from PIL import Image

img = Image.open('01.jpg')
imgGrey = img.convert('L')

img.show()
imgGrey.show()

img.save('img_copy.jpg')
imgGrey.save('img_gray.jpg')

from PIL import Image
import numpy as np

img = Image.open('01.jpg')

width, height = img.size
channel_mode = img.mode
mean_value = np.mean(img)

print(width)
print(height)
print(channel_mode)
print(mean_value)

from PIL import Image

width = 200
height = 100

img_white = Image.new('RGB', (width,height), (255,255,255))
img_black = Image.new('RGB', (width,height), (0,0,0))
img_L = Image.new('L', (width, height), (255))

img_white.show()
img_black.show()
img_L.show()

from PIL import Image

img = Image.open('01.jpg')

width, height = img.size

# 獲取指定坐標位置像素值
pixel_value = img.getpixel((width/2, height/2))
print(pixel_value)

# 或者使用load方法
pim = img.load()
pixel_value1 = pim[width/2, height/2]
print(pixel_value1)

# 設置指定坐標位置像素的值
pim[width/2, height/2] = (0, 0, 0)

# 或使用putpixel方法
img.putpixel((w//2, h//2), (255,255,255))

# 設置指定區域像素的值
for w in range(int(width/2) - 40, int(width/2) + 40):
for h in range(int(height/2) - 20, int(height/2) + 20):
pim[w, h] = (255, 0, 0)
# img.putpixel((w, h), (255,255,255))
img.show()

from PIL import Image

img = Image.open('01.jpg')

# 通道分離
R, G, B = img.split()

R.show)
G.show()
B.show()

# 通道合并
img_RGB = Image.merge('RGB', (R, G, B))
img_BGR = Image.merge('RGB', (B, G, R))
img_RGB.show()
img_BGR.show()

from PIL import Image, ImageDraw, ImageFont

img = Image.open('01.jpg')

# 創建Draw對象:
draw = ImageDraw.Draw(img)
# 字體顏色
fillColor = (255, 0, 0)

text = 'print text on PIL Image'
position = (200,100)

draw.text(position, text, fill=fillColor)
img.show()

from PIL import Image

img = Image.open('01.jpg')

width, height = img.size

img_NEARESET = img.resize((width//2, height//2)) # 縮放默認模式是NEARESET(最近鄰插值)
img_BILINEAR = img.resize((width//2, height//2), Image.BILINEAR) # BILINEAR 2x2區域的雙線性插值
img_BICUBIC = img.resize((width//2, height//2), Image.BICUBIC) # BICUBIC 4x4區域的雙三次插值
img_ANTIALIAS = img.resize((width//2, height//2), Image.ANTIALIAS) # ANTIALIAS 高質量下采樣濾波

from PIL import Image

img = Image.open('01.jpg').convert('L')

width, height = img.size

pim = img.load()

for w in range(width):
for h in range(height):
if pim[w, h] > 100:
img.putpixel((w, h), 255)
# pim[w, h] = 255
else:
img.putpixel((w, h), 0)
# pim[w, h] = 0

img.show()

from PIL import Image

img = Image.open('01.jpg').convert('L')

width, height = img.size

threshold = 125

for w in range(width):
for h in range(height):
if img.getpixel((w, h)) > threshold:
img.putpixel((w, h), 255)
else:
img.putpixel((w, h), 0)

img.save('binary.jpg')

from PIL import Image

img = Image.open('01.jpg')

width, height = img.size

# 前兩個坐標點是左上角坐標
# 后兩個坐標點是右下角坐標
# width在前， height在后
box = (100, 100, 550, 350)

region = img.crop(box)

region.save('crop.jpg')

# 邊界擴展
from PIL import Image

img = Image.open('test.png')

width, height = img.size
channel_mode = img.mode

img_makeBorder_full = Image.new(channel_mode, (2*width, height))
img_makeBorder_part = Image.new(channel_mode, (width+200, height))

# 圖像水平擴展整個圖像
img_makeBorder_full.paste(img, (0, 0, width, height))
img_makeBorder_full.paste(img, (width, 0, 2*width, height))

# 前兩個坐標點是左上角坐標
# 后兩個坐標點是右下角坐標
# width在前， height在后
box = (width-200, 0, width, height)
region = img.crop(box)

# 圖像水平右側擴展一個ROI
img_makeBorder_part.paste(img, (0, 0, width, height))
img_makeBorder_part.paste(region, (width, 0, width+200, height))
img_makeBorder_part.show()
img_makeBorder_full.show()

from PIL import Image
import numpy as np

img = Image.open('01.jpg')

array = np.array(img) # PIL.Image 轉 numpy

img1 = Image.fromarray(array) # numpy轉 PIL.Image
img1 = Image.fromarray(array.astype('uint8'))

img1.save('from_array.jpg')