Reading images (cv2.imread) in Computer Vision - ML Experiment: Train & Evaluate

Experiment - Reading images (cv2.imread)

Problem:You want to read images correctly using OpenCV's cv2.imread function to use them in your machine learning project.

Current Metrics:Currently, images are not loading properly; cv2.imread returns None, causing errors in further processing.

Issue:The images are not read because the file path might be incorrect or the image format is unsupported.

Your Task

Successfully load an image using cv2.imread and verify it is loaded by displaying its shape and showing the image in a window.

You must use cv2.imread to read the image.

Do not use other image reading libraries like PIL or matplotlib for loading.

Ensure the image path is correct and handle the case when the image is not found.

Hint 1

Hint 2

Hint 3

Solution

Computer Vision

import cv2

# Replace 'image.jpg' with your actual image file path
image_path = 'image.jpg'

# Read the image
image = cv2.imread(image_path)

# Check if image was loaded successfully
if image is None:
    print(f"Error: Image at path '{image_path}' could not be loaded.")
else:
    print(f"Image loaded successfully with shape: {image.shape}")
    # Display the image in a window
    cv2.imshow('Loaded Image', image)
    cv2.waitKey(0)  # Wait for a key press to close the window
    cv2.destroyAllWindows()

Added a check to verify if the image was loaded (image is not None).

Printed the shape of the loaded image to confirm successful reading.

Used cv2.imshow and cv2.waitKey to display the image window.

Included error message if image path is incorrect or image is missing.

Results Interpretation

Before: cv2.imread returned None, causing errors downstream.

After: Image is loaded correctly, shape is printed, and image is displayed in a window.

Always verify that images are loaded successfully with cv2.imread before processing. Incorrect paths or unsupported formats cause None returns.

Bonus Experiment

Try reading a grayscale image by using the flag cv2.IMREAD_GRAYSCALE in cv2.imread and display it.

💡 Hint

Use cv2.imread(image_path, cv2.IMREAD_GRAYSCALE) to load the image in grayscale mode.