add a grayscale gaussian blur to an image and set the blacks to transparent, converting from jpg to png

batchProcessImages.py

import numpy as np
import cv2
import os

# install all the above packages with pip3
# run this by setting the directories and calling fro command line
# python3 processImages.py

IMAGEFOLDER = '/Users/anthonyaragues/Downloads/in/'
OUTPUTFOLDER = '/Users/anthonyaragues/Downloads/out/'


def noisy(image, sigma=0.005):
    row, col, ch = image.shape
    gauss = sigma * np.random.randn(row, col, ch)
    gauss = gauss.reshape(row, col, ch)
    noisy = image + image * gauss
    return noisy


def turnGray(image):
    # Convert the image to grayscale
    gray = cv2.cvtColor(np.uint8(image), cv2.COLOR_RGBA2GRAY)
    # Convert the grayscale image back to RGBA format using the alpha channel from the original image
    rgba = cv2.cvtColor(gray, cv2.COLOR_GRAY2RGBA)
    # Copy the alpha channel from the original image to the grayscale image
    rgba[:, :, 3] = image[:, :, 3]
    return rgba


def convertImage(strFile, strOut):
    img = cv2.imread(strFile)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    # Create a mask of the image where black pixels are transparent
    mask = cv2.threshold(gray, 20, 255, cv2.THRESH_BINARY_INV)[1]
    # Invert the mask so that black pixels are transparent
    mask = cv2.bitwise_not(mask)
    # Create a 4-channel image with transparency
    rgba = cv2.cvtColor(img, cv2.COLOR_BGR2RGBA)
    rgba = noisy(rgba)
    # Set the alpha channel of the image using the mask
    rgba[:, :, 3] = mask
    rgba = turnGray(rgba)
    cv2.imwrite(strOut, rgba)


for strFile in [file for file in os.listdir(IMAGEFOLDER)]:
    if '.jpg' in strFile:
        strOut = strFile.replace('.jpg', '.png')
        convertImage(f'{IMAGEFOLDER}{strFile}', f'{OUTPUTFOLDER}{strOut}')