Testing with

import timeit
from PIL import Image
im = Image.open('Tests/images/iss634.webp')

def decode():
  im._decoder.reset()
  for i in range(im.n_frames):
    im._decoder.get_next()

print(timeit.timeit(decode, number=1000))

I find it hard to say that this is definitively faster than main.

Hi, I don't expect it to be faster than main in a single-threaded context – the point of releasing the GIL is to allow multiple threads to call get_next() concurrently (i.e. on different images).

I think you'll want a test with code like

import concurrent
import timeit
from PIL import Image
images = [Image.open('Tests/images/iss634.webp') for _ in range(100)]

def decode(im):
  im._decoder.reset()
  for i in range(im.n_frames):
    im._decoder.get_next()

with concurrent.futures.ThreadPoolExecutor(max_workers=5) as pool:
  pool.map(decode, images)

(untested but hopefully you get the idea)

You're right, that test code does demonstrate a substantial speed increase.

Updated w/ your code suggestion... I think you will have to re-approve the workflow run

Please could you post a summary of the speed increase?

And let's include this in the release notes.

I've pushed a commit with release notes, based on https://pillow.readthedocs.io/en/stable/releasenotes/9.3.0.html#release-gil-when-converting-images-using-matrix-operations