*Memos:
-
My post explains AugMix() about no arguments and
full
argument. -
My post explains AugMix() about
severity
argument (2).
AugMix() can randomly do AugMix to an image as shown below. *It's about severity
argument (1):
from torchvision.datasets import OxfordIIITPet
from torchvision.transforms.v2 import AugMix
from torchvision.transforms.functional import InterpolationMode
origin_data = OxfordIIITPet(
root="data",
transform=None
)
s1_data = OxfordIIITPet( # `s` is severity.
root="data",
transform=AugMix(severity=1)
)
s2_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=2)
)
s3_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=3)
)
s4_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=4)
)
s5_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=5)
)
s6_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=6)
)
s7_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=7)
)
s8_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=8)
)
s9_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=9)
)
s10_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=10)
)
s1mw50_data = OxfordIIITPet( # `mw` is mixture_width.
root="data",
transform=AugMix(severity=1, mixture_width=50)
)
s2mw50_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=2, mixture_width=50)
)
s3mw50_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=3, mixture_width=50)
)
s4mw50_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=4, mixture_width=50)
)
s5mw50_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=5, mixture_width=50)
)
s6mw50_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=6, mixture_width=50)
)
s7mw50_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=7, mixture_width=50)
)
s8mw50_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=8, mixture_width=50)
)
s9mw50_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=9, mixture_width=50)
)
s10mw50_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=10, mixture_width=50)
)
s1cd50_data = OxfordIIITPet( # `cd` is chain_depth.
root="data",
transform=AugMix(severity=1, chain_depth=50)
)
s2cd50_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=2, chain_depth=50)
)
s3cd50_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=3, chain_depth=50)
)
s4cd50_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=4, chain_depth=50)
)
s5cd50_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=5, chain_depth=50)
)
s6cd50_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=6, chain_depth=50)
)
s7cd50_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=7, chain_depth=50)
)
s8cd50_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=8, chain_depth=50)
)
s9cd50_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=9, chain_depth=50)
)
s10cd50_data = OxfordIIITPet(
root="data",
transform=AugMix(severity=10, chain_depth=50)
)
import matplotlib.pyplot as plt
def show_images1(data, main_title=None):
plt.figure(figsize=[10, 5])
plt.suptitle(t=main_title, y=0.8, fontsize=14)
for i, (im, _) in zip(range(1, 6), data):
plt.subplot(1, 5, i)
plt.imshow(X=im)
plt.xticks(ticks=[])
plt.yticks(ticks=[])
plt.tight_layout()
plt.show()
show_images1(data=origin_data, main_title="origin_data")
print()
show_images1(data=s1_data, main_title="s1_data")
show_images1(data=s2_data, main_title="s2_data")
show_images1(data=s3_data, main_title="s3_data")
show_images1(data=s4_data, main_title="s4_data")
show_images1(data=s5_data, main_title="s5_data")
show_images1(data=s6_data, main_title="s6_data")
show_images1(data=s7_data, main_title="s7_data")
show_images1(data=s8_data, main_title="s8_data")
show_images1(data=s9_data, main_title="s9_data")
show_images1(data=s10_data, main_title="s10_data")
print()
show_images1(data=s1mw50_data, main_title="s1mw50_data")
show_images1(data=s2mw50_data, main_title="s2mw50_data")
