Draw in an area, based on an color filter in Python

asked 2019-06-17 16:14:06 -0500

Arruda gravatar image

Hi, I'm developing a script that detects 2 lines that are laser sketches on the floor,

example:

image description

With the code below I can identify the lights and draw lines in the detection area:

vermelho_inicio = np.array([0, 9, 178]) #131,72,208 vermelho_fim = np.array([255, 60, 255]) mask = cv2.inRange(img, vermelho_inicio, vermelho_fim)

edges = cv2.Canny(mask, 100, 200)
#DESENHO AS LINHAS NO LASER (Cone)
lines = cv2.HoughLinesP(edges, 5, np.pi/180, 0, maxLineGap=100)
a,b,c = lines.shape
if lines is not None:
   for line in lines:          
      x1, y1, x2, y2 = line[0]
      cv2.line(img, (x1, y1), (x2, y2), (0, 255, 0), 5)

And my result Is:

image description

What I need?

I need to draw the area detected in red and get the positions x1, y1, x2, y2 of the drawn area. The result I hope is the result below or something close to that:

image description

My Complet Code:

# -*- coding: utf-8 -*-
import numpy as np
import cv2
import time
import math

#STREAMINGS
#http://68.116.13.142:82/mjpg/video.mjpg INDUSTRIAL
#http://95.255.38.86:8080/mjpg/video.mjpg RUA ITALIA
#http://81.198.213.128:82/mjpg/video.mjpg CORREDOR MOVIMENTADO

class DetectorAPI:


     cap = cv2.VideoCapture("VideoCone.MOV")
     while True:
        r, img = cap.read()
        #DEFINE A ÁREA DO VIDEO EM QUE O MODELO IRA ATUAR
        #img = img[10:1280, 230:1280]
        img = cv2.resize(img, (800, 600))
        #Frame Detectação Red Zone
        #frame = cv2.GaussianBlur(img (5, 5), 0)
        vermelho_inicio = np.array([0, 9, 178])
        #131,72,208
        vermelho_fim = np.array([255, 60, 255])
        mask = cv2.inRange(img, vermelho_inicio, vermelho_fim)

        edges = cv2.Canny(mask, 100, 200)
        #DESENHO AS LINHAS NO LASER (Cone)
        lines = cv2.HoughLinesP(edges, 5, np.pi/180, 0, maxLineGap=100)
        a,b,c = lines.shape
        if lines is not None:
           for line in lines:          
              x1, y1, x2, y2 = line[0]
              cv2.line(img, (x1, y1), (x2, y2), (0, 255, 0), 5)


        #Crio o overlay para fazer a transparência no quadrado da Danger Área
        overlay = img.copy()



        #DESENHO A DANGER ÁREA
        #x1,y1 ------
        #|          |
        #|          |
        #|          |
        #--------x2,y2
        #CAPTURO AS INFORMAÇÕES DO FRAME
        height, width, channels = img.shape
        #DIVISÃO PARA CAPTURAR O CENTRO DA IMAGEM
        upper_left = (int(width / 4), int(height / 4))
        bottom_right = (int(width * 3 / 4), int(height * 3 / 4))
        #ESCREVO O RETANGULO NO CENTRO DO VÍDEO
        #DangerArea = cv2.rectangle(overlay,upper_left, bottom_right,(0,0,255),-1);
        #Escrevo o texto na Danger Area
        #cv2.putText(DangerArea,'Danger Area',(int(width / 4),int(height * 3 / 4)),  cv2.FONT_HERSHEY_SIMPLEX, 0.5,(255,255,255),2,cv2.LINE_AA)
        #cv2.addWeighted(overlay,0.3,img,1-0.4,0,img);
        #Imprimo no console o centro da imagem
        print('Upper_Left: '+str(upper_left)+' bottom_right: '+str(bottom_right));


        #Exibe o video 
        cv2.imshow("edges", edges)
        cv2.imshow("Detectar Pessoas", img)

        key = cv2.waitKey(1)
        if key & 0xFF == ord('q'):
            break
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