OpenCV: 100 Essential Tips and Strategies for Mastering Image Processing in Computer Vision

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OpenCV (Open Source Computer Vision Library) is a powerful computer vision and image processing library in Python. Here are 100 tips for working with OpenCV:

1. Installation and Import:

1. Install OpenCV with pip install opencv-python.
2. Import OpenCV in your Python script or Jupyter Notebook with import cv2.

2. Image Reading and Display:

1. Read an image from a file with cv2.imread('path/to/image.jpg').
2. Display an image using cv2.imshow('Image', image).

3. Image Writing:

Save an image to a file with cv2.imwrite('output.jpg', image).

4. Image Properties:

1. Get image dimensions with height, width, channels = image.shape.
2. Access the number of pixels with num_pixels = image.size.

5. Color Spaces:

1. Convert an image to grayscale with gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY).
2. Switch color channels with b, g, r = cv2.split(image) and bgr_image = cv2.merge([b, g, r]).