*Memos:
- My post explains RandomCrop() about
sizeargument. - My post explains Resize().
- My post explains OxfordIIITPet().
Pad() can add padding to an image as shown below:
*Memos:
- The 1st argument for initialization is
padding(Required-Type:intortuple/list(int)): *Memos:- It's
[left, top, right, bottom]which can be converted from[left-right, top-bottom]or[left-top-right-bottom]. - A tuple/list must be the 1D with 1, 2 or 4 elements.
- A single value(
intortuple/list(int)) means[padding, padding, padding, padding]. - Double values(
tuple/list(int)) means[padding[0], padding[1], padding[0], padding[1]].
- It's
- The 2nd argument for initialization is
fill(Optional-Default:0-Type:int,floatortuple/list(intorfloat)): *Memos:- It can change the background of an image. *The background can be seen when rotating an image.
- A tuple/list must be the 1D with 1 or 3 elements.
- If all values are
x <= 0, it's black. - If all values are
255 <= x, it's white.
- The 3rd argument for initialization is
padding_mode(Optional-Default:'constant'-Type:str). *'constant','edge','reflect'or'symmetric'can be set to it. - The 1st argument is
img(Required-Type:PIL Imageortensor(int/float/complex/bool)): *Memos:- A tensor must be 3D or more D.
- Don't use
img=.
-
v2is recommended to use according to V1 or V2? Which one should I use?.
from torchvision.datasets import OxfordIIITPet from torchvision.transforms.v2 import Pad pad = Pad(padding=100) pad = Pad(padding=100, fill=0, padding_mode='constant') pad # Pad(padding=100, fill=0, padding_mode=constant) pad.padding # 100 pad.fill # 0 pad.padding_mode # 'constant' origin_data = OxfordIIITPet( root="data", transform=None ) p0origin_data = OxfordIIITPet( # `p` is padding. root="data", transform=Pad(padding=0) # transform=Pad(padding=[0, 0]) # transform=Pad(padding=[0, 0, 0, 0]) ) p50_data = OxfordIIITPet( root="data", transform=Pad(padding=50) ) p100_data = OxfordIIITPet( root="data", transform=Pad(padding=100) ) p150_data = OxfordIIITPet( root="data", transform=Pad(padding=150) ) pn50_data = OxfordIIITPet( # `n` is negative. root="data", transform=Pad(padding=-50) ) pn100_data = OxfordIIITPet( root="data", transform=Pad(padding=-100) ) pn150_data = OxfordIIITPet( root="data", transform=Pad(padding=-150) ) p100_50_data = OxfordIIITPet( root="data", transform=Pad(padding=[100, 50]) ) pn100n50_data = OxfordIIITPet( root="data", transform=Pad(padding=[-100, -50]) ) p100n50_data = OxfordIIITPet( root="data", transform=Pad(padding=[100, -50]) ) p25_50_75_100_data = OxfordIIITPet( root="data", transform=Pad(padding=[25, 50, 75, 100]) ) pn25n50n75n100_data = OxfordIIITPet( root="data", transform=Pad(padding=[-25, -50, -75, -100]) ) p25n50_75n100_data = OxfordIIITPet( root="data", transform=Pad(padding=[25, -50, 75, -100]) ) p100fgray_data = OxfordIIITPet( # `f` is fill. root="data", transform=Pad(padding=100, fill=150) # transform=Pad(padding=100, fill=[150]) ) p100fpurple_data = OxfordIIITPet( root="data", transform=Pad(padding=100, fill=[160, 32, 240]) ) p100pmconstant_data = OxfordIIITPet( # `pm` is padding_mode. root="data", transform=Pad(padding=100, padding_mode="constant") ) p100pmedge_data = OxfordIIITPet( root="data", transform=Pad(padding=100, padding_mode="edge") ) p100pmreflect_data = OxfordIIITPet( root="data", transform=Pad(padding=100, padding_mode="reflect") ) p100pmsymmetric_data = OxfordIIITPet( root="data", transform=Pad(padding=100, padding_mode="symmetric") ) 