opencv 45 detect and improve low contrast image

original

contrast level 1

contrast level 2

original, contrast level 1 - 5

final enhanced image

#low_contrast.py

from skimage.exposure import is_low_contrast

from imutils.paths import list_images

import argparse

import imutils

import cv2

# construct the argument parser and parse the arguments

ap = argparse.ArgumentParser()

ap.add_argument("-i", "--input", required=True,

                help="path to input directory of images")

ap.add_argument("-t", "--thresh", type=float, default=0.35,

                help="threshold for low contrast")

args = vars(ap.parse_args())

def increase_contrast(image, level):

    lab = cv2.cvtColor(image, cv2.COLOR_BGR2LAB)

    l, a, b = cv2.split(lab)

    clahe = cv2.createCLAHE(clipLimit=0.01 + level, tileGridSize=(8, 8))

    cl = clahe.apply(l)

    limg = cv2.merge((cl, a, b))

    final = cv2.cvtColor(limg, cv2.COLOR_LAB2BGR)

    return final

# grab images from low contrast directory

imagePaths = sorted(list(list_images(args["input"])))

# loop over the image paths

for (i, imagePath) in enumerate(imagePaths):

    # load the input image from disk, resize it, and convert it to

    # grayscale

    print("[INFO] processing image {}/{}".format(i + 1,

                                                 len(imagePaths)))

    image = cv2.imread(imagePath)

    image = imutils.resize(image, width=450)

    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

    constrast_level = 0

    

    while True:

        # update the text and color

        text = "Low contrast: Yes"

        color = (0, 0, 255)

        image_copy = image.copy()

        # draw the text on the output image

        cv2.putText(image_copy, text, (5, 25), cv2.FONT_HERSHEY_SIMPLEX, 0.8,

                    color, 2)

        if constrast_level == 0:

            cv2.imshow("original", image_copy)

        constrast_level += 1

        image_increased_contrast = increase_contrast(image, constrast_level)

        gray = cv2.cvtColor(image_increased_contrast, cv2.COLOR_BGR2GRAY)

        if not is_low_contrast(gray, fraction_threshold=args["thresh"]):

            # is *not* low contrast

            text = "Low contrast: No"

            color = (0, 255, 0)

            # draw the text on the output image

            cv2.putText(image_increased_contrast, text, (5, 25), cv2.FONT_HERSHEY_SIMPLEX, 0.8,

                            color, 2)

            cv2.imshow("contrast level " + str(constrast_level), image_increased_contrast)

            break

        else:

            # draw the text on the output image

            cv2.putText(image_increased_contrast, text, (5, 25), cv2.FONT_HERSHEY_SIMPLEX, 0.8,

                        color, 2)

            cv2.imshow("contrast level " + str(constrast_level), image_increased_contrast)

    cv2.waitKey(0)

---------------------

#logs

(venv) C:\Users\zchen\PycharmProjects\opencv>python low_contrast.py -i assets/low_contrast

[INFO] processing image 1/2

[INFO] processing image 2/2

reference:

https://www.pyimagesearch.com/2021/01/25/detecting-low-contrast-images-with-opencv-scikit-image-and-python/

increase image contrast

https://chuanshuoge2.blogspot.com/2021/03/opencv-12-adjust-contrast.html

pip install skimage, DLL load failed while importing _remap

https://github.com/scikit-image/scikit-image/issues/4780

download & install visual studio 2019

https://visualstudio.microsoft.com/downloads/

In visual studio installer, check python development