Detect different color blob opencv

Question

I'm new to opencv and for a school project i need to detect a red and a green circle with a camera, so i've use blobdetection, but it detect me the two colors, i think that my mask is bad, each color is linked to a specific action.

At the moment my code detect well red and green circle on the same page but i want it to detect only red circle on a white page.

Thank for your help

# Standard imports
import cv2
import numpy as np;

    # Read image
im = cv2.VideoCapture(0)

# Setup SimpleBlobDetector parameters.
params = cv2.SimpleBlobDetector_Params()

# Change thresholds
params.minThreshold = 100;
params.maxThreshold = 200;

# Filter by Area.
params.filterByArea = True
params.minArea = 200
params.maxArea = 20000

# Filter by Circularity
params.filterByCircularity = True
params.minCircularity = 0.1

# Filter by Convexity
params.filterByConvexity = True
params.minConvexity = 0.1

# Filter by Inertia
params.filterByInertia = True
params.minInertiaRatio = 0.1


blueLower = (0,85,170)  #100,130,50
blueUpper = (140,110,255) #200,200,130


while(1):

    ret, frame=im.read()

    mask = cv2.inRange(frame, blueLower, blueUpper)
    mask = cv2.erode(mask, None, iterations=0)
    mask = cv2.dilate(mask, None, iterations=0)
    frame = cv2.bitwise_and(frame,frame,mask = mask)

# Set up the detector with default parameters.
    detector = cv2.SimpleBlobDetector_create(params)

# Detect blobs.
    keypoints = detector.detect(mask)

# Draw detected blobs as red circles.
# cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS ensures the size of the circle corresponds to the size of blob
    im_with_keypoints = cv2.drawKeypoints(mask, keypoints, np.array([]), (0,0,255), cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)


# Display the resulting frame

    frame = cv2.bitwise_and(frame,im_with_keypoints,mask = mask)

    cv2.imshow('frame',frame)

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

# When everything done, release the capture
im.release()
cv2.destroyAllWindows()

EDIT 1: Code update

Now i got a issue where my full circle isn't detected.

No Blob Detection

Second Version

# Standard imports
import cv2
import numpy as np;

# Read image
im = cv2.VideoCapture(0)

while(1):
        ret, frame=im.read()


        lower = (130,150,80)  #130,150,80
        upper = (250,250,120) #250,250,120
        mask = cv2.inRange(frame, lower, upper)
        lower, contours, upper = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
        blob = max(contours, key=lambda el: cv2.contourArea(el))
        M = cv2.moments(blob)
        center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))
        canvas = im.copy()
        cv2.circle(canvas, center, 2, (0,0,255), -1)

        cv2.imshow('frame',frame)

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

Answer 1

You need to work out what the BGR numbers for your green are (let's say for arguments sake [0, 255, 0]), then create a mask that ignores any colours outside a tolerance around your green:

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

Take a look at this tutorial for a step by step.

Play around with lower and upper to get the right behaviour. Then you can find the contours in the mask:

_, contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, 
                                                    cv2.CHAIN_APPROX_NONE)

Then go through the contours list to find the biggest one (filter out any possible noise):

blob = max(contours, key=lambda el: cv2.contourArea(el))

And that's your final 'blob'. You can find the center by doing:

M = cv2.moments(blob)
center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))

You can draw this center onto a copy of your image, for checking:

canvas = im.copy()
cv2.circle(canvas, center, 2, (0,0,255), -1)

Obviously, this makes the assumption that there's only one green ball and nothing else green in the image. But it's a start.

EDIT - RESPONSE TO SECOND POST

I think the following should work. I haven't tested it, but you should be able to at least do a bit more debugging with the canvas and mask displayed:

# Standard imports
import cv2
import numpy as np;

# Read image
cam = cv2.VideoCapture(0)

while(1):
        ret, frame = cam.read()

        if not ret:
            break

        canvas = frame.copy()


        lower = (130,150,80)  #130,150,80
        upper = (250,250,120) #250,250,120
        mask = cv2.inRange(frame, lower, upper)
        try:
            # NB: using _ as the variable name for two of the outputs, as they're not used
            _, contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
            blob = max(contours, key=lambda el: cv2.contourArea(el))
            M = cv2.moments(blob)
            center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))

            cv2.circle(canvas, center, 2, (0,0,255), -1)

        except (ValueError, ZeroDivisionError):
            pass

        cv2.imshow('frame',frame)
        cv2.imshow('canvas',canvas)
        cv2.imshow('mask',mask)

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

Answer 2

You should use HSV color space for better results if you wanna make filter by color.

ret, frame=im.read()

frame= cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) # Add this to your code

mask = cv2.inRange(frame, blueLower, blueUpper)