I have a laser pointer that projects red cross shape. My aim is to write a python code that detects those two projected lines from a video source. I use my mobile phone camera as a source and the video is streamed via web IP source.

First, I wanted to detect the lines from a single image before trying it out with video input. I have written python code below, as a result I came out with multiple lines instead of the main lines on the cross. You can see input and output images. I want to get rid of unwanted lines and detect only the main two lines on the cross.

# import necessary modules
import numpy as np
import urllib.request
import cv2 as cv

# read the image
with open("5.jpg", "rb") as image:
    f = image.read()

    # convert to byte array
    bytef = bytearray(f)

    # convert to numpy array
    image = np.asarray(bytef)

    # Convert image to grayscale
    gray = cv.imdecode(image, 1)

    # Use canny edge detection
    edges = cv.Canny(gray, 50, 150, apertureSize=3) # default apertureSize: 3

    # Apply HoughLinesP method to
    # to directly obtain line end points
    lines_list = []
    lines = cv.HoughLinesP(
        edges,  # Input edge image
        1,  # Distance resolution in pixels
        np.pi / 180,  # Angle resolution in radians
        threshold=100,  # Min number of votes for valid line (default: 100)
        minLineLength=50,  # Min allowed length of line
        maxLineGap=10  # Max allowed gap between line for joining them (default: 10)
    )

    if lines is not None:
        # Iterate over points
        for points in lines:
            # Extracted points nested in the list
            x1, y1, x2, y2 = points[0]
            # Draw the lines joing the points
            # On the original image
            cv.line(gray, (x1, y1), (x2, y2), (0, 255, 0), 2)
            # Maintain a simples lookup list for points
            lines_list.append([(x1, y1), (x2, y2)])

    # display image
    cv.imshow("Image", gray)
    cv.waitKey()

input image
output image

When I tried it with video source, it did not detect any lines at all. Mobile app that I used to stream video is “IP Webcam”. You can see my code below.

import numpy as np
import cv2 as cv

# replace with your own IP provided in ip webcam mobile app "IPv4_address/video"
cap = cv.VideoCapture("http://192.168.1.33:8080/video")

while(True):
    _, image = cap.read()

    # Resize the image
    image = cv.resize(image, (500, 500))

    # Convert image to grayscale
    gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)

    # Use canny edge detection
    edges = cv.Canny(gray, 50, 150, apertureSize=3)

    # Apply HoughLinesP method to
    # to directly obtain line end points
    lines_list = []
    lines = cv.HoughLinesP(
        edges,  # Input edge image
        1,  # Distance resolution in pixels
        np.pi / 180,  # Angle resolution in radians
        threshold=10,  # Min number of votes for valid line (default: 100)
        minLineLength=5,  # Min allowed length of line
        maxLineGap=200  # Max allowed gap between line for joining them (default: 10)
    )

    if lines is not None:
        # Iterate over points
        for points in lines:
            # Extracted points nested in the list
            x1, y1, x2, y2 = points[0]
            # Draw the lines joing the points
            # On the original image
            cv.line(gray, (x1, y1), (x2, y2), (0, 255, 0), 2)
            # Maintain a simples lookup list for points
            lines_list.append([(x1, y1), (x2, y2)])

    cv.imshow('Livestream', image)
    if cv.waitKey(1) == ord('q'):
        break

cap.release()
cv.destroyAllWindows()