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') print() show_images1(data=p0origin_data, main_title='p0origin_data') show_images1(data=p50_data, main_title='p50_data') show_images1(data=p100_data, main_title='p100_data') show_images1(data=p150_data, main_title='p150_data') print() show_images1(data=p0origin_data, main_title='p0origin_data') show_images1(data=pn50_data, main_title='pn50_data') show_images1(data=pn100_data, main_title='pn100_data') show_images1(data=pn150_data, main_title='pn150_data') print() show_images1(data=p0origin_data, main_title='p0origin_data') show_images1(data=p100_50_data, main_title='p100_50_data') show_images1(data=pn100n50_data, main_title='pn100n50_data') show_images1(data=p100n50_data, main_title='p100n50_data') print() show_images1(data=p0origin_data, main_title='p0origin_data') show_images1(data=p25_50_75_100_data, main_title='p25_50_75_100_data') show_images1(data=pn25n50n75n100_data, main_title='pn25n50n75n100_data') show_images1(data=p25n50_75n100_data, main_title='p25n50_75n100_data') print() show_images1(data=p100fgray_data, main_title='p100fgray_data') show_images1(data=p100fpurple_data, main_title='p100fpurple_data') print() show_images1(data=p100pmconstant_data, main_title='p100pmconstant_data') show_images1(data=p100pmedge_data, main_title='p100pmedge_data') show_images1(data=p100pmreflect_data, main_title='p100pmreflect_data') show_images1(data=p100pmsymmetric_data, main_title='p100pmsymmetric_data') # ↓ ↓ ↓ ↓ ↓ ↓ The code below is identical to the code above. ↓ ↓ ↓ ↓ ↓ ↓ def show_images2(data, main_title=None, p=None, f=0, pm='constant'): 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) pad = Pad(padding=p, fill=f, padding_mode=pm) plt.imshow(X=pad(im)) else: for i, (im, _) in zip(range(1, 6), data): plt.subplot(1, 5, i) plt.imshow(X=im) plt.tight_layout() plt.show() show_images2(data=origin_data, main_title='origin_data') print() show_images2(data=origin_data, main_title='p0origin_data', p=0) show_images2(data=origin_data, main_title='p50_data', p=50) show_images2(data=origin_data, main_title='p100_data', p=100) show_images2(data=origin_data, main_title='p150_data', p=150) print() show_images2(data=origin_data, main_title='p0origin_data', p=0) show_images2(data=origin_data, main_title='pn50_data', p=-50) show_images2(data=origin_data, main_title='pn100_data', p=-100) show_images2(data=origin_data, main_title='pn150_data', p=-150) print() show_images2(data=origin_data, main_title='p0origin_data', p=0) show_images2(data=origin_data, main_title='p100_50_data', p=[100, 50]) show_images2(data=origin_data, main_title='pn100n50_data', p=[-100, -50]) show_images2(data=origin_data, main_title='p100n50_data', p=[100, -50]) print() show_images2(data=origin_data, main_title='p0origin_data', p=0) show_images2(data=origin_data, main_title='p25p50p75p100_data', p=[25, 50, 75, 100]) show_images2(data=origin_data, main_title='pn25n50n75n100_data', p=[-25, -50, -75, -100]) show_images2(data=origin_data, main_title='p25n50_75n100_data', p=[25, -50, 75, -100]) print() show_images2(data=origin_data, main_title='p100fgray_data', p=100, f=150) show_images2(data=origin_data, main_title='p100fpurple_data', p=100, f=[160, 32, 240]) print() show_images2(data=origin_data, main_title='p100pmconstant_data', p=100, pm='constant') show_images2(data=origin_data, main_title='p100pmedge_data', p=100, pm='edge') show_images2(data=origin_data, main_title='p100pmreflect_data', p=100, pm='reflect') show_images2(data=origin_data, main_title='p100pmsymmetric_data', p=100, pm='symmetric') 
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