Homework Help is Here – Start Your Trial Now!
Engineering
Computer Science
can you please design a flowchart for this code?   import cv2 as cv import numpy as np from matplotlib import pyplot as plt def lanesDetection(img):       height = img.shape[0]     width = img.shape[1]     region_of_interest_vertices = [         (200, height), (width/2, height/1.37), (width-300, height)     ]     gray_img = cv.cvtColor(img, cv.COLOR_RGB2GRAY)     edge = cv.Canny(gray_img, 50, 100, apertureSize=3)     cropped_image = region_of_interest(         edge, np.array([region_of_interest_vertices], np.int32))     lines = cv.HoughLinesP(cropped_image, rho=2, theta=np.pi/180,                            threshold=50, lines=np.array([]), minLineLength=10, maxLineGap=30)     image_with_lines = draw_lines(img, lines)       return image_with_lines def region_of_interest(img, vertices):     mask = np.zeros_like(img)       match_mask_color = (255)     cv.fillPoly(mask, vertices, match_mask_color)     masked_image = cv.bitwise_and(img, mask)     return masked_image def draw_lines(img, lines):     img = np.copy(img)     blank_image = np.zeros((img.shape[0], img.shape[1], 3), np.uint8)     for line in lines:         for x1, y1, x2, y2 in line:             cv.line(blank_image, (x1, y1), (x2, y2), (0, 255, 0), 2)     img = cv.addWeighted(img, 0.8, blank_image, 1, 0.0)     return img def videoLanes():     cap = cv.VideoCapture('./img/Lane.mp4')     while(cap.isOpened()):         ret, frame = cap.read()         frame = lanesDetection(frame)         cv.imshow('Lanes Detection', frame)         if cv.waitKey(1) & 0xFF == ord('q'):             break     cap.release()     cv.destroyAllWindows() if __name__ == "__main__":     videoLanes()

can you please design a flowchart for this code?   import cv2 as cv import numpy as np from matplotlib import pyplot as plt def lanesDetection(img):       height = img.shape[0]     width = img.shape[1]     region_of_interest_vertices = [         (200, height), (width/2, height/1.37), (width-300, height)     ]     gray_img = cv.cvtColor(img, cv.COLOR_RGB2GRAY)     edge = cv.Canny(gray_img, 50, 100, apertureSize=3)     cropped_image = region_of_interest(         edge, np.array([region_of_interest_vertices], np.int32))     lines = cv.HoughLinesP(cropped_image, rho=2, theta=np.pi/180,                            threshold=50, lines=np.array([]), minLineLength=10, maxLineGap=30)     image_with_lines = draw_lines(img, lines)       return image_with_lines def region_of_interest(img, vertices):     mask = np.zeros_like(img)       match_mask_color = (255)     cv.fillPoly(mask, vertices, match_mask_color)     masked_image = cv.bitwise_and(img, mask)     return masked_image def draw_lines(img, lines):     img = np.copy(img)     blank_image = np.zeros((img.shape[0], img.shape[1], 3), np.uint8)     for line in lines:         for x1, y1, x2, y2 in line:             cv.line(blank_image, (x1, y1), (x2, y2), (0, 255, 0), 2)     img = cv.addWeighted(img, 0.8, blank_image, 1, 0.0)     return img def videoLanes():     cap = cv.VideoCapture('./img/Lane.mp4')     while(cap.isOpened()):         ret, frame = cap.read()         frame = lanesDetection(frame)         cv.imshow('Lanes Detection', frame)         if cv.waitKey(1) & 0xFF == ord('q'):             break     cap.release()     cv.destroyAllWindows() if __name__ == "__main__":     videoLanes()

Database System Concepts
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
See similar textbooks
icon
Related questions
Question

can you please design a flowchart for this code?

 

import cv2 as cv
import numpy as np
from matplotlib import pyplot as plt


def lanesDetection(img):
 
    height = img.shape[0]
    width = img.shape[1]

    region_of_interest_vertices = [
        (200, height), (width/2, height/1.37), (width-300, height)
    ]
    gray_img = cv.cvtColor(img, cv.COLOR_RGB2GRAY)
    edge = cv.Canny(gray_img, 50, 100, apertureSize=3)
    cropped_image = region_of_interest(
        edge, np.array([region_of_interest_vertices], np.int32))

    lines = cv.HoughLinesP(cropped_image, rho=2, theta=np.pi/180,
                           threshold=50, lines=np.array([]), minLineLength=10, maxLineGap=30)
    image_with_lines = draw_lines(img, lines)
 
    return image_with_lines


def region_of_interest(img, vertices):
    mask = np.zeros_like(img)
 
    match_mask_color = (255)
    cv.fillPoly(mask, vertices, match_mask_color)
    masked_image = cv.bitwise_and(img, mask)
    return masked_image


def draw_lines(img, lines):
    img = np.copy(img)
    blank_image = np.zeros((img.shape[0], img.shape[1], 3), np.uint8)

    for line in lines:
        for x1, y1, x2, y2 in line:
            cv.line(blank_image, (x1, y1), (x2, y2), (0, 255, 0), 2)

    img = cv.addWeighted(img, 0.8, blank_image, 1, 0.0)
    return img


def videoLanes():
    cap = cv.VideoCapture('./img/Lane.mp4')
    while(cap.isOpened()):
        ret, frame = cap.read()
        frame = lanesDetection(frame)
        cv.imshow('Lanes Detection', frame)
        if cv.waitKey(1) & 0xFF == ord('q'):
            break

    cap.release()
    cv.destroyAllWindows()


if __name__ == "__main__":
    videoLanes()

 

Expert Solution
steps

Step by step

Solved in 3 steps with 1 images

SEE SOLUTIONCheck out a sample Q&A here
Blurred answer
Knowledge Booster
Topological Sort
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, computer-science and related others by exploring similar questions and additional content below.
Similar questions
Recommended textbooks for you
Database System Concepts
Database System Concepts
Computer Science
ISBN:
9780078022159
Author:
Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:
McGraw-Hill Education
Starting Out with Python (4th Edition)
Starting Out with Python (4th Edition)
Computer Science
ISBN:
9780134444321
Author:
Tony Gaddis
Publisher:
PEARSON
Digital Fundamentals (11th Edition)
Digital Fundamentals (11th Edition)
Computer Science
ISBN:
9780132737968
Author:
Thomas L. Floyd
Publisher:
PEARSON
C How to Program (8th Edition)
C How to Program (8th Edition)
Computer Science
ISBN:
9780133976892
Author:
Paul J. Deitel, Harvey Deitel
Publisher:
PEARSON
Database Systems: Design, Implementation, & Manag…
Database Systems: Design, Implementation, & Manag…
Computer Science
ISBN:
9781337627900
Author:
Carlos Coronel, Steven Morris
Publisher:
Cengage Learning
Programmable Logic Controllers
Programmable Logic Controllers
Computer Science
ISBN:
9780073373843
Author:
Frank D. Petruzella
Publisher:
McGraw-Hill Education
SEE MORE TEXTBOOKS