I got a code on the internet which works with raspberry pi 3 and Pi camera. I want to modify a portion of it. I want to display on the camera the distance the colored object the code identifies is from the middle of the streaming video.

The code I have streams a video that recognizes red color and puts a red dot on the object. The code is below;

import the necessary packages

from picamera.array import PiRGBArray

from picamera import PiCamera

import time

import cv2

import numpy as np

initialize the camera and grab a reference to the raw camera capture

camera = PiCamera()

camera.resolution = (480, 320)

camera.framerate = 30

camera.hflip = True

rawCapture = PiRGBArray(camera, size=(480, 320))

allow the camera to warmup

time.sleep(0.1)

capture frames from the camera

for frame in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):

# grab the raw NumPy array representing the image, then initialize the timestamp

# and occupied/unoccupied text

    image = frame.array

    blur = cv2.blur(image, (3,3))

    #hsv to complicate things, or stick with BGR
    #hsv = cv2.cvtColor(blur,cv2.COLOR_BGR2HSV)
    #thresh = cv2.inRange(hsv,np.array((0, 200, 200)), np.array((20, 255, 255)))

    lower = np.array([4,10,120],dtype="uint8")
    #upper = np.array([225,88,50], dtype="uint8")
    upper = np.array([90,100,255], dtype="uint8")

    thresh = cv2.inRange(blur, lower, upper)
    thresh2 = thresh.copy()

    # find contours in the threshold image
    image, contours,hierarchy = cv2.findContours(thresh,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)

    # finding contour with maximum area and store it as best_cnt
    max_area = 0
    best_cnt = 1
    for cnt in contours:
            area = cv2.contourArea(cnt)
            if area > max_area:
                    max_area = area
                    best_cnt = cnt

    # finding centroids of best_cnt and draw a circle there
    M = cv2.moments(best_cnt)
    cx,cy = int(M['m10']/M['m00']), int(M['m01']/M['m00'])
    #if best_cnt>1:
    cv2.circle(blur,(cx,cy),10,(100,100,255),-1)
    # show the frame
    cv2.imshow("Frame", blur)
    #cv2.imshow('thresh',thresh2)
    key = cv2.waitKey(1) & 0xFF

# clear the stream in preparation for the next frame
    rawCapture.truncate(0)

# if the `q` key was pressed, break from the loop
    if key == ord("q"):
        break

I got a code on the internet which works with raspberry pi 3 and Pi camera. I want to modify a portion of it. I want to display on the camera the distance the colored object the code identifies is from the middle of the streaming video.

The code I have streams a video that recognizes red color and puts a red dot on the object. The code is below;

use_video_port=True):

    # grab the raw NumPy array representing the image, then initialize the timestamp

 # and occupied/unoccupied text

     image = frame.array

     blur = cv2.blur(image, (3,3))

     #hsv to complicate things, or stick with BGR
     #hsv = cv2.cvtColor(blur,cv2.COLOR_BGR2HSV)
     #thresh = cv2.inRange(hsv,np.array((0, 200, 200)), np.array((20, 255, 255)))

     lower = np.array([4,10,120],dtype="uint8")
     #upper = np.array([225,88,50], dtype="uint8")
     upper = np.array([90,100,255], dtype="uint8")

     thresh = cv2.inRange(blur, lower, upper)
     thresh2 = thresh.copy()

     # find contours in the threshold image
     image, contours,hierarchy = cv2.findContours(thresh,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)

     # finding contour with maximum area and store it as best_cnt
     max_area = 0
     best_cnt = 1
     for cnt in contours:
             area = cv2.contourArea(cnt)
             if area > max_area:
                     max_area = area
                     best_cnt = cnt

     # finding centroids of best_cnt and draw a circle there
     M = cv2.moments(best_cnt)
     cx,cy = int(M['m10']/M['m00']), int(M['m01']/M['m00'])
     #if best_cnt>1:
     cv2.circle(blur,(cx,cy),10,(100,100,255),-1)
     # show the frame
     cv2.imshow("Frame", blur)
     #cv2.imshow('thresh',thresh2)
     key = cv2.waitKey(1) & 0xFF

 # clear the stream in preparation for the next frame
     rawCapture.truncate(0)

 # if the `q` key was pressed, break from the loop
     if key == ord("q"):
         break