ColorJitter in PyTorch (2)

#python #pytorch #colorjitter #v2
*Memos:
My post explains ColorJitter() with brightness and contrast argument.
My post explains OxfordIIITPet().
ColorJitter() can randomly change the brightness, contrast, saturation and hue of an image as shown below:
from torchvision.datasets import OxfordIIITPet
from torchvision.transforms.v2 import ColorJitter

origin_data = OxfordIIITPet(
    root="data",
    transform=None
    # transform=ColorJitter()
    # colorjitter = ColorJitter(brightness=0,
    #                           contrast=0,
    #                           saturation=0,
    #                           hue=0)
    # transform=ColorJitter(brightness=[1, 1]),
    #                       contrast=[1, 1],
    #                       saturation=[1, 1],
    #                       hue=[0, 0])
)

saturation1_1origin_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(saturation=[1, 1])
)

saturation0_5_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(saturation=[0, 5])
    # transform=ColorJitter(saturation=4)
)

saturation0_1_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(saturation=[0, 1])
)

saturation1_5_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(saturation=[1, 5])
)

saturation08_08_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(saturation=[0.8, 0.8])
)

saturation06_06_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(saturation=[0.6, 0.6])
)

saturation04_04_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(saturation=[0.4, 0.4])
)

saturation02_02_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(saturation=[0.2, 0.2])
)

saturation0_0_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(saturation=[0, 0])
)

saturation2_2_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(saturation=[2, 2])
)

saturation4_4_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(saturation=[4, 4])
)

saturation8_8_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(saturation=[8, 8])
)

saturation16_16_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(saturation=[16, 16])
)

saturation50_50_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(saturation=[50, 50])
)

hue0_0origin_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(hue=[0, 0])
)

huen05_05_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(hue=[-0.5, 0.5])
    # transform=ColorJitter(hue=0.5)
)

huen05_0_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(hue=[-0.5, 0])
)

hue0_05_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(hue=[0, 0.5])
)

hue01_01_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(hue=[0.1, 0.1])
)

hue02_02_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(hue=[0.2, 0.2])
)

hue03_03_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(hue=[0.3, 0.3])
)

hue04_04_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(hue=[0.4, 0.4])
)

hue05_05_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(hue=[0.5, 0.5])
)

huen01n01_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(hue=[-0.1, -0.1])
)

huen02n02_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(hue=[-0.2, -0.2])
)

huen03n03_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(hue=[-0.3, -0.3])
)

huen04n04_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(hue=[-0.4, -0.4])
)

huen05n05_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(hue=[-0.5, -0.5])
)

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=saturation1_1origin_data, 
             main_title="saturation1_1origin_data")
show_images1(data=saturation0_5_data, main_title="saturation0_5_data")
show_images1(data=saturation0_1_data, main_title="saturation0_1_data")
show_images1(data=saturation1_5_data, main_title="saturation1_5_data")
print()
show_images1(data=saturation1_1origin_data,
             main_title="saturation1_1origin_data")
show_images1(data=saturation08_08_data, main_title="saturation08_08_data")
show_images1(data=saturation06_06_data, main_title="saturation06_06_data")
show_images1(data=saturation04_04_data, main_title="saturation04_04_data")
show_images1(data=saturation02_02_data, main_title="saturation02_02_data")
show_images1(data=saturation0_0_data, main_title="saturation0_0_data")
print()
show_images1(data=saturation1_1origin_data,
             main_title="saturation1_1origin_data")
show_images1(data=saturation2_2_data, main_title="saturation2_2_data")
show_images1(data=saturation4_4_data, main_title="saturation4_4_data")
show_images1(data=saturation8_8_data, main_title="saturation8_8_data")
show_images1(data=saturation16_16_data, main_title="saturation16_16_data")
show_images1(data=saturation50_50_data, main_title="saturation50_50_data")
print()
show_images1(data=hue0_0origin_data, main_title="hue0_0origin_data")
show_images1(data=huen05_05_data, main_title="huen05_05_data")
show_images1(data=huen05_0_data, main_title="huen05_0_data")
show_images1(data=hue0_05_data, main_title="hue0_05_data")
print()
show_images1(data=hue0_0origin_data, main_title="hue0_0origin_data")
show_images1(data=hue01_01_data, main_title="hue01_01_data")
show_images1(data=hue02_02_data, main_title="hue02_02_data")
show_images1(data=hue03_03_data, main_title="hue03_03_data")
show_images1(data=hue04_04_data, main_title="hue04_04_data")
show_images1(data=hue05_05_data, main_title="hue05_05_data")
print()
show_images1(data=hue0_0origin_data, main_title="hue0_0origin_data")
show_images1(data=huen01n01_data, main_title="huen01n01_data")
show_images1(data=huen02n02_data, main_title="huen02n02_data")
show_images1(data=huen03n03_data, main_title="huen03n03_data")
show_images1(data=huen04n04_data, main_title="huen04n04_data")
show_images1(data=huen05n05_data, main_title="huen05n05_data")

