python PIL Image图像处理基本操作有哪些

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1. 图片加载、灰度图、 显示和保存

from PIL import Imageimg = Image.open('01.jpg')imgGrey = img.convert('L')img.show()imgGrey.show()img.save('img_copy.jpg')imgGrey.save('img_gray.jpg')

2. 图片宽、高、通道模式、平均值获取

from PIL import Imageimport numpy as npimg = Image.open('01.jpg')width, height = img.sizechannel_mode = img.modemean_value = np.mean(img)print(width)print(height)print(channel_mode)print(mean_value)

3. 创建指定大小，指定通道类型的空图像

from PIL import Imagewidth = 200height = 100img_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()

4. 访问和操作图像像素

from PIL import Imageimg = Image.open('01.jpg')width, height = img.size# 获取指定坐标位置像素值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)# 设置指定坐标位置像素的值pim[width/2, height/2] = (0, 0, 0)# 或使用putpixel方法img.putpixel((w//2, h//2), (255,255,255))# 设置指定区域像素的值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()

5. 图像通道分离和合并

from PIL import Imageimg = Image.open('01.jpg')# 通道分离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()

6. 在图像上输出文字

from PIL import Image, ImageDraw, ImageFontimg = Image.open('01.jpg')# 创建Draw对象:draw = ImageDraw.Draw(img)# 字体颜色fillColor = (255, 0, 0)text = 'print text on PIL Image'position = (200,100)draw.text(position, text, fill=fillColor)img.show()

7. 图像缩放

from PIL import Imageimg = Image.open('01.jpg')width, height = img.sizeimg_NEARESET = img.resize((width//2, height//2)) # 缩放默认模式是NEARESET(最近邻插值)img_BILINEAR = img.resize((width//2, height//2), Image.BILINEAR) # BILINEAR 2x2区域的双线性插值img_BICUBIC = img.resize((width//2, height//2), Image.BICUBIC) # BICUBIC 4x4区域的双三次插值img_ANTIALIAS = img.resize((width//2, height//2), Image.ANTIALIAS) # ANTIALIAS 高质量下采样滤波

8. 图像遍历操作

from PIL import Imageimg = Image.open('01.jpg').convert('L')width, height = img.sizepim = 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] = 255else:img.putpixel((w, h), 0)# pim[w, h] = 0img.show()

9. 图像阈值分割、 二值化

from PIL import Imageimg = Image.open('01.jpg').convert('L')width, height = img.sizethreshold = 125for 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')

10. 图像裁剪

from PIL import Imageimg = Image.open('01.jpg')width, height = img.size# 前两个坐标点是左上角坐标# 后两个坐标点是右下角坐标# width在前， height在后box = (100, 100, 550, 350)region = img.crop(box)region.save('crop.jpg')

11. 图像边界扩展

# 边界扩展from PIL import Imageimg = Image.open('test.png')width, height = img.sizechannel_mode = img.modeimg_makeBorder_full = Image.new(channel_mode, (2*width, height))img_makeBorder_part = Image.new(channel_mode, (width+200, height))# 图像水平扩展整个图像img_makeBorder_full.paste(img, (0, 0, width, height))img_makeBorder_full.paste(img, (width, 0, 2*width, height))# 前两个坐标点是左上角坐标# 后两个坐标点是右下角坐标# width在前， height在后box = (width-200, 0, width, height)region = img.crop(box)# 图像水平右侧扩展一个ROIimg_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()

12. PIL.Image 和 numpy 格式相互转换

from PIL import Imageimport numpy as npimg = Image.open('01.jpg')array = np.array(img) # PIL.Image 转 numpyimg1 = Image.fromarray(array) # numpy转 PIL.Imageimg1 = Image.fromarray(array.astype('uint8'))img1.save('from_array.jpg')

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