Answered Essay: I have a color detection code using the Pi Camera and OpenCV. I need help with WHILE and ELSE or IF and E

I have a color detection code using the Pi Camera and OpenCV. I need help with WHILE and ELSE or IF and ELSE statements in the code on recognizing a particular color. I want to know how to write the statement that results in a reaction after the code is detected. Part of the code is below;

#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([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)
cv2.putText(blur, “Red Detected”, (cx – 20, cy – 20),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 2)
# 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)

*while (thresh = cv2.inRange(blur, lower, upper)):
Thrusters_control.forward()
else:
Thrusters_control.turn_right()*

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

Expert Answer

 

Option 1:

You can get the bounds for the colours you need:

upper = np.array([210,90,70], dtype=”uint8″)

lower = np.array([76,31,4],dtype=”uint8″)

red_upper =np.array([0,0,255],dtype=”uint8″)

red_lower = np.array([30,30,200],dtype=”uint8″)

green_upper =np.array([0,255,0],dtype=”uint8″)

green_lower = np.array([30,200,30],dtype=”uint8″)

blue_upper =np.array([2550,0,0],dtype=”uint8″)

blue_lower = np.array([200,30,30],dtype=”uint8″)

Now you can detect each color using a function.

Option 2:

Alternatively, you can use Python to define your colours and then detect them:

colourLimits =

[

([17, 15, 100], [50, 56, 200]),

([86, 31, 4], [220, 88, 50]),

([25, 146, 190], [62, 174, 250]),

([103, 86, 65], [145, 133, 128])

]

Now you can employ colour detection –

# loop over the colour limits

for (lower, upper) in the limits:

# create NumPy arrays from the colour limits

upper = np.array(upper, dtype = “uint8”)

lower = np.array(lower, dtype = “uint8”)

# now apply a mask for the colours

mask = cv2.inRange(image, lower, upper)

output = cv2.bitwise_and(image, image, mask = mask)

# now have the images shown

cv2.imshow(“images”, np.hstack([image, output]))

cv2.waitKey(0)

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