给我买咖啡☕
*备忘录:
centercrop()可以裁剪图像,以此为中心:
*备忘录:
from torchvision.datasets import OxfordIIITPet from torchvision.transforms.v2 import CenterCrop centercrop = CenterCrop(size=100) centercrop # CenterCrop(size=(100, 100)) centercrop.size # (100, 100) origin_data = OxfordIIITPet( root="data", transform=None ) s600_data = OxfordIIITPet( # `s` is size. root="data", transform=CenterCrop(size=600) # transform=CenterCrop(size=[600]) # transform=CenterCrop(size=[600, 600]) ) s400_data = OxfordIIITPet( root="data", transform=CenterCrop(size=400) ) s200_data = OxfordIIITPet( root="data", transform=CenterCrop(size=200) ) s100_data = OxfordIIITPet( root="data", transform=CenterCrop(size=100) ) s50_data = OxfordIIITPet( root="data", transform=CenterCrop(size=50) ) s10_data = OxfordIIITPet( root="data", transform=CenterCrop(size=10) ) s1_data = OxfordIIITPet( root="data", transform=CenterCrop(size=1) ) s200_300_data = OxfordIIITPet( root="data", transform=CenterCrop(size=[200, 300]) ) s300_200_data = OxfordIIITPet( root="data", transform=CenterCrop(size=[300, 200]) ) 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.tight_layout() plt.show() show_images1(data=origin_data, main_title="origin_data") show_images1(data=s600_data, main_title="s600_data") show_images1(data=s400_data, main_title="s400_data") show_images1(data=s200_data, main_title="s200_data") show_images1(data=s100_data, main_title="s100_data") show_images1(data=s50_data, main_title="s50_data") show_images1(data=s10_data, main_title="s10_data") show_images1(data=s1_data, main_title="s1_data") print() show_images1(data=origin_data, main_title="origin_data") show_images1(data=s200_300_data, main_title="s200_300_data") show_images1(data=s300_200_data, main_title="s300_200_data") # ↓ ↓ ↓ ↓ ↓ ↓ The code below is identical to the code above. ↓ ↓ ↓ ↓ ↓ ↓ def show_images2(data, main_title=None, s=None): plt.figure(figsize=[10, 5]) plt.suptitle(t=main_title, y=0.8, fontsize=14) temp_s = s for i, (im, _) in zip(range(1, 6), data): plt.subplot(1, 5, i) if not temp_s: s = [im.size[1], im.size[0]] cc = CenterCrop(size=s) # Here plt.imshow(X=cc(im)) # Here plt.tight_layout() plt.show() show_images2(data=origin_data, main_title="origin_data") show_images2(data=origin_data, main_title="s600_data", s=600) show_images2(data=origin_data, main_title="s400_data", s=400) show_images2(data=origin_data, main_title="s200_data", s=200) show_images2(data=origin_data, main_title="s100_data", s=100) show_images2(data=origin_data, main_title="s50_data", s=50) show_images2(data=origin_data, main_title="s10_data", s=10) show_images2(data=origin_data, main_title="s1_data", s=1) print() show_images2(data=origin_data, main_title="origin_data") show_images2(data=origin_data, main_title="s200_300_data", s=[200, 300]) show_images2(data=origin_data, main_title="s300_200_data", s=[300, 200])
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