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thanks for your excellent job! it seems that the training is very slow when i use the straug(6x times slower than that without straug). What about the real speed when you test? The following is my aug-code.
class RecStraugRandAug(object):
def __init__(self, num_aug=2, prob=0.5, **kwargs):
super().__init__()
self.num_aug = num_aug
self.prob = prob
try:
from straug.blur import GaussianBlur, DefocusBlur, MotionBlur, GlassBlur
from straug.camera import Contrast, Brightness, JpegCompression, Pixelate
from straug.geometry import Perspective, Shrink, Rotate
from straug.noise import GaussianNoise, ShotNoise, ImpulseNoise, SpeckleNoise
from straug.pattern import Grid, VGrid, HGrid, RectGrid, EllipseGrid
from straug.process import Posterize, Solarize, Invert, Equalize, AutoContrast, Sharpness, Color
from straug.warp import Stretch, Distort, Curve
from straug.weather import Fog, Snow, Frost, Rain, Shadow
self.augs = [
[GaussianBlur(), DefocusBlur(), MotionBlur(), GlassBlur()],
[Contrast(), Brightness(), JpegCompression(), Pixelate()],
[Perspective(), Shrink(), Rotate()],
[GaussianNoise(), ShotNoise(), ImpulseNoise(), SpeckleNoise()],
[Grid(), VGrid(), HGrid(), RectGrid(), EllipseGrid()],
[Posterize(), Solarize(), Invert(), Equalize(), AutoContrast(), Sharpness(), Color()],
[Stretch(), Distort(), Curve()],
[Fog(), Snow(), Frost(), Rain(), Shadow()],
]
except Exception as ex:
print(f"exception: {ex}, you can install straug using `pip install straug`")
exit(-1)
def __call__(self, data):
img = Image.fromarray(data["image"])
for idx in range(self.num_aug):
aug_type_idx = np.random.randint(0, len(self.augs))
aug_idx = np.random.randint(0, len(self.augs[aug_type_idx]))
img = self.augs[aug_type_idx][aug_idx](img, mag=random.randint(-1,2), prob=self.prob)
data["image"] = np.array(img)
return dataMetadata
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