Unify CodeFormer and GFPGAN restoration backends, use Spandrel for GFPGAN

test/test_face_restorers.py

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+import os
+from test.conftest import test_files_path, test_outputs_path
+
+import numpy as np
+import pytest
+from PIL import Image
+
+
+@pytest.mark.usefixtures("initialize")
+@pytest.mark.parametrize("restorer_name", ["gfpgan", "codeformer"])
+def test_face_restorers(restorer_name):
+    from modules import shared
+
+    if restorer_name == "gfpgan":
+        from modules import gfpgan_model
+        gfpgan_model.setup_model(shared.cmd_opts.gfpgan_models_path)
+        restorer = gfpgan_model.gfpgan_fix_faces
+    elif restorer_name == "codeformer":
+        from modules import codeformer_model
+        codeformer_model.setup_model(shared.cmd_opts.codeformer_models_path)
+        restorer = codeformer_model.codeformer.restore
+    else:
+        raise NotImplementedError("...")
+    img = Image.open(os.path.join(test_files_path, "two-faces.jpg"))
+    np_img = np.array(img, dtype=np.uint8)
+    fixed_image = restorer(np_img)
+    assert fixed_image.shape == np_img.shape
+    assert not np.allclose(fixed_image, np_img)  # should have visibly changed
+    Image.fromarray(fixed_image).save(os.path.join(test_outputs_path, f"{restorer_name}.png"))