shravankumar147

shravankumar147

# USAGE
# python face_detection.py --image face1.jpg

# import the necessary packages
# from imutils import face_utils
# import numpy as np
import argparse
import imutils
import dlib
import cv2

shravankumar147

set nocompatible              " be iMproved, required
filetype off                  " required
set exrc

set rtp+=~/.vim/bundle/Vundle.vim
call vundle#begin()

" ==== PLUGINS ====
Plugin 'VundleVim/Vundle.vim'
Plugin 'vim-scripts/L9'

shravankumar147

  from datetime import datetime                                                                                                                     
                                                                                                                                                    
                                                                                                                                                    
  def post_name(name):                                                                                                                              
      """                                                                                                                                           
      This will generate your github post name.                                                                                                     
      example:                                                                                                                    

shravankumar147

# Implementation of a simple MLP network with one hidden layer. Tested on the iris data set.
# Requires: numpy, sklearn>=0.18.1, tensorflow>=1.0

# NOTE: In order to make the code simple, we rewrite x * W_1 + b_1 = x' * W_1'
# where x' = [x | 1] and W_1' is the matrix W_1 appended with a new row with elements b_1's.
# Similarly, for h * W_2 + b_2
import tensorflow as tf
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split

shravankumar147

iris["Species"] = iris["Species"].map({"Iris-setosa":0,"Iris-virginica":1,"Iris-versicolor":2})

shravankumar147

shravankumar147

import pafy
from pydub import AudioSegment
import argparse

# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-u", "--url", required=True, help="download link")
args = vars(ap.parse_args())

shravankumar147

import os

cmd = "wget -c --progress=bar https://docs.microsoft.com/en-us/azure/cognitive-services/face/images/landmarks.1.jpg"
os.system(cmd)

shravankumar147

# USAGE
# python build_face_dataset.py --cascade haarcascade_frontalface_default.xml --output dataset/adrian

# import the necessary packages
from imutils.video import VideoStream
import argparse
import imutils
import time
import cv2
import os