converts a jpeg file with a planet on black background to a transparent png

planet2png.py

#!/usr/bin/python3

# converts a jpeg file with a planet on black background to a transparent png
# like this imagemagick function does:
# for i in planet_*.jpg; do   nr=$(echo ${i/planet_/}|sed s/.jpg//g|xargs);   convert $i -fuzz 1% -transparent black trans/planet_${nr}.png; done
# but the python script will create them without arkifacts

# needs
# sudo apt install python3-opencv python3-sklearn python3-skimage

# make sure, you created the subfolders thresh/, circle/, mask/, transparent/ and crop/
# mkdir thresh circle mask transparent crop

# call with 
# for i in planet_*.jpg; do   nr=$(echo ${i/planet_/}|sed s/.jpg//g|xargs); python planet2png.py -i $i -o planet_${nr}.png; done


import cv2
import numpy as np
import sys, getopt
import skimage.exposure

def main(argv):
  inputfile = ''
  outputfile = ''
  try:
    opts, args = getopt.getopt(argv,"hi:o:",["ifile=","ofile="])
  except getopt.GetoptError:
    print ('planet2png.py -i <inputfile> -o <outputfile>')
    sys.exit(2)
  for opt, arg in opts:
    if opt == '-h':
      print ('planet2png.py -i <inputfile> -o <outputfile>')
      sys.exit()
    elif opt in ("-i", "--ifile"):
      inputfile = arg
    elif opt in ("-o", "--ofile"):
      outputfile = arg
  if inputfile == '':
    print ("missing inputfile")
    sys.exit()
  if outputfile == '':
    print ("missing outputfile")
    sys.exit()
  
  print ("crop",inputfile)
  
  # read image
  img = cv2.imread(inputfile)
  h, w, c = img.shape

  # convert to grayscale
  gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

  # threshold
  thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)[1]

  # get contour
  contours = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
  contours = contours[0] if len(contours) == 2 else contours[1]
  big_contour = max(contours, key=cv2.contourArea)

  # get enclosing circle
  center, radius = cv2.minEnclosingCircle(big_contour)
  cx = int(round(center[0]))
  cy = int(round(center[1]))
  rr = int(round(radius))

  # draw outline circle over input
  circle = img.copy()
  cv2.circle(circle, (cx,cy), rr, (0, 0, 255), 1)

  # draw white filled circle on black background as mask
  mask = np.full((h,w), 0, dtype=np.uint8)
  cv2.circle(mask, (cx,cy), rr, 255, -1)
  
  # antialias
  blur = cv2.GaussianBlur(mask, (0,0), sigmaX=1, sigmaY=1, borderType = cv2.BORDER_DEFAULT)
  mask = skimage.exposure.rescale_intensity(blur, in_range=(127,255), out_range=(0,255))

  # put mask into alpha channel to make outside transparent
  imgT = cv2.cvtColor(img, cv2.COLOR_BGR2BGRA)
  imgT[:,:,3] = mask

  # crop the image
  ulx = int(cx-rr+0.5)
  uly = int(cy-rr+0.5)
  brx = int(cx+rr+1)
  bry = int(cy+rr+1)
  print(ulx,brx,uly,bry)
  crop = imgT[uly:bry, ulx:brx]

  # write result to disk
  #cv2.imwrite("thresh/"+outputfile, thresh)
  #cv2.imwrite("circle/"+outputfile, circle)
  #cv2.imwrite("mask/"+outputfile, mask)
  cv2.imwrite("transparent/"+outputfile, imgT)
  cv2.imwrite("crop/"+outputfile, crop)

  # display it
  #cv2.imshow("thresh", thresh)
  #cv2.imshow("circle", circle)
  #cv2.imshow("mask", mask)
  #cv2.waitKey(0)

if __name__ == "__main__":
   main(sys.argv[1:])

Those are all planets, I want to convert: https://framadrop.org/lufi/r/xZyupNVL_p#pf9g8cvzJU4wgFVgJAb9sGdN9V+l+IZZCdEcA/j90hc=

developed here: https://stackoverflow.com/questions/65044104/batch-crop-quad-images-with-diffenrent-sizes-to-a-circle/65053727#65053727