AugMix in PyTorch (5)

Buy Me a Coffee☕ Memos: My post explains AugMix() about no arguments and full argument. My post explains AugMix() about severity argument (1). My post explains AugMix() about severity argument (2). My post explains AugMix() about mixture_width argument (1). AugMix() can randomly do AugMix to an image as shown below. It's about mixture_width 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 ) mw0a50_data = OxfordIIITPet( # `mw` is mixture_width and `a` is alpha. root="data", transform=AugMix(mixture_width=0, alpha=50.0) ) mw1a50_data = OxfordIIITPet( root="data", transform=AugMix(mixture_width=1, alpha=50.0) ) mw2a50_data = OxfordIIITPet( root="data", transform=AugMix(mixture_width=2, alpha=50.0) ) mw5a50_data = OxfordIIITPet( root="data", transform=AugMix(mixture_width=5, alpha=50.0) ) mw10a50_data = OxfordIIITPet( root="data", transform=AugMix(mixture_width=10, alpha=50.0) ) mw25a50_data = OxfordIIITPet( root="data", transform=AugMix(mixture_width=25, alpha=50.0) ) mw50a50_data = OxfordIIITPet( root="data", transform=AugMix(mixture_width=50, alpha=50.0) ) s10mw0cd50a50_data = OxfordIIITPet( # `s` is severity and `cd` is chain_depth. root="data", transform=AugMix(severity=10, mixture_width=0, chain_depth=50, alpha=50.0) ) s10mw1cd50a50_data = OxfordIIITPet( root="data", transform=AugMix(severity=10, mixture_width=1, chain_depth=50, alpha=50.0) ) s10mw2cd50a50_data = OxfordIIITPet( root="data", transform=AugMix(severity=10, mixture_width=2, chain_depth=50, alpha=50.0) ) s10mw5cd50a50_data = OxfordIIITPet( root="data", transform=AugMix(severity=10, mixture_width=5, chain_depth=50, alpha=50.0) ) s10mw10cd50a50_data = OxfordIIITPet( root="data", transform=AugMix(severity=10, mixture_width=10, chain_depth=50, alpha=50.0) ) s10mw25cd50a50_data = OxfordIIITPet( root="data", transform=AugMix(severity=10, mixture_width=25, chain_depth=50, alpha=50.0) ) s10mw50cd50a50_data = OxfordIIITPet( root="data", transform=AugMix(severity=10, mixture_width=50, chain_depth=50, 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=mw0a50_data, main_title="mw0a50_data") show_images1(data=mw1a50_data, main_title="mw1a50_data") show_images1(data=mw2a50_data, main_title="mw2a50_data") show_images1(data=mw5a50_data, main_title="mw5a50_data") show_images1(data=mw10a50_data, main_title="mw10a50_data") show_images1(data=mw25a50_data, main_title="mw25a50_data") show_images1(data=mw50a50_data, main_title="mw50a50_data") print() show_images1(data=s10mw0cd50a50_data, main_title="s10mw0cd50a50_data") show_images1(data=s10mw1cd50a50_data, main_title="s10mw1cd50a50_data") show_images1(data=s10mw2cd50a50_data, main_title="s10mw2cd50a50_data") show_images1(data=s10mw5cd50a50_data, main_title="s10mw5cd50a50_data") show_images1(data=s10mw10cd50a50_data, main_title="s10mw10cd50a50_data") show_images1(data=s10mw25cd50a50_data, main_title="s10mw25cd50a50_data") show_images1(data=s10mw50cd50a50_data, main_title="s10mw50cd50a50_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="mw0a50_data", mw=0, a=50.0) show_images2(data=origin_data, main_title="mw1a50_data", mw=1, a=50.0) show_images2(data=origin_data, main_title="mw2a50_data", mw=2, a=50.0) show_images2(data=origin_data, main_title="mw5a50_data", mw=5, a=50.0) show_images2(data=origin_data, main_title="mw10a50_data", mw=10, a=50.0) show_images2(data=origin_data, main_ti

Mar 22, 2025 - 01:38

*Memos:

My post explains AugMix() about no arguments and full argument.
My post explains AugMix() about severity argument (1).
My post explains AugMix() about severity argument (2).
My post explains AugMix() about mixture_width argument (1).

