RandomResizedCrop in PyTorch (5)



This content originally appeared on DEV Community and was authored by Super Kai (Kazuya Ito)

Buy Me a Coffee☕

*Memos:

RandomResizedCrop() can crop a random part of an image, then resize it to a given size as shown below. *It’s about ratio argument (1):

from torchvision.datasets import OxfordIIITPet
from torchvision.transforms.v2 import RandomResizedCrop
from torchvision.transforms.functional import InterpolationMode

origin_data = OxfordIIITPet(
    root="data",
    transform=None
)

s1000r1_1origin_data = OxfordIIITPet( # `s` is size and `r` is ratio.
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[1, 1])
)

s1000r01_10_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[0.1, 10])
)

s1000r01_1_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[0.1, 1])
)

s1000r1_10_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[1, 10])
)

s1000r09_09_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[0.9, 0.9])
)

s1000r08_08_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[0.8, 0.8])
)

s1000r07_07_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[0.7, 0.7])
)

s1000r06_06_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[0.6, 0.6])
)

s1000r05_05_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[0.5, 0.5])
)

s1000r04_04_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[0.4, 0.4])
)

s1000r03_03_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[0.3, 0.3])
)

s1000r02_02_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[0.2, 0.2])
)

s1000r01_01_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[0.1, 0.1])
)

s1000r001_001_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[0.01, 0.01])
)

s1000r0001_0001_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[0.001, 0.001])
)

s1000r00001_00001_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[0.0001, 0.0001])
)

s1000r2_2_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[2, 2])
)

s1000r3_3_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[3, 3])
)

s1000r4_4_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[4, 4])
)

s1000r5_5_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[5, 5])
)

s1000r6_6_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[6, 6])
)

s1000r7_7_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[7, 7])
)

s1000r8_8_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[8, 8])
)

s1000r9_9_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[9, 9])
)

s1000r10_10_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[10, 10])
)

s1000r100_100_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[100, 100])
)

s1000r1000_1000_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[1000, 1000])
)

s1000r10000_10000_data = OxfordIIITPet(
    root="data",
    transform=RandomResizedCrop(size=1000, ratio=[10000, 10000])
)

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=s1000r1_1origin_data, main_title="s1000r1_1origin_data")
show_images1(data=s1000r01_10_data, main_title="s1000r01_10_data")
show_images1(data=s1000r01_1_data, main_title="s1000r01_1_data")
show_images1(data=s1000r1_10_data, main_title="s1000r1_10_data")
print()
show_images1(data=s1000r1_1origin_data, main_title="s1000r1_1origin_data")
show_images1(data=s1000r09_09_data , main_title="s1000r09_09_data")
show_images1(data=s1000r08_08_data, main_title="s1000r08_08_data")
show_images1(data=s1000r07_07_data, main_title="s1000r07_07_data")
show_images1(data=s1000r06_06_data, main_title="s1000r06_06_data")
show_images1(data=s1000r05_05_data, main_title="s1000r05_05_data")
show_images1(data=s1000r04_04_data, main_title="s1000r04_04_data")
show_images1(data=s1000r03_03_data, main_title="s1000r03_03_data")
show_images1(data=s1000r02_02_data, main_title="s1000r02_02_data")
show_images1(data=s1000r01_01_data, main_title="s1000r01_01_data")
show_images1(data=s1000r001_001_data, main_title="s1000r001_001_data")
show_images1(data=s1000r0001_0001_data, main_title="s1000r0001_0001_data")
show_images1(data=s1000r00001_00001_data, main_title="s1000r00001_00001_data")
print()
show_images1(data=s1000r1_1origin_data, main_title="s1000r1_1origin_data")
show_images1(data=s1000r2_2_data, main_title="s1000r2_2_data")
show_images1(data=s1000r3_3_data, main_title="s1000r3_3_data")
show_images1(data=s1000r4_4_data, main_title="s1000r4_4_data")
show_images1(data=s1000r5_5_data, main_title="s1000r5_5_data")
show_images1(data=s1000r6_6_data, main_title="s1000r6_6_data")
show_images1(data=s1000r7_7_data, main_title="s1000r7_7_data")
show_images1(data=s1000r8_8_data, main_title="s1000r8_8_data")
show_images1(data=s1000r9_9_data, main_title="s1000r9_9_data")
show_images1(data=s1000r10_10_data, main_title="s1000r10_10_data")
show_images1(data=s1000r100_100_data, main_title="s1000r100_100_data")
show_images1(data=s1000r1000_1000_data, main_title="s1000r1000_1000_data")
show_images1(data=s1000r10000_10000_data, main_title="s1000r10000_10000_data")

