Goal:
I am trying to batch process images contained inside a folder to resize and optimize them for use online.
Problem:
The following script works, but I have to run it twice before I get the output I want. This is how I would expect it to work:
function 1: resize_aspect_fit()
Resizes each image in the target folder to a specific size, adds "_small.png" to the file name, and saves it as a new file in the subfolder "optimized_images", created in the same directory as the original group of images.
function2: png_conversion()
Takes the newly made images inside "optimized_images" ("_small.png") and applies a conversion that reduces the size of the original file, adding the "-opt.png" suffix to indicate it has been optimized.
function3: unoptimized_cleanup()
Takes the files built by function 1, which are no longer necessary (since they have been optimized) and deletes them, to reduce clutter.
When I run the script I get the expected response from function1, all files in the target file are resized appropriately and saved in the "optimized_images" folder. But I have to run the script a second time before function 2 and 3 take effect. It does work, but I have never encountered an issue like this before. Any idea why this is happening?
What I tried:
I thought this might be related to file open/close operations, but I think I am closing them all at the appropriate time. I swapped Image.open syntax to use "with Image.open(path) as image:" but that did not solve the problem.
I thought there might be some issue with os.listdir or os.path where it might have to be 'reset' in order to iterate through a directory of files twice, but I cannot find anything.
from PIL import Image
import os, sys
path = "../path/to/images/"
new_folder = '/optimized_images/'
optimized_path = path + new_folder[1:]
dirs = os.listdir( path )
optimized_dirs = os.listdir( optimized_path )
def resize_aspect_fit(final_size=250, dirs=dirs, optimized_path=optimized_path, optimized_dirs=optimized_dirs):
for item in dirs:
if item == '.DS_Store':
continue
if os.path.isfile(path+item):
with Image.open(path+item) as im:
f, e = os.path.splitext(path+item)
size = im.size
ratio = float(final_size) / max(size)
new_image_size = tuple([int(x*ratio) for x in size])
im = im.resize(new_image_size, Image.ANTIALIAS)
new_im = Image.new("RGBA", (final_size, final_size), color=(255,255,255,0))
new_im.paste(im, ((final_size-new_image_size[0])//2, (final_size-new_image_size[1])//2))
new_path, new_filename = f.rsplit('/', 1)
new_im.save(new_path + new_folder + new_filename + '_small.png', 'PNG', quality=10, optimize=True)
new_im.close()
def png_conversion(optimized_dirs=optimized_dirs, optimized_path=optimized_path):
for item in optimized_dirs:
if item == '.DS_Store':
continue
f, e = os.path.splitext(optimized_path+item)
with Image.open(f + e) as im:
im.load()
# Get the alpha band
alpha = im.split()[-1]
im = im.convert('RGB').convert('P', palette=Image.ADAPTIVE, colors=255)
# Set all pixel values below 128 to 255,
# and the rest to 0
mask = Image.eval(alpha, lambda a: 255 if a <=128 else 0)
# Paste the color of index 255 and use alpha as a mask
im.paste(255, mask)
# The transparency index is 255
e = e.split('.png')[0]
im.save(f + e + "-opt.png", transparency=255)
im.close()
def unoptimized_cleanup(optimized_dirs=optimized_dirs, optimized_path=optimized_path):
for item in optimized_dirs:
if item.endswith('small.png'):
os.remove(os.path.join(optimized_path, item))
#functions called in order
resize_aspect_fit(final_size=250, dirs=dirs)
png_conversion(optimized_dirs=optimized_dirs, optimized_path=optimized_path)
unoptimized_cleanup(optimized_dirs=optimized_dirs, optimized_path=optimized_path)
I expect that for the following folder structure:
folder/image1.png
folder/image2.png
the output should look like this, with the appropriately sized and smaller files:
folder/optimized_images/image1_small-opt.png
folder/optimized_images/image2_small-opt.png
Relevant Sources that I pulled from:
Converting PNG32 to PNG8 with PIL while preserving transparency
Python/PIL Resize all images in a folder