Realizing color detection with OpenCV

1. Pre knowledge points

（1） HSV,Opencv Medium Mat And picture properties

https://mydreamambitious.blog.csdn.net/article/details/125339425

（2）Opencv Basic knowledge points in

https://mydreamambitious.blog.csdn.net/article/details/125351256

（3）Opencv Realize the basic transformation of the image

https://mydreamambitious.blog.csdn.net/article/details/125428402

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2. Code combat

（1） Create windows and set the size of video frames

cap=cv2.VideoCapture(0)
# Set the height and width of the display 
cap.set(cv2.CAP_PROP_FRAME_WIDTH,1100)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT,750)

（2） Flip the image and move the picture from BGR->HSV

ret,frame=cap.read()
    # Flip the image frame （ because opencv The image is opposite to our normal 
    frame=cv2.flip(src=frame,flipCode=2)
    # frame=cv2.resize(src=frame,dsize=(750,600))
    hsv_frame=cv2.cvtColor(src=frame,code=cv2.COLOR_BGR2HSV)

（3） obtain hsv The hue value of hue

# obtain hsv The hue value of hue
    pixel_center=hsv_frame[cy,cx]
    hue_value=pixel_center[0]

（4） Define the color according to the hue value

color='Unknow'
    if hue_value<5:
        color='RED'
    elif hue_value<22:
        color='ORANGE'
    elif hue_value<33:
        color="YELLOW"
    elif hue_value<78:
        color="GREEN"
    elif hue_value<131:
        color="BLUE"
    elif hue_value<167:
        color="VIOLED"
    else:
        color="RED"

（5） Draw detection area

# Draw detection area 
    cv2.rectangle(img=frame,pt1=(width//2+100,20),pt2=(width//2+390,200),color=(0,255,0),thickness=2)
    cv2.putText(img=frame,text='detect locate',org=(width//2+150,cy-10),fontFace=cv2.FONT_HERSHEY_SIMPLEX,
                fontScale=1.0,color=(0,255,0),thickness=2)

（6） Draw the text of the test results

# Get the object color of the detection position 
    b,g,r=int(frame[cy,cx][0]),int(frame[cy,cx][1]),int(frame[cy,cx][2])
    # Draw text 
    cv2.putText(img=frame,text=color,org=(20,50),fontFace=cv2.FONT_HERSHEY_SIMPLEX,
                fontScale=1.0,color=(0,255,0),thickness=2)
    cv2.circle(img=frame,center=(cx+30,cy),radius=5,color=(0,255,0),thickness=3)

（7） The overall code

import os
import cv2
import numpy as np

cap=cv2.VideoCapture(0)
# Set the height and width of the display 
cap.set(cv2.CAP_PROP_FRAME_WIDTH,1100)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT,750)

while cap.isOpened():
    ret,frame=cap.read()
    # Flip the image frame （ because opencv The image is opposite to our normal 
    frame=cv2.flip(src=frame,flipCode=2)
    # frame=cv2.resize(src=frame,dsize=(750,600))
    hsv_frame=cv2.cvtColor(src=frame,code=cv2.COLOR_BGR2HSV)
    # Get the height and width of the read frame 
    height,width,channel=frame.shape
    # print(height,width)
    # Get the location of the checkpoint 
    cx = width // 2+190
    cy=height//6+30
    # Draw detection area 
    cv2.rectangle(img=frame,pt1=(width//2+100,20),pt2=(width//2+390,200),color=(0,255,0),thickness=2)
    cv2.putText(img=frame,text='detect locate',org=(width//2+150,cy-10),fontFace=cv2.FONT_HERSHEY_SIMPLEX,
                fontScale=1.0,color=(0,255,0),thickness=2)
    # obtain hsv The hue value of hue
    pixel_center=hsv_frame[cy,cx]
    hue_value=pixel_center[0]
    color='Unknow'
    if hue_value<5:
        color='RED'
    elif hue_value<22:
        color='ORANGE'
    elif hue_value<33:
        color="YELLOW"
    elif hue_value<78:
        color="GREEN"
    elif hue_value<131:
        color="BLUE"
    elif hue_value<167:
        color="VIOLED"
    else:
        color="RED"
    # Get the object color of the detection position 
    b,g,r=int(frame[cy,cx][0]),int(frame[cy,cx][1]),int(frame[cy,cx][2])
    # Draw text 
    cv2.putText(img=frame,text=color,org=(20,50),fontFace=cv2.FONT_HERSHEY_SIMPLEX,
                fontScale=1.0,color=(0,255,0),thickness=2)
    cv2.circle(img=frame,center=(cx+30,cy),radius=5,color=(0,255,0),thickness=3)

    cv2.imshow('frame',frame)
    key=cv2.waitKey(1)
    if key==27:
        break

cap.release()
cv2.destroyAllWindows()

# # Picture reading and zooming 
# img=cv2.imread('images/1.png')
# img=cv2.resize(src=img,dsize=(450,450))
# # display picture 
# cv2.imshow('img',img)
# cv2.waitKey(0)
# cv2.destroyAllWindows()

if __name__ == '__main__':
    print('Pycharm')

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Reference link https://b23.tv/6ZJL1WY