Delete tests/test_utils.py

tests/test_utils.py

@@ -1,43 +0,0 @@
-import cv2
-from facexlib.utils.face_restoration_helper import FaceRestoreHelper
-
-from gfpgan.archs.gfpganv1_arch import GFPGANv1
-from gfpgan.archs.gfpganv1_clean_arch import GFPGANv1Clean
-from gfpgan.utils import GFPGANer
-
-
-def test_gfpganer():
-    # initialize with the clean model
-    restorer = GFPGANer(
-        model_path='experiments/pretrained_models/GFPGANCleanv1-NoCE-C2.pth',
-        upscale=2,
-        arch='clean',
-        channel_multiplier=2,
-        bg_upsampler=None)
-    # test attribute
-    assert isinstance(restorer.gfpgan, GFPGANv1Clean)
-    assert isinstance(restorer.face_helper, FaceRestoreHelper)
-
-    # initialize with the original model
-    restorer = GFPGANer(
-        model_path='experiments/pretrained_models/GFPGANv1.pth',
-        upscale=2,
-        arch='original',
-        channel_multiplier=1,
-        bg_upsampler=None)
-    # test attribute
-    assert isinstance(restorer.gfpgan, GFPGANv1)
-    assert isinstance(restorer.face_helper, FaceRestoreHelper)
-
-    # ------------------ test enhance ---------------- #
-    img = cv2.imread('tests/data/gt/00000000.png', cv2.IMREAD_COLOR)
-    result = restorer.enhance(img, has_aligned=False, paste_back=True)
-    assert result[0][0].shape == (512, 512, 3)
-    assert result[1][0].shape == (512, 512, 3)
-    assert result[2].shape == (1024, 1024, 3)
-
-    # with has_aligned=True
-    result = restorer.enhance(img, has_aligned=True, paste_back=False)
-    assert result[0][0].shape == (512, 512, 3)
-    assert result[1][0].shape == (512, 512, 3)
-    assert result[2] is None