[Python] What is the difference between using cv2.imread(path) with cvtColor vs...

I came across two ways to convert an image to grayscale, and I want to understand the difference between them:

# Method 1
image = cv2.imread('image.png')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)


and

# Method 2
gray = cv2.imread('image.png', cv2.IMREAD_GRAYSCALE)


From what I understand:

1. In the first method, the image is first loaded as a color (BGR) image, and then converted to grayscale using cvtColor.
2. In the second method, the image is directly read in grayscale mode.

Could someone please explain:

• What exactly is the difference between these two approaches internally?
• Are there any advantages or disadvantages in terms of performance or image data quality?
• In which cases should each approach be preferred?

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