Buy Me a Coffee

*Memos:

AugMix() can randomly do AugMix to an image as shown below. *It's about alpha argument (2):

from torchvision.datasets import OxfordIIITPet
from torchvision.transforms.v2 import AugMix
from torchvision.transforms.functional import InterpolationMode

origin_data = OxfordIIITPet(
    root="data",
    transform=None
)

cd50a0_data = OxfordIIITPet( # `cd` is chain_depth and `a` is alpha.
    root="data",
    transform=AugMix(chain_depth=50, alpha=0.0)
)

cd50a1_data = OxfordIIITPet(
    root="data",
    transform=AugMix(chain_depth=50, alpha=1.0)
)

cd50a2_data = OxfordIIITPet(
    root="data",
    transform=AugMix(chain_depth=50, alpha=2.0)
)

cd50a5_data = OxfordIIITPet(
    root="data",
    transform=AugMix(chain_depth=50, alpha=5.0)
)

cd50a10_data = OxfordIIITPet(
    root="data",
    transform=AugMix(chain_depth=50, alpha=10.0)
)

cd50a25_data = OxfordIIITPet(
    root="data",
    transform=AugMix(chain_depth=50, alpha=25.0)
)

cd50a50_data = OxfordIIITPet(
    root="data",
    transform=AugMix(chain_depth=50, alpha=50.0)
)

s10mw50cd50a0_data = OxfordIIITPet( # `s` is severity.
    root="data",                    # `mw` is mixture_width.
    transform=AugMix(severity=10, mixture_width=50, chain_depth=50, alpha=0.0)
)

s10mw50cd50a1_data = OxfordIIITPet(
    root="data",
    transform=AugMix(severity=10, mixture_width=50, chain_depth=50, alpha=1.0)
)

s10mw50cd50a2_data = OxfordIIITPet(
    root="data",
    transform=AugMix(severity=10, mixture_width=50, chain_depth=50, alpha=2.0)
)

s10mw50cd50a5_data = OxfordIIITPet(
    root="data",
    transform=AugMix(severity=10, mixture_width=50, chain_depth=50, alpha=5.0)
)

s10mw50cd50a10_data = OxfordIIITPet(
    root="data",
    transform=AugMix(severity=10, mixture_width=50, chain_depth=50, alpha=10.0)
)

s10mw50cd50a25_data = OxfordIIITPet(
    root="data",
    transform=AugMix(severity=10, mixture_width=50, chain_depth=50, alpha=25.0)
)

s10mw50cd50a50_data = OxfordIIITPet(
    root="data",
    transform=AugMix(severity=10, mixture_width=50, chain_depth=50, alpha=50.0)
)

s1mw0cd0a0_data = OxfordIIITPet(
    root="data", 
    transform=AugMix(severity=1, mixture_width=0, chain_depth=0, alpha=0.0)
)

s1mw0cd0a1_data = OxfordIIITPet(
    root="data",
    transform=AugMix(severity=1, mixture_width=0, chain_depth=0, alpha=1.0)
)

s1mw0cd0a2_data = OxfordIIITPet(
    root="data",
    transform=AugMix(severity=1, mixture_width=0, chain_depth=0, alpha=2.0)
)

s1mw0cd0a5_data = OxfordIIITPet(
    root="data",
    transform=AugMix(severity=1, mixture_width=0, chain_depth=0, alpha=5.0)
)

s1mw0cd0a10_data = OxfordIIITPet(
    root="data",
    transform=AugMix(severity=1, mixture_width=0, chain_depth=0, alpha=10.0)
)

s1mw0cd0a25_data = OxfordIIITPet(
    root="data",
    transform=AugMix(severity=1, mixture_width=0, chain_depth=0, alpha=25.0)
)

s1mw0cd0a50_data = OxfordIIITPet(
    root="data",
    transform=AugMix(severity=1, mixture_width=0, chain_depth=0, alpha=50.0)
)

