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L40S
Running
on
L40S
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 | |