AugMix() can randomly do AugMix to an image as shown below. *It's about mixture_width 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
)

mw0a50_data = OxfordIIITPet( # `mw` is mixture_width and `a` is alpha.
    root="data",
    transform=AugMix(mixture_width=0, alpha=50.0)
)

mw1a50_data = OxfordIIITPet(
    root="data",
    transform=AugMix(mixture_width=1, alpha=50.0)
)

mw2a50_data = OxfordIIITPet(
    root="data",
    transform=AugMix(mixture_width=2, alpha=50.0)
)

mw5a50_data = OxfordIIITPet(
    root="data",
    transform=AugMix(mixture_width=5, alpha=50.0)
)

mw10a50_data = OxfordIIITPet(
    root="data",
    transform=AugMix(mixture_width=10, alpha=50.0)
)

mw25a50_data = OxfordIIITPet(
    root="data",
    transform=AugMix(mixture_width=25, alpha=50.0)
)

mw50a50_data = OxfordIIITPet(
    root="data",
    transform=AugMix(mixture_width=50, alpha=50.0)
)

s10mw0cd50a50_data = OxfordIIITPet( # `s` is severity and `cd` is chain_depth.
    root="data",
    transform=AugMix(severity=10, mixture_width=0, chain_depth=50, alpha=50.0)
)

s10mw1cd50a50_data = OxfordIIITPet(
    root="data",
    transform=AugMix(severity=10, mixture_width=1, chain_depth=50, alpha=50.0)
)

s10mw2cd50a50_data = OxfordIIITPet(
    root="data",
    transform=AugMix(severity=10, mixture_width=2, chain_depth=50, alpha=50.0)
)

s10mw5cd50a50_data = OxfordIIITPet(
    root="data",
    transform=AugMix(severity=10, mixture_width=5, chain_depth=50, alpha=50.0)
)

s10mw10cd50a50_data = OxfordIIITPet(
    root="data",
    transform=AugMix(severity=10, mixture_width=10, chain_depth=50, alpha=50.0)
)

s10mw25cd50a50_data = OxfordIIITPet(
    root="data",
    transform=AugMix(severity=10, mixture_width=25, chain_depth=50, alpha=50.0)
)

s10mw50cd50a50_data = OxfordIIITPet(
    root="data",
    transform=AugMix(severity=10, mixture_width=50, chain_depth=50, 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=mw0a50_data, main_title="mw0a50_data")
show_images1(data=mw1a50_data, main_title="mw1a50_data")
show_images1(data=mw2a50_data, main_title="mw2a50_data")
show_images1(data=mw5a50_data, main_title="mw5a50_data")
show_images1(data=mw10a50_data, main_title="mw10a50_data")
show_images1(data=mw25a50_data, main_title="mw25a50_data")
show_images1(data=mw50a50_data, main_title="mw50a50_data")
print()
show_images1(data=s10mw0cd50a50_data, main_title="s10mw0cd50a50_data")
show_images1(data=s10mw1cd50a50_data, main_title="s10mw1cd50a50_data")
show_images1(data=s10mw2cd50a50_data, main_title="s10mw2cd50a50_data")
show_images1(data=s10mw5cd50a50_data, main_title="s10mw5cd50a50_data")
show_images1(data=s10mw10cd50a50_data, main_title="s10mw10cd50a50_data")
show_images1(data=s10mw25cd50a50_data, main_title="s10mw25cd50a50_data")
show_images1(data=s10mw50cd50a50_data, main_title="s10mw50cd50a50_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="mw0a50_data", mw=0, a=50.0)
show_images2(data=origin_data, main_title="mw1a50_data", mw=1, a=50.0)
show_images2(data=origin_data, main_title="mw2a50_data", mw=2, a=50.0)
show_images2(data=origin_data, main_title="mw5a50_data", mw=5, a=50.0)
show_images2(data=origin_data, main_title="mw10a50_data", mw=10, a=50.0)
show_images2(data=origin_data, main_title="mw25a50_data", mw=25, a=50.0)
show_images2(data=origin_data, main_title="mw50a50_data", mw=50, a=50.0)
print()
show_images2(data=origin_data, main_title="s10mw0cd50a50_data", s=10, mw=0,
             cd=50, a=50.0)
show_images2(data=origin_data, main_title="s10mw1cd50a50_data", s=10, mw=1,
             cd=50, a=50.0)
show_images2(data=origin_data, main_title="s10mw2cd50a50_data", s=10, mw=2,
             cd=50, a=50.0)
show_images2(data=origin_data, main_title="s10mw5cd50a50_data", s=10, mw=5,
             cd=50, a=50.0)
show_images2(data=origin_data, main_title="s10mw10cd50a50_data", s=10, mw=10,
             cd=50, a=50.0)
show_images2(data=origin_data, main_title="s10mw25cd50a50_data", s=10, mw=25,
             cd=50, a=50.0)
show_images2(data=origin_data, main_title="s10mw50cd50a50_data", s=10, mw=50,
             cd=50, a=50.0)