image-processing-basics

Introductory image processing project built during Deep Learning course at Tehran Data

🛠 Libraries Used

• matplotlib.pyplot for loading and displaying images
• numpy for handling image data as arrays

📌 What You’ll Learn

• Reading an image using plt.imread()
• Displaying the image using plt.imshow()
• Checking image dimensions using .shape
• Accessing a specific pixel's RGB values
• Modifying individual color channels
• Recoloring a specific region in the image
• Converting an RGB image to grayscale
• Displaying grayscale images properly using cmap='gray'

▶️ How to Run

1. Upload your target image (e.g., sign.jpg) into the /content/ directory if using Google Colab.
2. Open the notebook and run all cells in sequence.
3. Make sure to update the image path if you're running this locally or from a different directory.

🎓 Credits

Notebook created as part of a learning exercise during the Deep Learning course at Tehran Data School, with reference to code from Dr. Alireza Akhavan's GitHub repo.