ColorJitter in PyTorch (1)

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*Memos:

• My post explains ColorJitter() with saturation and hue argument.
• My post explains OxfordIIITPet().

ColorJitter() can randomly change the brightness, contrast, saturation and hue of an image as shown below:

*Memos:

• The 1st argument for initialization is brightness(Optional-Default:0-Type:int, float or tuple/list(int or float)): *Memos:
  • It's the range of the brightness [min, max] so it must be min <= max.
  • It must be 0 <= x.
  • A tuple/list must be the 1D with 2 elements.
  • A single value means [max(0, 1-brightness), 1+brightness].
• The 2nd argument for initialization is contrast(Optional-Default:0-Type:int, float or tuple/list(int or float)): *Memos:
  • It's the range of the contrast [min, max] so it must be min <= max.
  • It must be 0 <= x.
  • A tuple/list must be the 1D with 2 elements.
  • A single value means [max(0, 1-contrast), 1+contrast].
• The 3rd argument for initialization is saturation(Optional-Default:0-Type:int, float or tuple/list(int or float)): *Memos:
  • It's the range of the saturation [min, max] so it must be min <= max.
  • It must be 0 <= x.
  • A tuple/list must be the 1D with 2 elements.
  • A single value means [max(0, 1-saturation), 1+saturation].
• The 4th argument for initialization is hue(Optional-Default:0-Type:float or tuple/list(float)): *Memos:
  • It's the range of the hue [min, max] so it must be min <= max.
  • It must be -0.5 <= x <= 0.5.
  • A tuple or list must be the 1D with 2 elements.
  • A single value means [-hue, +hue].
• The 1st argument is img(Required-Type:PIL Image or tensor(int)): *Memos:
  • A tensor must be 2D or 3D.
  • Don't use img=.
• v2 is recommended to use according to V1 or V2? Which one should I use?.

from torchvision.datasets import OxfordIIITPet
from torchvision.transforms.v2 import ColorJitter

colorjitter = ColorJitter()
colorjitter = ColorJitter(brightness=0,
                          contrast=0,
                          saturation=0,
                          hue=0)
colorjitter = transform=ColorJitter(brightness=[1, 1]),
                                    contrast=[1, 1],
                                    saturation=[1, 1],
                                    hue=[0, 0])
colorjitter
# ColorJitter()

print(colorjitter.brightness)
# None

print(colorjitter.contrast)
# None

print(colorjitter.saturation)
# None

print(colorjitter.hue)
# None

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])
)

brightness1_1origin_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(brightness=[1, 1])
)

brightness0_5_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(brightness=[0, 5])
    # transform=ColorJitter(brightness=4)
)

brightness0_1_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(brightness=[0, 1])
)

brightness1_5_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(brightness=[1, 5])
)

brightness08_08_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(brightness=[0.8, 0.8])
)

brightness06_06_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(brightness=[0.6, 0.6])
)

brightness04_04_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(brightness=[0.4, 0.4])
)

brightness02_02_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(brightness=[0.2, 0.2])
)

brightness0_0_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(brightness=[0, 0])
)

brightness2_2_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(brightness=[2, 2])
)

brightness4_4_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(brightness=[4, 4])
)

brightness8_8_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(brightness=[8, 8])
)

brightness16_16_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(brightness=[16, 16])
)

brightness50_50_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(brightness=[50, 50])
)

contrast1_1origin_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(contrast=[1, 1])
)

contrast0_5_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(contrast=[0, 5])
    # transform=ColorJitter(contrast=4)
)

contrast0_1_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(contrast=[0, 1])
)

contrast1_5_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(contrast=[1, 5])
)

contrast08_08_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(contrast=[0.8, 0.8])
)

contrast06_06_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(contrast=[0.6, 0.6])
)

contrast04_04_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(contrast=[0.4, 0.4])
)

contrast02_02_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(contrast=[0.2, 0.2])
)

contrast0_0_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(contrast=[0, 0])
)

contrast2_2_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(contrast=[2, 2])
)

contrast4_4_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(contrast=[4, 4])
)

contrast8_8_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(contrast=[8, 8])
)

contrast16_16_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(contrast=[16, 16])
)

contrast50_50_data = OxfordIIITPet(
    root="data",
    transform=ColorJitter(contrast=[50, 50])
)

