CODEWITHSUNDEEP
pythonopencv
vincenthavinh
vincenthavinh

Reputation: 462

wrong colors when saving image with openCV

With openCV, when I save my processed image in .png format with openCV, I get differents colors than when I display it on screen.

(code is at the end of message)

Here's what I get by displaying the image on screen with cv2.imshow('after', after) (that is what I want):

enter image description here

Here's what I get by saving the same image in .png with cv2.imwrite("debug.png", after) (that is not what I want):

enter image description here

The box and center seems to be transparent, because when I open the .png on vs code, they are blackish like vs code background (see picture above), but when I open it in windows Photos software, they are white (see picture below)

enter image description here

Here's my code that is kind of a fusion between this post and this post. It draws green boxes around differences between two images and draws the center of each difference :

def find_diff(before, after):
    before = np.array(before)
    after = np.array(after)

    # Convert images to grayscale
    before_gray = cv2.cvtColor(before, cv2.COLOR_BGR2GRAY)
    after_gray = cv2.cvtColor(after, cv2.COLOR_BGR2GRAY)

    # Compute SSIM between two images
    (score, diff) = structural_similarity(before_gray, after_gray, full=True)
    diff = (diff * 255).astype("uint8")

    # Threshold the difference image, followed by finding contours to
    # obtain the regions of the two input images that differ
    thresh = cv2.threshold(diff, 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
    contours = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    contours = contours[0] if len(contours) == 2 else contours[1]

    centers = []
    for c in contours:
        area = cv2.contourArea(c)
        if area > 40:
            # Find centroid
            M = cv2.moments(c)
            cX = int(M["m10"] / M["m00"])
            cY = int(M["m01"] / M["m00"])
            centers.append((cY,cY)) 
            cv2.circle(after, (cX, cY), 2, (320, 159, 22), -1) 
            
            #draw boxes on diffs
            x, y, w, h = cv2.boundingRect(c)
            cv2.rectangle(after, (x, y), (x + w, y + h), (36, 255, 12), 2)

    cv2.imwrite("debug.png", after)
    cv2.imshow('after', after)
    cv2.waitKey(0)
    return centers


before = mss.mss().grab((466, 325, 1461, 783))
sleep(3)
after = mss.mss().grab((466, 325, 1461, 783))
relative_diffs = find_diff(before, after)

I can't figure out at which step it messes up. I do give green and blue colors when calling .circle() and .rectangle().

Upvotes: 0

Views: 863

Answers (1)

vincenthavinh
vincenthavinh

Reputation: 462

As @fmw42 pointed at me in the question comments section, I was calling np.array() on mss ScreenShot objects and expecting them to it to work out of the box. It turns out ScreenShot class stores image data on a specific format, and when np.array() manipulates an instance object, it uses a different format for managing image channels, specifically the alpha channel.

So the solution was to first convert mss ScreenShot objects in Image objects that hold image data in compatible way for np.array() to handle them :

def find_diff(before, after):
    before = Image.frombytes("RGB", before.size, before.bgra, "raw", "BGRX")
    after = Image.frombytes("RGB", after.size, after.bgra, "raw", "BGRX")
    before = np.array(before)
    after = np.array(after)
    ...

Upvotes: 1

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