes the format/extension of the file that will be downnloaded

Possible values: json, CSV, inline Default Value: inline

If the -df argument is mentioned either json or CSV and -dp is not metioned downloads/ path is auto created in the current working directory

help h show the help message regarding the usage of the above arguments

You can either pass the arguments directly from the command as in the examples below or you can pass it through a config file. Below is a sample of how a config file looks.

You can pass more than one record through a config file. The below sample consist of two set of records. The code will iterate through each of the record and download images based on arguments passed.

{
    "Arguments":
    {
        "known_images_path": "/users/NoSkillGuy/mysites/time_sheet/images",
        "download_path": "/users/NoSkillGuy/mysites/time_sheet/downloads",
        "download_format": "json"
    }
}
  • If you are calling this library from another python file, below is the sample code
from time_sheet import time_sheet   #importing the library

response = time_sheet.timesheet()   #class instantiation

arguments = {
    "known_images_path": "/users/NoSkillGuy/mysites/time_sheet/images",
    "download_path":"/users/NoSkillGuy/mysites/timesheet/downloads",
    "download_format":"json"
}   #creating list of arguments

response.capture(arguments)   #passing the arguments to the function
  • If you are passing arguments from a config file, simply pass the config_file argument with name of your JSON file
$ timesheet -cf example.json
  • Simple example of using arguments
$ timesheet --known_images_path /users/NoSkillGuy/mysites/time_sheet/images --download_path /users/NoSkillGuy/mysites/time_sheet/downloads --download_format json
  • To use the short hand command
$ timesheet --kip /users/NoSkillGuy/mysites/time_sheet/images --dp /users/NoSkillGuy/mysites/time_sheet/downloads --df json

## timesheet: command not found

While using the above commands, if you get Error: -bash: timesheet: command not found then you have to set the correct path variable.

To get the details of the repo, run the following command:

$ pip show -f time_sheet

you will get the result like this:

Location: /Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages
Files:
  ../../../bin/timesheet

together they make: /Library/Frameworks/Python.framework/Versions/2.7/bin which you need add it to the path:

$ export PATH="/Library/Frameworks/Python.framework/Versions/2.7/bin"

## [Errno 13] Permission denied creating directory 'downloads'

When you run the command, it downloads the images in the current directory (the directory from where you are running the command). If you get permission denied error for creating the downloads directory, then move to a directory in which you have the write permission and then run the command again.

## Permission denied while installing the library

On MAC and Linux, when you get permission denied when installing the library using pip, try doing a user install.

$ pip install time_sheet --user

You can also run pip install as a superuser with sudo pip install time_sheet but it is not generally a good idea because it can cause issues with your system-level packages.

Anyone is welcomed to contribute to this script. If you would like to make a change, open a pull request. For issues and discussion visit the Issue Tracker.

If this project gets 10 Stars, then i will work on the following

  1. Implementing a command line utility for taking a snapshot so that one can easily add his/her picture before trying out timesheet
  2. Documentation
  3. Examples
  4. Tests

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Python Script for 'tracking' number of hours you spend before the Computer. Built using dlib's state-of-the-art face recognition built with deep learning

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