Posted on Mar 11 • Edited on May 2

RandomSolarize in PyTorch

#python #pytorch #randomsolarize #v2

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*Memos:

My post explains RandomInvert().
My post explains OxfordIIITPet().

RandomSolarize() can randomly solarize an image with a given probability as shown below:

*Memos:

The 1st argument for initialization is threshold(Required-Type:int or float). *All pixels equal or above this value are inverted.
The 2nd argument for initialization is p(Optional-Default:0.5-Type:int or float): *Memos:
- It's the probability of whether an image is solarized or not.
- It must be 0 <= x <= 1.
The 1st argument is img(Required-Type:PIL Image or tensor(int/float)): *Memos:
- A tensor must be 0D or more D.
- Don't use img=.
v2 is recommended to use according to V1 or V2? Which one should I use?.

from torchvision.datasets import OxfordIIITPet from torchvision.transforms.v2 import RandomSolarize rs = RandomSolarize(threshold=0) rs = RandomSolarize(threshold=0, p=0.5) rs # RandomSolarize(p=0.5, threshold=0)  rs.threshold # 0  rs.p # 0.5  origin_data = OxfordIIITPet( root="data", transform=None ) t300p1_data = OxfordIIITPet( # `t` is threshold.  root="data", transform=RandomSolarize(threshold=300, p=1) ) t256p1_data = OxfordIIITPet( root="data", transform=RandomSolarize(threshold=256, p=1) ) t250p1_data = OxfordIIITPet( root="data", transform=RandomSolarize(threshold=250, p=1) ) t240p1_data = OxfordIIITPet( root="data", transform=RandomSolarize(threshold=240, p=1) ) t220p1_data = OxfordIIITPet( root="data", transform=RandomSolarize(threshold=220, p=1) ) t200p1_data = OxfordIIITPet( root="data", transform=RandomSolarize(threshold=200, p=1) ) t150p1_data = OxfordIIITPet( root="data", transform=RandomSolarize(threshold=150, p=1) ) t100p1_data = OxfordIIITPet( root="data", transform=RandomSolarize(threshold=100, p=1) ) t50p1_data = OxfordIIITPet( root="data", transform=RandomSolarize(threshold=50, p=1) ) t10p1_data = OxfordIIITPet( root="data", transform=RandomSolarize(threshold=10, p=1) ) t0p1_data = OxfordIIITPet( root="data", transform=RandomSolarize(threshold=0, p=1) ) tn10p1_data = OxfordIIITPet( # `n` is negative.  root="data", transform=RandomSolarize(threshold=-10, p=1) ) tn100p1_data = OxfordIIITPet( root="data", transform=RandomSolarize(threshold=-100, p=1) ) t0p0_data = OxfordIIITPet( root="data", transform=RandomSolarize(threshold=0, p=0) ) t0p05_data = OxfordIIITPet( root="data", transform=RandomSolarize(threshold=0, p=0.5) # transform=RandomSolarize(threshold=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=t300p1_data, main_title="t300p1_data") show_images1(data=t256p1_data, main_title="t256p1_data") show_images1(data=t255p1_data, main_title="t255p1_data") show_images1(data=t250p1_data, main_title="t250p1_data") show_images1(data=t240p1_data, main_title="t240p1_data") show_images1(data=t220p1_data, main_title="t220p1_data") show_images1(data=t200p1_data, main_title="t200p1_data") show_images1(data=t150p1_data, main_title="t150p1_data") show_images1(data=t100p1_data, main_title="t100p1_data") show_images1(data=t50p1_data, main_title="t50p1_data") show_images1(data=t10p1_data, main_title="t10p1_data") show_images1(data=t0p1_data, main_title="t0p1_data") show_images1(data=tn10p1_data, main_title="tn10p1_data") show_images1(data=tn100p1_data, main_title="tn100p1_data") print() show_images1(data=t0p0_data, main_title="t0p0_data") show_images1(data=t0p0_data, main_title="t0p0_data") show_images1(data=t0p0_data, main_title="t0p0_data") print() show_images1(data=t0p05_data, main_title="t0p05_data") show_images1(data=t0p05_data, main_title="t0p05_data") show_images1(data=t0p05_data, main_title="t0p05_data") print() show_images1(data=t0p1_data, main_title="t0p1_data") show_images1(data=t0p1_data, main_title="t0p1_data") show_images1(data=t0p1_data, main_title="t0p1_data") # ↓ ↓ ↓ ↓ ↓ ↓ The code below is identical to the code above. ↓ ↓ ↓ ↓ ↓ ↓ def show_images2(data, main_title=None, t=None, p=0): 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) rs = RandomSolarize(threshold=t, p=p) plt.imshow(X=rs(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="t300p1_data", t=300, p=1) show_images2(data=origin_data, main_title="t256p1_data", t=256, p=1) show_images2(data=origin_data, main_title="t255p1_data", t=255, p=1) show_images2(data=origin_data, main_title="t250p1_data", t=250, p=1) show_images2(data=origin_data, main_title="t240p1_data", t=240, p=1) show_images2(data=origin_data, main_title="t220p1_data", t=220, p=1) show_images2(data=origin_data, main_title="t200p1_data", t=200, p=1) show_images2(data=origin_data, main_title="t150p1_data", t=150, p=1) show_images2(data=origin_data, main_title="t100p1_data", t=100, p=1) show_images2(data=origin_data, main_title="t50p1_data", t=50, p=1) show_images2(data=origin_data, main_title="t10p1_data", t=10, p=1) show_images2(data=origin_data, main_title="t0p1_data", t=0, p=1) show_images2(data=origin_data, main_title="tn10p1_data", t=-10, p=1) show_images2(data=origin_data, main_title="tn100p1_data", t=-100, p=1) print() show_images2(data=origin_data, main_title="t0p0_data", t=0, p=0) show_images2(data=origin_data, main_title="t0p0_data", t=0, p=0) show_images2(data=origin_data, main_title="t0p0_data", t=0, p=0) print() show_images2(data=origin_data, main_title="t0p05_data", t=0, p=0.5) show_images2(data=origin_data, main_title="t0p05_data", t=0, p=0.5) show_images2(data=origin_data, main_title="t0p05_data", t=0, p=0.5) print() show_images2(data=origin_data, main_title="t0p1_data", t=0, p=1) show_images2(data=origin_data, main_title="t0p1_data", t=0, p=1) show_images2(data=origin_data, main_title="t0p1_data", t=0, p=1)

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RandomSolarize in PyTorch

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