fritzfrancisco

#!/usr/bin/env python

from pathlib import Path
import os
import cv2
import argparse

# Supported OpenCV Backend Ubuntu 24.04.1 LTS
os.environ["QT_QPA_PLATFORM"] = "xcb"
os.environ["OPENCV_UI_BACKEND"] = "xcb"

fritzfrancisco

#!/usr/bin/env python3

def create_response():
  '''Create polited and humble response to reviewer suggestions'''
  a = ['y', 'u', 'e', 'n', 'f', ' ', '?', 'a', 'p', ' ', 'r', 's', 'd', 'u', 'o', 't', 'i', ' ', 'c', 'u', 'g', 'k', 'i']
  b = [4, 17, 2, 12, 8, 3, 21, 0, 18, 7, 1, 15, 20, 6, 5, 16, 19, 14, 10, 9, 13, 11, 12]
  out = ''.join([x for _,x in sorted(zip(b,a))])
  return out

fritzfrancisco

#!/usr/bin/env python3

import numpy as np
import cv2 as cv
import os
import sys
import argparse

import matplotlib.pylab as plt

fritzfrancisco

#!/usr/bin/env python3

# input video file:
input_file = 'input_video.mp4'

# termination criteria
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)

# change this to your checkerboard dimensions:
width_number_of_squares = 14

fritzfrancisco

''' Python implementation of basic background subtraction and object detection from
video using the OpenCV and numpy packages.'''

import cv2
import numpy as np

# input video
cap = cv2.VideoCapture('video/file/directory/goes/here')

# initiating basic background subtraction, creating a background from history=n frames

fritzfrancisco

fritzfrancisco

#!/usr/bin/env python3

import numpy as np
import cv2
import sys, os
import argparse

ap = argparse.ArgumentParser(
    description='Input specific output pathway and framerate')
ap.add_argument("-i", "--input1",type=str, required=True,