ElasticTransform in PyTorch (3)

from torchvision.datasets import OxfordIIITPet from torchvision.transforms.v2 import ElasticTransform from torchvision.transforms.functional import InterpolationMode origin_data = OxfordIIITPet( root="data", transform=None ) a5000s01_data = OxfordIIITPet( # `a` is alpha and `s` is sigma.  root="data", transform=ElasticTransform(alpha=5000, sigma=0.1) # transform=ElasticTransform(alpha=5000, sigma=[0.1, 0.1]) ) a5000s1_data = OxfordIIITPet( root="data", transform=ElasticTransform(alpha=5000, sigma=1) ) a5000s5_data = OxfordIIITPet( root="data", transform=ElasticTransform(alpha=5000, sigma=5) ) a5000s10_data = OxfordIIITPet( root="data", transform=ElasticTransform(alpha=5000, sigma=10) ) a5000s20_data = OxfordIIITPet( root="data", transform=ElasticTransform(alpha=5000, sigma=20) ) a5000s40_data = OxfordIIITPet( root="data", transform=ElasticTransform(alpha=5000, sigma=40) ) a5000s40_01_data = OxfordIIITPet( root="data", transform=ElasticTransform(alpha=5000, sigma=[40, 0.1]) ) a5000s40_1_data = OxfordIIITPet( root="data", transform=ElasticTransform(alpha=5000, sigma=[40, 1]) ) a5000s40_5_data = OxfordIIITPet( root="data", transform=ElasticTransform(alpha=5000, sigma=[40, 5]) ) a5000s40_10_data = OxfordIIITPet( root="data", transform=ElasticTransform(alpha=5000, sigma=[40, 10]) ) a5000s40_20_data = OxfordIIITPet( root="data", transform=ElasticTransform(alpha=5000, sigma=[40, 20]) ) a5000s40_40_data = OxfordIIITPet( root="data", transform=ElasticTransform(alpha=5000, sigma=[40, 40]) ) a5000s01_40_data = OxfordIIITPet( root="data", transform=ElasticTransform(alpha=5000, sigma=[0.1, 40]) ) a5000s1_40_data = OxfordIIITPet( root="data", transform=ElasticTransform(alpha=5000, sigma=[1, 40]) ) a5000s5_40_data = OxfordIIITPet( root="data", transform=ElasticTransform(alpha=5000, sigma=[5, 40]) ) a5000s10_40_data = OxfordIIITPet( root="data", transform=ElasticTransform(alpha=5000, sigma=[10, 40]) ) a5000s20_40_data = OxfordIIITPet( root="data", transform=ElasticTransform(alpha=5000, sigma=[20, 40]) ) a5000s40_40_data = OxfordIIITPet( root="data", transform=ElasticTransform(alpha=5000, sigma=[40, 40]) ) a5000s5fgray_data = OxfordIIITPet( # `f` is fill.  root="data", transform=ElasticTransform(alpha=5000, sigma=5, fill=150) # transform=ElasticTransform(alpha=5000, sigma=5, fill=[150]) ) a5000s10fgray_data = OxfordIIITPet( root="data", transform=ElasticTransform(alpha=5000, sigma=10, fill=150) ) a5000s5fpurple_data = OxfordIIITPet( root="data", transform=ElasticTransform(alpha=5000, sigma=5, fill=[160, 32, 240]) ) a5000s10fpurple_data = OxfordIIITPet( root="data", transform=ElasticTransform(alpha=5000, sigma=10, fill=[160, 32, 240]) ) 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=a5000s01_data, main_title="a5000s01_data") show_images1(data=a5000s1_data, main_title="a5000s1_data") show_images1(data=a5000s5_data, main_title="a5000s5_data") show_images1(data=a5000s10_data, main_title="a5000s10_data") show_images1(data=a5000s20_data, main_title="a5000s20_data") show_images1(data=a5000s40_data, main_title="a5000s40_data") print() show_images1(data=a5000s40_01_data, main_title="a5000s40_01_data") show_images1(data=a5000s40_1_data, main_title="a5000s40_1_data") show_images1(data=a5000s40_5_data, main_title="a5000s40_5_data") show_images1(data=a