Topic: Python OpenCV – Part 1: Introduction, Image Reading, and Basic Operations

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What is OpenCV?

• OpenCV (Open Source Computer Vision Library) is a powerful computer vision and image processing library.

• It supports image and video capture, analysis, object detection, face recognition, and much more.

• Commonly used with Python, C++, and machine learning pipelines.

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Installing OpenCV

pip install opencv-python

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1. Reading and Displaying Images

import cv2

# Read the image
image = cv2.imread('image.jpg')

# Display the image in a window
cv2.imshow('My Image', image)
cv2.waitKey(0)  # Wait for any key to close the window
cv2.destroyAllWindows()

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2. Image Shape and Type

print(image.shape)  # (height, width, channels)
print(image.dtype)  # uint8 (8-bit integers for each channel)

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3. Converting Color Spaces

# Convert BGR to Grayscale
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# Convert BGR to RGB (for matplotlib or image correction)
rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)

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4. Saving an Image

cv2.imwrite('gray_image.png', gray)

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5. Drawing Shapes

# Draw a red rectangle
cv2.rectangle(image, (50, 50), (200, 200), (0, 0, 255), 2)

# Draw a filled circle
cv2.circle(image, (150, 150), 40, (255, 0, 0), -1)

# Draw text
cv2.putText(image, 'OpenCV!', (40, 300), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)

cv2.imshow('Drawn Image', image)
cv2.waitKey(0)
cv2.destroyAllWindows()

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6. Resize and Flip

# Resize image
resized = cv2.resize(image, (300, 300))

# Flip image horizontally
flipped = cv2.flip(image, 1)

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Summary

• OpenCV allows you to read, display, modify, and save images easily.

• You can perform basic tasks like drawing, resizing, flipping, and color transformations.

• These operations are the building blocks for image analysis, preprocessing, and machine vision applications.

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Exercise

• Write a program that:

1. Loads an image.
2. Converts it to grayscale.
3. Draws a blue circle in the center.
4. Saves the new image to disk.

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