Image processing is a critical task in various fields such as computer vision, medical imaging, and machine learning. While the topic of "processamento de imagem" is broad, it is highly relevant to the Apple environment, particularly macOS, which provides robust support for image processing through various libraries and tools. This article will guide you on how to perform image processing on macOS using Python, leveraging libraries such as OpenCV and Pillow. These libraries offer extensive functionalities for manipulating and analyzing images, making them ideal for developers and researchers working on macOS.

Examples:

1. Setting Up the Environment:
To get started with image processing on macOS, you need to install Python and the necessary libraries. You can use Homebrew to install Python if it's not already installed.

   brew install python

Next, install the OpenCV and Pillow libraries using pip:

   pip install opencv-python Pillow

2. Basic Image Processing with OpenCV:
Below is a simple Python script to read an image, convert it to grayscale, and save the processed image.

   import cv2



   # Read the image

   image = cv2\.imread('input.jpg')



   # Convert to grayscale

   gray_image = cv2\.cvtColor(image, cv2\.COLOR_BGR2GRAY)



   # Save the processed image

   cv2\.imwrite('output_gray.jpg', gray_image)



   print("Image processing complete. Grayscale image saved as 'output_gray.jpg'.")

To run the script, save it as image_processing.py and execute it via Terminal:

   python image_processing.py

3. Image Manipulation with Pillow:
Pillow is another powerful library for image processing. Here is an example of how to resize an image and apply a filter using Pillow.

   from PIL import Image, ImageFilter



   # Open an image file

   with Image.open('input.jpg') as img:

       # Resize the image

       img_resized = img.resize((800, 600))



       # Apply a filter

       img_filtered = img_resized.filter(ImageFilter.BLUR)



       # Save the processed image

       img_filtered.save('output_filtered.jpg')



       print("Image processing complete. Filtered image saved as 'output_filtered.jpg'.")

To run this script, save it as pillow_processing.py and execute it via Terminal:

   python pillow_processing.py