ImageProcessing.py

from PIL import Image
import os
import cv2 
# ------ Flipping of Ambulance Text Image ------ #

# file_path = r"Ambulance.png"

# if os.path.exists(file_path):
#     img = Image.open(file_path)
#     transposeImg = img.transpose(Image.FLIP_LEFT_RIGHT)
#     transposeImg.save("flippedAmbulance.png")
#     print("Transpose is Done!")
# else:
#     print("Error: File not found! Please check the path.")

img= cv2.imread(r"DhakshuScenery.jpg") # Read the Image using 'imread()'

# Ensure the image is loaded  
if img is None:
    print("Error: File not found! Check the path.")
    exit()

# Convert to Gray Color  
gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)  

# 1️⃣ CLAHE - Contrast-Limited Adaptive Histogram Equalization  
clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))  
clahe_img = clahe.apply(gray_img)  

# 2️⃣ Gaussian Blur (Smooth Effect)  
gaussian_blur = cv2.GaussianBlur(img, (15, 15), 0)  

# 3️⃣ Edge Detection (Canny Edge Filter)  
edges = cv2.Canny(img, 100, 200)  

# 4️⃣ Sketch Effect (Invert + Blur + Divide)  
inv_gray = 255 - gray_img  
blurred = cv2.GaussianBlur(inv_gray, (21, 21), 0)  
sketch = cv2.divide(gray_img, 255 - blurred, scale=256)  

# Save the filtered images  
cv2.imwrite("Dhakshu_CLAHE.jpg", clahe_img)  
cv2.imwrite("Dhakshu_GaussianBlur.jpg", gaussian_blur)  
cv2.imwrite("Dhakshu_EdgeDetection.jpg", edges)  
cv2.imwrite("Dhakshu_SketchEffect.jpg", sketch)  

print("✅ All filters applied and saved successfully!")