import cv2
import numpy as np
import matplotlib.pyplot as plt

# Load the image in grayscale
image_path = "dark.tif"
img = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)

# Check if the image is loaded correctly
if img is None:
    print("Error: Image not loaded. Please check the file path.")
else:
    # Apply Histogram Equalization
    equalized_img = cv2.equalizeHist(img)

    # Compute histograms
    hist_original = cv2.calcHist([img], [0], None, [256], [0, 256])
    hist_equalized = cv2.calcHist([equalized_img], [0], None, [256], [0, 256])

    # Flatten the histograms for plotting
    hist_original = hist_original.flatten()
    hist_equalized = hist_equalized.flatten()

    # Display images and histograms
    plt.figure(figsize=(10, 5))

    # Original Image
    plt.subplot(2, 2, 1)
    plt.imshow(img, cmap='gray')
    plt.title("Original Image")
    plt.axis('off')

    # Histogram of Original Image
    plt.subplot(2, 2, 2)
    plt.plot(hist_original, color='black')
    plt.title("Histogram of Original Image")
    plt.xlim(0, 256)  # Ensure x-axis is from 0 to 255

    # Equalized Image
    plt.subplot(2, 2, 3)
    plt.imshow(equalized_img, cmap='gray')
    plt.title("Equalized Image")
    plt.axis('off')

    # Histogram of Equalized Image
    plt.subplot(2, 2, 4)
    plt.plot(hist_equalized, color='black')
    plt.title("Histogram of Equalized Image")
    plt.xlim(0, 256)  # Ensure x-axis is from 0 to 255

    plt.tight_layout()
    plt.show()