Color space conversion in Computer Vision - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to convert an image from BGR to grayscale using OpenCV.

Computer Vision

gray_image = cv2.cvtColor(color_image, [1])

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Acv2.COLOR_BGR2GRAY

Bcv2.COLOR_RGB2GRAY

Ccv2.COLOR_GRAY2BGR

Dcv2.COLOR_BGR2RGB

Attempts:

3 left

💡 Hint

Common Mistakes

Using cv2.COLOR_RGB2GRAY which assumes the image is in RGB format.

Using cv2.COLOR_GRAY2BGR which converts grayscale to color, not the other way.

OpenCV uses BGR format by default, so to convert to grayscale, use cv2.COLOR_BGR2GRAY.

2fill in blank

medium

Complete the code to convert an image from BGR to HSV color space.

Computer Vision

hsv_image = cv2.cvtColor(input_image, [1])

Drag options to blanks, or click blank then click option'

Acv2.COLOR_RGB2HSV

Bcv2.COLOR_BGR2HSV

Ccv2.COLOR_HSV2BGR

Dcv2.COLOR_BGR2GRAY

Attempts:

3 left

💡 Hint

Common Mistakes

Using cv2.COLOR_RGB2HSV which is incorrect for BGR images.

Using cv2.COLOR_HSV2BGR which converts back from HSV to BGR.

Since OpenCV images are in BGR format, use cv2.COLOR_BGR2HSV to convert to HSV.

3fill in blank

hard

Fix the error in the code to convert an image from HSV back to BGR.

Computer Vision

bgr_image = cv2.cvtColor(hsv_image, [1])

Drag options to blanks, or click blank then click option'

Acv2.COLOR_BGR2HSV

Bcv2.COLOR_RGB2HSV

Ccv2.COLOR_HSV2BGR

Dcv2.COLOR_BGR2GRAY

Attempts:

3 left

💡 Hint

Common Mistakes

Using cv2.COLOR_BGR2HSV which converts in the wrong direction.

Using cv2.COLOR_BGR2GRAY which changes color space incorrectly.

To convert from HSV back to BGR, use cv2.COLOR_HSV2BGR.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps color names to their HSV ranges.

Computer Vision

hsv_ranges = {color: ([1], [2]) for color in colors}

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Alower_bounds

Bupper_bounds

Ccolor

Drange

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'color' or 'range' instead of the HSV bound variables.

Swapping lower and upper bounds.

The dictionary maps each color to a tuple of its lower and upper HSV bounds.

5fill in blank

hard

Fill all three blanks to create a mask for a color range and apply it to the image.

Computer Vision

mask = cv2.inRange(hsv_image, [1], [2])
result = cv2.bitwise_and(original_image, original_image, mask=[3])

Drag options to blanks, or click blank then click option'

Alower_hsv

Bupper_hsv

Cmask

Dhsv_image

Attempts:

3 left

💡 Hint

Common Mistakes

Using the image instead of mask in the bitwise_and function.

Swapping lower and upper HSV bounds.

The mask is created using lower and upper HSV bounds, then applied to the original image using the mask.