def __init__(self, labelfile, imagesdir, mean, std, width=800, height=800):
self.width = width
self.height = height
self.items = common.load_webface(labelfile, imagesdir)
self.mean = mean
self.std = std
# create logger
trial_name = "small-H-dense-wide64-UCBA"
jobdir = f"jobs/{trial_name}"
log = logger.create(trial_name, f"{jobdir}/logs/eval.log")
# load and init model
model = DBFace(has_landmark=True, wide=64, has_ext=True, upmode="UCBA")
model.load(f"{jobdir}/models/150.pth")
model.eval()
model.cuda()
# load dataset
mean = [0.408, 0.447, 0.47]
std = [0.289, 0.274, 0.278]
files, anns = zip(
*common.load_webface("webface/val/label.txt", "webface/WIDER_val/images"))
# forward and summary
prefix = "webface/WIDER_val/images/"
all_result_dict = {}
total_file = len(files)
for i in range(total_file):
# preper key and file_name
file = files[i]
key = file[len(prefix):file.rfind("/")]
file_name = common.file_name_no_suffix(file)
# load image and forward
image = common.imread(file)