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=brightness1_1origin_data,
             main_title="brightness1_1origin_data")
show_images1(data=brightness0_5_data, main_title="brightness0_5_data")
show_images1(data=brightness0_1_data, main_title="brightness0_1_data")
show_images1(data=brightness1_5_data, main_title="brightness1_5_data")
print()
show_images1(data=brightness1_1origin_data,
             main_title="brightness1_1origin_data")
show_images1(data=brightness08_08_data, main_title="brightness08_08_data")
show_images1(data=brightness06_06_data, main_title="brightness06_06_data")
show_images1(data=brightness04_04_data, main_title="brightness04_04_data")
show_images1(data=brightness02_02_data, main_title="brightness02_02_data")
show_images1(data=brightness0_0_data, main_title="brightness0_0_data")
print()
show_images1(data=brightness1_1origin_data,
             main_title="brightness1_1origin_data")
show_images1(data=brightness2_2_data, main_title="brightness2_2_data")
show_images1(data=brightness4_4_data, main_title="brightness4_4_data")
show_images1(data=brightness8_8_data, main_title="brightness8_8_data")
show_images1(data=brightness16_16_data, main_title="brightness16_16_data")
show_images1(data=brightness50_50_data, main_title="brightness50_50_data")
print()
show_images1(data=contrast1_1origin_data,
             main_title="contrast1_1origin_data")
show_images1(data=contrast0_5_data, main_title="contrast0_5_data")
show_images1(data=contrast0_1_data, main_title="contrast0_1_data")
show_images1(data=contrast1_5_data, main_title="contrast1_5_data")
print()
show_images1(data=contrast1_1origin_data,
             main_title="contrast1_1origin_data")
show_images1(data=contrast08_08_data, main_title="contrast08_08_data")
show_images1(data=contrast06_06_data, main_title="contrast06_06_data")
show_images1(data=contrast04_04_data, main_title="contrast04_04_data")
show_images1(data=contrast02_02_data, main_title="contrast02_02_data")
show_images1(data=contrast0_0_data, main_title="contrast0_0_data")
print()
show_images1(data=contrast1_1origin_data,
             main_title="contrast1_1origin_data")
show_images1(data=contrast2_2_data, main_title="contrast2_2_data")
show_images1(data=contrast4_4_data, main_title="contrast4_4_data")
show_images1(data=contrast8_8_data, main_title="contrast8_8_data")
show_images1(data=contrast16_16_data, main_title="contrast16_16_data")
show_images1(data=contrast50_50_data, main_title="contrast50_50_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="brightness1_1origin_data",
             b=[1, 1])
show_images2(data=origin_data, main_title="brightness0_5_data", b=[0, 5])
# ↑ show_images2(data=origin_data, main_title="brightness4_data", b=4)
show_images2(data=origin_data, main_title="brightness0_1_data", b=[0, 1])
show_images2(data=origin_data, main_title="brightness1_5_data", b=[1, 5])
print()
show_images2(data=origin_data, main_title="brightness1_1origin_data", b=[1, 1])
show_images2(data=origin_data, main_title="brightness08_08_data", 
             b=[0.8, 0.8])
show_images2(data=origin_data, main_title="brightness06_06_data",
             b=[0.6, 0.6])
show_images2(data=origin_data, main_title="brightness04_04_data",
             b=[0.4, 0.4])
show_images2(data=origin_data, main_title="brightness02_02_data",
             b=[0.2, 0.2])
show_images2(data=origin_data, main_title="brightness0_0_data", b=[0, 0])
print()
show_images2(data=origin_data, main_title="brightness1_1origin_data",
             b=[1, 1])
show_images2(data=origin_data, main_title="brightness2_2_data", b=[2, 2])
show_images2(data=origin_data, main_title="brightness4_4_data", b=[4, 4])
show_images2(data=origin_data, main_title="brightness8_8_data", b=[8, 8])
show_images2(data=origin_data, main_title="brightness16_16_data", b=[16, 16])
show_images2(data=origin_data, main_title="brightness50_50_data", b=[50, 50])
print()
show_images2(data=origin_data, main_title="contrast1_1origin_data", c=[1, 1])
show_images2(data=origin_data, main_title="contrast0_5_data", c=[0, 5])
# ↑ show_images2(data=origin_data, main_title="contrast4_data", c=4)
show_images2(data=origin_data, main_title="contrast0_1_data", c=[0, 1])
show_images2(data=origin_data, main_title="contrast1_5_data", c=[1, 5])
print()
show_images2(data=origin_data, main_title="contrast1_1origin_data", c=[1, 1])
show_images2(data=origin_data, main_title="contrast08_08_data", c=[0.8, 0.8])
show_images2(data=origin_data, main_title="contrast06_06_data", c=[0.6, 0.6])
show_images2(data=origin_data, main_title="contrast04_04_data", c=[0.4, 0.4])
show_images2(data=origin_data, main_title="contrast02_02_data", c=[0.2, 0.2])
show_images2(data=origin_data, main_title="contrast0_0_data", c=[0, 0])
print()
show_images2(data=origin_data, main_title="contrast1_1origin_data", c=[1, 1])
show_images2(data=origin_data, main_title="contrast2_2_data", c=[2, 2])
show_images2(data=origin_data, main_title="contrast4_4_data", c=[4, 4])
show_images2(data=origin_data, main_title="contrast8_8_data", c=[8, 8])
show_images2(data=origin_data, main_title="contrast16_16_data", c=[16, 16])
show_images2(data=origin_data, main_title="contrast50_50_data", c=[50, 50])

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