import os, glob, sys
import numpy as np
import cv2
import matplotlib.pyplot as plt
import skimage.filters as filters
import seaborn as sns

def brightness_and_contrast_adjustment(image, alpha=1.999, beta=-30):
    image = alpha * image + beta
    image = np.clip(image, 0, 255)
    return image.astype(np.uint8)

def gamma_correction(image, gamma=2.2):
    image = ((image/255)**(1/gamma)) * 255
    return image.astype(np.uint8)

clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))
def preprocess_image(image):
    image = brightness_and_contrast_adjustment(image)
    kernel = np.ones((2, 2),np.uint8)
    image = cv2.erode(image, kernel, iterations=1)
    image = clahe.apply(image)
    return image.astype(np.uint8)

paths = glob.glob("sample/*.jpg")
n_images = 5
fig, ax = plt.subplots(n_images, 2, figsize=(30, 10*n_images))
for i, path in enumerate(paths):
    image = cv2.imread(path)
    image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    preprocessed_image = preprocess_image(image)
    ax[i, 0].imshow(image, cmap="gray")
    ax[i, 1].imshow(preprocessed_image, cmap="gray")
    if i == n_images-1:
        break
plt.show()