# ↓ ↓ ↓ ↓ ↓ ↓ The code below is identical to the code above. ↓ ↓ ↓ ↓ ↓ ↓
def show_images2(data, main_title=None, b=0, c=0, s=0, h=0):
    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)
        cj = ColorJitter(brightness=b, contrast=c, # Here
                         saturation=s, hue=h)
        plt.imshow(X=cj(im)) # Here
        plt.xticks(ticks=[])
        plt.yticks(ticks=[])
    plt.tight_layout()
    plt.show()

show_images2(data=origin_data, main_title="saturation1_1origin_data", s=[1, 1])
show_images2(data=origin_data, main_title="saturation0_5_data", s=[0, 5])
# ↑ show_images2(data=origin_data, main_title="saturation4_data", s=4)
show_images2(data=origin_data, main_title="saturation0_1_data", s=[0, 1])
show_images2(data=origin_data, main_title="saturation1_5_data", s=[1, 5])
print()
show_images2(data=origin_data, main_title="saturation1_1origin_data", s=[1, 1])
show_images2(data=origin_data, main_title="saturation08_08_data", s=[0.8, 0.8])
show_images2(data=origin_data, main_title="saturation06_06_data", s=[0.6, 0.6])
show_images2(data=origin_data, main_title="saturation04_04_data", s=[0.4, 0.4])
show_images2(data=origin_data, main_title="saturation02_02_data", s=[0.2, 0.2])
show_images2(data=origin_data, main_title="saturation0_0_data", s=[0, 0])
print()
show_images2(data=origin_data, main_title="saturation1_1origin_data", s=[1, 1])
show_images2(data=origin_data, main_title="saturation2_2_data", s=[2, 2])
show_images2(data=origin_data, main_title="saturation4_4_data", s=[4, 4])
show_images2(data=origin_data, main_title="saturation8_8_data", s=[8, 8])
show_images2(data=origin_data, main_title="saturation16_16_data", s=[16, 16])
show_images2(data=origin_data, main_title="saturation50_50_data", s=[50, 50])
print()
show_images2(data=origin_data, main_title="hue0_0origin_data", h=[0, 0])
show_images2(data=origin_data, main_title="huen05_05_data", h=[-0.5, 0.5])
# ↑ show_images2(data=origin_data, main_title="huen05_data", h=0.5)
show_images2(data=origin_data, main_title="huen05_0_data", h=[-0.5, 0])
show_images2(data=origin_data, main_title="hue0_05_data", h=[0, 0.5])
print()
show_images2(data=origin_data, main_title="hue0_0origin_data", h=[0, 0])
show_images2(data=origin_data, main_title="hue01_01_data", h=[0.1, 0.1])
show_images2(data=origin_data, main_title="hue02_02_data", h=[0.2, 0.2])
show_images2(data=origin_data, main_title="hue03_03_data", h=[0.3, 0.3])
show_images2(data=origin_data, main_title="hue04_04_data", h=[0.4, 0.4])
show_images2(data=origin_data, main_title="hue05_05_data", h=[0.5, 0.5])
print()
show_images2(data=origin_data, main_title="hue0_0origin_data", h=[0, 0])
show_images2(data=origin_data, main_title="huen01n01_data", h=[-0.1, -0.1])
show_images2(data=origin_data, main_title="huen02n02_data", h=[-0.2, -0.2])
show_images2(data=origin_data, main_title="huen03n03_data", h=[-0.3, -0.3])
show_images2(data=origin_data, main_title="huen04n04_data", h=[-0.4, -0.4])
show_images2(data=origin_data, main_title="huen05n05_data", h=[-0.5, -0.5])