Practice

import cv2
import numpy as np

def inspect_image(image_path):
    """
    A complete image inspector — practice applying Module 1 concepts.
    """
    # Load the image
    image = cv2.imread(image_path)

    if image is None:
        print(f"Error: Could not load image from '{image_path}'")
        print("Make sure the file path is correct and the image exists.")
        return

    print("=" * 45)
    print("IMAGE INSPECTION REPORT")
    print("=" * 45)

    # Basic dimensions
    height, width, channels = image.shape
    print(f"Width:      {width} pixels")
    print(f"Height:     {height} pixels")
    print(f"Channels:   {channels}")
    print(f"Total pixels: {width * height:,}")
    print(f"Memory used: {image.nbytes:,} bytes")
    print(f"Data type:  {image.dtype}")

    # Colour channel analysis
    b, g, r = cv2.split(image)
    print()
    print("COLOUR CHANNEL STATISTICS")
    print(f"  Blue  — min: {b.min():3d}, max: {b.max():3d}, mean: {b.mean():.1f}")
    print(f"  Green — min: {g.min():3d}, max: {g.max():3d}, mean: {g.mean():.1f}")
    print(f"  Red   — min: {r.min():3d}, max: {r.max():3d}, mean: {r.mean():.1f}")

    # Grayscale analysis
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    print()
    print("GRAYSCALE ANALYSIS")
    print(f"  Min brightness:  {gray.min()}")
    print(f"  Max brightness:  {gray.max()}")
    print(f"  Mean brightness: {gray.mean():.1f}")

    # Sample some pixels
    print()
    print("SAMPLE PIXELS (row, col) -> [B, G, R]")
    for row, col in [(0, 0), (height//2, width//2), (height-1, width-1)]:
        print(f"  ({row}, {col}) -> {image[row, col]}")

    print("=" * 45)

# Run the inspector
# Replace with a real image path on your computer
inspect_image("your_image.jpg")