5000s40_10_data, main_title="a5000s40_10_data") show_images1(data=a5000s40_20_data, main_title="a5000s40_20_data") show_images1(data=a5000s40_40_data, main_title="a5000s40_40_data") print() show_images1(data=a5000s01_40_data, main_title="a5000s01_40_data") show_images1(data=a5000s1_40_data, main_title="a5000s1_40_data") show_images1(data=a5000s5_40_data, main_title="a5000s5_40_data") show_images1(data=a5000s10_40_data, main_title="a5000s10_40_data") show_images1(data=a5000s20_40_data, main_title="a5000s20_40_data") show_images1(data=a5000s40_40_data, main_title="a5000s40_40_data") print() show_images1(data=a5000fgray_data, main_title="a5000fgray_data") show_images1(data=a10000fgray_data, main_title="a10000fgray_data") show_images1(data=a5000fpurple_data, main_title="a5000fpurple_data") show_images1(data=a10000fpurple_data, main_title="a10000fpurple_data") # ↓ ↓ ↓ ↓ ↓ ↓ The code below is identical to the code above. ↓ ↓ ↓ ↓ ↓ ↓ def show_images2(data, main_title=None, a=50, s=5, ip=InterpolationMode.BILINEAR, f=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) et = ElasticTransform(alpha=a, sigma=s, interpolation=ip, fill=f) plt.imshow(X=et(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="a5000s01_data", a=5000, s=0.1) show_images2(data=origin_data, main_title="a5000s1_data", a=5000, s=1) show_images2(data=origin_data, main_title="a5000s5_data", a=5000, s=5) show_images2(data=origin_data, main_title="a5000s10_data", a=5000, s=10) show_images2(data=origin_data, main_title="a5000s20_data", a=5000, s=20) show_images2(data=origin_data, main_title="a5000s40_data", a=5000, s=40) print() show_images2(data=origin_data, main_title="a5000s40_01_data", a=5000, s=[40, 0.1]) show_images2(data=origin_data, main_title="a5000s40_1_data", a=5000, s=[40, 1]) show_images2(data=origin_data, main_title="a5000s40_5_data", a=5000, s=[40, 5]) show_images2(data=origin_data, main_title="a5000s40_10_data", a=5000, s=[40, 10]) show_images2(data=origin_data, main_title="a5000s40_20_data", a=5000, s=[40, 20]) show_images2(data=origin_data, main_title="a5000s40_40_data", a=5000, s=[40, 40]) print() show_images2(data=origin_data, main_title="a5000s01_40_data", a=5000, s=[0.1, 40]) show_images2(data=origin_data, main_title="a5000s1_40_data", a=5000, s=[1, 40]) show_images2(data=origin_data, main_title="a5000s5_40_data", a=5000, s=[5, 40]) show_images2(data=origin_data, main_title="a5000s10_40_data", a=5000, s=[10, 40]) show_images2(data=origin_data, main_title="a5000s20_40_data", a=5000, s=[20, 40]) show_images2(data=origin_data, main_title="a5000s40_40_data", a=5000, s=[40, 40]) print() show_images2(data=origin_data, main_title="a5000fgray_data", a=5000, f=150) show_images2(data=origin_data, main_title="a10000fgray_data", a=10000, f=150) show_images2(data=origin_data, main_title="a5000fpurple_data", a=5000, f=[160, 32, 240]) show_images2(data=origin_data, main_title="a10000fpurple_data", a=10000, f=[160, 32, 240]) print() show_images2(data=origin_data, main_title="a5000s5fgray_data", a=5000, s=5, f=150) show_images2(data=origin_data, main_title="a5000s10fgray_data", a=5000, s=10, f=150) print() show_images2(data=origin_data, main_title="a5000s5fpurple_data", a=5000, s=5, f=[160, 32, 240]) show_images2(data=origin_data, main_title="a5000s10fpurple_data", a=5000, s=10, f=[160, 32, 240])