smeschke

import cv2
import numpy as np
cap = cv2.VideoCapture('/home/sm/Desktop/VIRB0034.MP4')
fourcc = cv2.VideoWriter_fourcc(*'XVID')
out = cv2.VideoWriter('/home/sm/Desktop/balance.avi',fourcc, 30.0, (1920,1080))

color = (123,123,12)
def dst(f,c):
    distance = math.sqrt((f[0]-c[0])**2+(f[1]-c[1])**2)
    return distance

smeschke

#import necessary libraries
import cv2
import numpy as np

#capture video from the webcam
cap = cv2.VideoCapture(0)

#load the face finder
face_cascade = cv2.CascadeClassifier('/home/sm/Desktop/haarcascade_frontalface_default.xml')

smeschke

import cv2
import numpy as np
cap = cv2.VideoCapture(0)

# params for ShiTomasi corner detection
feature_params = dict( maxCorners = 50,
                       qualityLevel = 0.2,
                       minDistance = 7,
                       blockSize = 7 )

smeschke

from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import csv

#get list of temple name, location, dedication data, lat, and lon
path = '/home/sm/Desktop/temple_data.csv'
temples = [] #create a list to store the temple data from the spread sheet
with open(path, 'rb') as csvfile: #open the csv file
    temple_data = csv.reader(csvfile, delimiter=',', quotechar='"') #load temple data
    for temple in temple_data: #iterate through data to change year to int

smeschke

import cv2
import numpy as np

cap = cv2.VideoCapture(0)

kernel = np.ones((8,8),np.uint8)

while(1):

    # Take each frame

smeschke

import pygame
import random
import math

background_colour = (255,255,255)
(width, height) = (500, 500)

class Particle():
    def __init__(self, (x, y), size):
        self.x = x

smeschke

import pygame
import random
import math

background_colour = (255,255,255)
(width, height) = (400, 400)
drag = 0.999
elasticity = 0.75
gravity = (math.pi, 0.002)
import cv2

smeschke

import cv2
import numpy as np

#path to video paths
#source_path = '/home/sm/Desktop/VIRB0054.MP4'
source_path = 0
save_path = '/home/sm/Desktop/mandt_effect.avi'
image_path = '/home/sm/Desktop/map.png'
frame_rate, resolution = 25.0, (640,480)
text = cv2.imread(image_path)

smeschke

article_path = 'furniture/furniture_invintory' #path to the article
article = open(article_path, 'r') #open the article
products = []
while True:
    line = article.readline()
    if line[:-1] == 'end_furniture': break
    if line[:-1] == 'start_product':
        product_key = article.readline()
        product_name = article.readline()
        banner_line_one = article.readline()

smeschke

import numpy as np
import cv2
import math
#capture webcam video
cap = cv2.VideoCapture(0)
width, height = 1920,1080
cap.set(3,width)
cap.set(4,height)

#create a method that can seperate the foreground from the background