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=cd50a0_data, main_title="cd50a0_data")
show_images1(data=cd50a1_data, main_title="cd50a1_data")
show_images1(data=cd50a2_data, main_title="cd50a2_data")
show_images1(data=cd50a5_data, main_title="cd50a5_data")
show_images1(data=cd50a10_data, main_title="cd50a10_data")
show_images1(data=cd50a25_data, main_title="cd50a25_data")
show_images1(data=cd50a50_data, main_title="cd50a50_data")
print()
show_images1(data=s10mw50cd50a0_data, main_title="s10mw50cd50a0_data")
show_images1(data=s10mw50cd50a1_data, main_title="s10mw50cd50a1_data")
show_images1(data=s10mw50cd50a2_data, main_title="s10mw50cd50a2_data")
show_images1(data=s10mw50cd50a5_data, main_title="s10mw50cd50a5_data")
show_images1(data=s10mw50cd50a10_data, main_title="s10mw50cd50a10_data")
show_images1(data=s10mw50cd50a25_data, main_title="s10mw50cd50a25_data")
show_images1(data=s10mw50cd50a50_data, main_title="s10mw50cd50a50_data")
print()
show_images1(data=s1mw0cd0a0_data, main_title="s1mw0cd0a0_data")
show_images1(data=s1mw0cd0a1_data, main_title="s1mw0cd0a1_data")
show_images1(data=s1mw0cd0a2_data, main_title="s1mw0cd0a2_data")
show_images1(data=s1mw0cd0a5_data, main_title="s1mw0cd0a5_data")
show_images1(data=s1mw0cd0a10_data, main_title="s1mw0cd0a10_data")
show_images1(data=s1mw0cd0a25_data, main_title="s1mw0cd0a25_data")
show_images1(data=s1mw0cd0a50_data, main_title="s1mw0cd0a50_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="cd50a0_data", cd=50, a=0.0)
show_images2(data=origin_data, main_title="cd50a1_data", cd=50, a=1.0)
show_images2(data=origin_data, main_title="cd50a2_data", cd=50, a=2.0)
show_images2(data=origin_data, main_title="cd50a5_data", cd=50, a=5.0)
show_images2(data=origin_data, main_title="cd50a10_data", cd=50, a=10.0)
show_images2(data=origin_data, main_title="cd50a25_data", cd=50, a=25.0)
show_images2(data=origin_data, main_title="cd50a50_data", cd=50, a=50.0)
print()
show_images2(data=origin_data, main_title="s10mw50cd50a0_data", s=10, mw=50,
             cd=50, a=0.0)
show_images2(data=origin_data, main_title="s10mw50cd50a1_data", s=10, mw=50,
             cd=50, a=1.0)
show_images2(data=origin_data, main_title="s10mw50cd50a2_data", s=10, mw=50,
             cd=50, a=2.0)
show_images2(data=origin_data, main_title="s10mw50cd50a5_data", s=10, mw=50,
             cd=50, a=5.0)
show_images2(data=origin_data, main_title="s10mw50cd50a10_data", s=10, mw=50,
             cd=50, a=10.0)
show_images2(data=origin_data, main_title="s10mw50cd50a25_data", s=10, mw=50,
             cd=50, a=25.0)
show_images2(data=origin_data, main_title="s10mw50cd50a50_data", s=10, mw=50,
             cd=50, a=50.0)
print()
show_images2(data=origin_data, main_title="s1mw0cd0a0_data", s=1, mw=0, cd=0,
             a=0.0)
show_images2(data=origin_data, main_title="s1mw0cd0a1_data", s=1, mw=0, cd=0,
             a=1.0)
show_images2(data=origin_data, main_title="s1mw0cd0a2_data", s=1, mw=0, cd=0,
             a=2.0)
show_images2(data=origin_data, main_title="s1mw0cd0a5_data", s=1, mw=0, cd=0,
             a=5.0)
show_images2(data=origin_data, main_title="s1mw0cd0a10_data", s=1, mw=0, cd=0,
             a=10.0)
show_images2(data=origin_data, main_title="s1mw0cd0a25_data", s=1, mw=0, cd=0,
             a=25.0)
show_images2(data=origin_data, main_title="s1mw0cd0a50_data", s=1, mw=0, cd=0,
             a=50.0)

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