Assignment.py

"""
🖼️ Image Blurring and Sharpening App
====================================

This app allows users to experiment with different image filtering techniques
such as Gaussian Blur, Median Blur, and Sharpening using OpenCV.

-------------------------------------------------------------
📋 Instructions:

1. Start the program.

2. Choose one of the following options:
   ------------------------------------
   [1] Apply Gaussian Blur
       • Upload or select an image
       • Provide kernel size (odd numbers only, e.g., 3, 5, 9)
       • Set sigma value (strength of blur)
       • Result: Smoothened image by averaging nearby pixels

   [2] Apply Median Blur
       • Upload or select an image
       • Provide kernel size (odd number, e.g., 3, 5, 7)
       • Result: Removes salt-and-pepper noise using median filter

   [3] Apply Sharpening Filter
       • Upload or select an image
       • Set ddepth value (e.g., -1 to match input depth)
       • Result: Enhances edges and image contrast

   [4] View Original Image
       • Simply displays the uploaded image without processing

-------------------------------------------------------------
💡 Notes:

- All filters work with color images (BGR) using OpenCV.
- Filtered images are shown in a popup window (CLI) or on the page (Streamlit).
- Users can optionally download/save the processed image.

-------------------------------------------------------------
🎓 Learning Objectives:

✅ Understand how image blurring (Gaussian & Median) works
✅ Learn edge enhancement using sharpening kernels
✅ Get hands-on with OpenCV functions and image processing concepts

-------------------------------------------------------------
🔧 Dependencies:

• OpenCV (cv2)
• NumPy
• Streamlit (for web app version)
• PIL (Pillow, for image saving)

"""

import cv2
import numpy as np


def load_image():
    path = input("Enter the full path to the image: ")
    img = cv2.imread(path)
    if img is None:
        print("❌ Failed to load image. Please check the path.")
    return img


def apply_gaussian_blur(img):
    kx = int(input("Enter kernel size X (odd number): "))
    ky = int(input("Enter kernel size Y (odd number): "))
    sigma = float(input("Enter sigma value: "))
    blurred = cv2.GaussianBlur(img, (kx, ky), sigma)
    return blurred


def apply_median_blur(img):
    k = int(input("Enter kernel size (odd number): "))
    median = cv2.medianBlur(img, k)
    return median


def apply_sharpening(img):
    ddepth = int(input("Enter ddepth (-1 for default): "))
    kernel = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]])
    sharpened = cv2.filter2D(img, ddepth, kernel)
    return sharpened


def show_image(title, img):
    cv2.imshow(title, img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()


def save_image(img):
    path = input("Enter filename to save (e.g., output.jpg): ")
    cv2.imwrite(path, img)
    print(f"✅ Saved as {path}")


def main():
    print("\n=== 🖼️ Image Filtering CLI ===")
    print("Choose an option:")
    print("1. Apply Gaussian Blur")
    print("2. Apply Median Blur")
    print("3. Apply Sharpening Filter")
    print("4. View Original Image")

    choice = input("Enter choice (1-4): ")
    img = load_image()
    if img is None:
        return

    if choice == "1":
        result = apply_gaussian_blur(img)
    elif choice == "2":
        result = apply_median_blur(img)
    elif choice == "3":
        result = apply_sharpening(img)
    elif choice == "4":
        show_image("Original Image", img)
        return
    else:
        print("❌ Invalid choice")
        return

    show_image("Processed Image", result)
    save = input("Do you want to save the image? (y/n): ").lower()
    if save == "y":
        save_image(result)


if __name__ == "__main__":
    main()