# ↓ ↓ ↓ ↓ ↓ ↓ The code below is identical to the code above. ↓ ↓ ↓ ↓ ↓ ↓ 
def show_images2(data, main_title=None, s=None, sc=(0.08, 1),
                 r=(0.75, 1.3333333333333333),
                 ip=InterpolationMode.BILINEAR, a=True):
    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)
            rrc = RandomResizedCrop(size=s, scale=sc,
                                    ratio=r, interpolation=ip,
                                    antialias=a)
            plt.imshow(X=rrc(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="s1000r1_1origin_data", s=1000,  
             r=[1, 1])
show_images2(data=origin_data, main_title="s1000r01_10_data", s=1000,
             r=[0.1, 10])
show_images2(data=origin_data, main_title="s1000r01_1_data", s=1000,
             r=[0.1, 1])
show_images2(data=origin_data, main_title="s1000r1_10_data", s=1000, r=[1, 10])
print()
show_images2(data=origin_data, main_title="s1000r1_1origin_data", s=1000,
             r=[1, 1])
show_images2(data=origin_data, main_title="s1000r09_09_data", s=1000,
             r=[0.9, 0.9])
show_images2(data=origin_data, main_title="s1000r08_08_data", s=1000,
             r=[0.8, 0.8])
show_images2(data=origin_data, main_title="s1000r07_07_data", s=1000,
             r=[0.7, 0.7])
show_images2(data=origin_data, main_title="s1000r06_06_data", s=1000,
             r=[0.6, 0.6])
show_images2(data=origin_data, main_title="s1000r05_05_data", s=1000,
             r=[0.5, 0.5])
show_images2(data=origin_data, main_title="s1000r04_04_data", s=1000,
             r=[0.4, 0.4])
show_images2(data=origin_data, main_title="s1000r03_03_data", s=1000,
             r=[0.3, 0.3])
show_images2(data=origin_data, main_title="s1000r02_02_data", s=1000,
             r=[0.2, 0.2])
show_images2(data=origin_data, main_title="s1000r01_01_data", s=1000,
             r=[0.1, 0.1])
show_images2(data=origin_data, main_title="s1000r001_001_data", s=1000,
             r=[0.01, 0.01])
show_images2(data=origin_data, main_title="s1000r0001_0001_data", s=1000,
             r=[0.001, 0.001])
show_images2(data=origin_data, main_title="s1000r00001_00001_data", s=1000,
             r=[0.0001, 0.0001])
print()
show_images2(data=origin_data, main_title="s1000r1_1origin_data", s=1000,
             r=[1, 1])
show_images2(data=origin_data, main_title="s1000r2_2_data", s=1000, r=[2, 2])
show_images2(data=origin_data, main_title="s1000r3_3_data", s=1000, r=[3, 3])
show_images2(data=origin_data, main_title="s1000r4_4_data", s=1000, r=[4, 4])
show_images2(data=origin_data, main_title="s1000r5_5_data", s=1000, r=[5, 5])
show_images2(data=origin_data, main_title="s1000r6_6_data", s=1000, r=[6, 6])
show_images2(data=origin_data, main_title="s1000r7_7_data", s=1000, r=[7, 7])
show_images2(data=origin_data, main_title="s1000r8_8_data", s=1000, r=[8, 8])
show_images2(data=origin_data, main_title="s1000r9_9_data", s=1000, r=[9, 9])
show_images2(data=origin_data, main_title="s1000r10_10_data", s=1000,
             r=[10, 10])
show_images2(data=origin_data, main_title="s1000r100_100_data", s=1000,
             r=[100, 100])
show_images2(data=origin_data, main_title="s1000r1000_1000_data", s=1000,
             r=[1000, 1000])
show_images2(data=origin_data, main_title="s1000r10000_10000_data", s=1000,
             r=[10000, 10000])

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description

Image description


This content originally appeared on DEV Community and was authored by Super Kai (Kazuya Ito)