*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). - My post explains AugMix() about
mixture_width
argument (2). - My post explains AugMix() about
chain_depth
argument (1). - My post explains AugMix() about
chain_depth
argument (2). - My post explains AugMix() about
alpha
argument (1).
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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