show_images1(data=s3mw50_data, main_title="s3mw50_data")
show_images1(data=s4mw50_data, main_title="s4mw50_data")
show_images1(data=s5mw50_data, main_title="s5mw50_data")
show_images1(data=s6mw50_data, main_title="s6mw50_data")
show_images1(data=s7mw50_data, main_title="s7mw50_data")
show_images1(data=s8mw50_data, main_title="s8mw50_data")
show_images1(data=s9mw50_data, main_title="s9mw50_data")
show_images1(data=s10mw50_data, main_title="s10mw50_data")
print()
show_images1(data=s1cd50_data, main_title="s1cd50_data")
show_images1(data=s2cd50_data, main_title="s2cd50_data")
show_images1(data=s3cd50_data, main_title="s3cd50_data")
show_images1(data=s4cd50_data, main_title="s4cd50_data")
show_images1(data=s5cd50_data, main_title="s5cd50_data")
show_images1(data=s6cd50_data, main_title="s6cd50_data")
show_images1(data=s7cd50_data, main_title="s7cd50_data")
show_images1(data=s8cd50_data, main_title="s8cd50_data")
show_images1(data=s9cd50_data, main_title="s9cd50_data")
show_images1(data=s10cd50_data, main_title="s10cd50_data")
# ↓ ↓ ↓ ↓ ↓ ↓ The code below is identical to the code above. ↓ ↓ ↓ ↓ ↓ ↓
def show_images2(data, main_title=None, s=3, mw=3, cd=-1, a=1.0,
ao=True, ip=InterpolationMode.BILINEAR, f=None):
plt.figure(figsize=[10, 5])
plt.suptitle(t=main_title, y=0.8, fontsize=14)
if main_title != "origin_data":
for i, (im, _) in zip(range(1, 6), data):
plt.subplot(1, 5, i)
am = AugMix(severity=s, mixture_width=mw, chain_depth=cd,
alpha=a, all_ops=ao, interpolation=ip, fill=f)
plt.imshow(X=am(im))
plt.xticks(ticks=[])
plt.yticks(ticks=[])
else:
for i, (im, _) in zip(range(1, 6), data):
plt.subplot(1, 5, i)
plt.imshow(X=im)
plt.xticks(ticks=[])
plt.yticks(ticks=[])
plt.tight_layout()
plt.show()
show_images2(data=origin_data, main_title="origin_data")
print()
show_images2(data=origin_data, main_title="s1_data", s=1)
show_images2(data=origin_data, main_title="s2_data", s=2)
show_images2(data=origin_data, main_title="s3_data", s=3)
show_images2(data=origin_data, main_title="s4_data", s=4)
show_images2(data=origin_data, main_title="s5_data", s=5)
show_images2(data=origin_data, main_title="s6_data", s=6)
show_images2(data=origin_data, main_title="s7_data", s=7)
show_images2(data=origin_data, main_title="s8_data", s=8)
show_images2(data=origin_data, main_title="s9_data", s=9)
show_images2(data=origin_data, main_title="s10_data", s=10)
print()
show_images2(data=origin_data, main_title="s1mw50_data", s=1, mw=50)
show_images2(data=origin_data, main_title="s2mw50_data", s=2, mw=50)
show_images2(data=origin_data, main_title="s3mw50_data", s=3, mw=50)
show_images2(data=origin_data, main_title="s4mw50_data", s=4, mw=50)
show_images2(data=origin_data, main_title="s5mw50_data", s=5, mw=50)
show_images2(data=origin_data, main_title="s6mw50_data", s=6, mw=50)
show_images2(data=origin_data, main_title="s7mw50_data", s=7, mw=50)
show_images2(data=origin_data, main_title="s8mw50_data", s=8, mw=50)
show_images2(data=origin_data, main_title="s9mw50_data", s=9, mw=50)
show_images2(data=origin_data, main_title="s10mw50_data", s=10, mw=50)
print()
show_images2(data=origin_data, main_title="s1cd50_data", s=1, cd=50)
show_images2(data=origin_data, main_title="s2cd50_data", s=2, cd=50)
show_images2(data=origin_data, main_title="s3cd50_data", s=3, cd=50)
show_images2(data=origin_data, main_title="s4cd50_data", s=4, cd=50)
show_images2(data=origin_data, main_title="s5cd50_data", s=5, cd=50)
show_images2(data=origin_data, main_title="s6cd50_data", s=6, cd=50)
show_images2(data=origin_data, main_title="s7cd50_data", s=7, cd=50)
show_images2(data=origin_data, main_title="s8cd50_data", s=8, cd=50)
show_images2(data=origin_data, main_title="s9cd50_data", s=9, cd=50)
show_images2(data=origin_data, main_title="s10cd50_data", s=10, cd=50)
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