±à¼ÍƼö: |
±¾ÎÄÀ´×ÔÓÚר֪£¬±¾ÎÄʹÓÃ×îÁ÷ÐеÄPythonÓïÑÔΪ¹¤¾ß£¬¶ÔͼÏñ´¦Àí¼¼ÊõµÄ¾ßÌå²Ù×÷½øÐÐÏêϸ½²Êö£¬Ö¼ÔÚÈÃÁã»ù´¡µÄ¶ÁÕßÒ²¿ÉÒÔÇáËÉÉÏÊÖ£¡
|
|
¡¾µ¼¶Á¡¿ÔÚµ±½ñ»¥ÁªÍø·ÉËÙ·¢Õ¹µÄÉç»áÖУ¬ÊýÁ¿ÅÓ´óµÄͼÏñºÍÊÓÆµ³ä³â×ÅÎÒÃǵÄÉú»î£¬ÈÃÎÒÃÇÐèÒª¶ÔͼƬ½øÐмìË÷¡¢·ÖÀàµÈ²Ù×÷ʱ£¬ÀûÓÃÈ˹¤ÊÖ¶ÎÏÔÈ»ÊDz»ÏÖʵµÄ£¬ÓÚÊÇ£¬¼ÆËã»úÊÓ¾õÏà¹Ø¼¼Êõ±ãÓ¦Ô˶øÉú£¬²¢Çҵõ½ÁË¿ìËٵķ¢Õ¹¡£
»ù±¾µÄͼÏñ²Ù×÷ºÍ´¦Àí
PythonÖÐÓкö๤¾ß°üÓ¦ÓÃÓÚͼÏñ´¦Àíµ±ÖУ¬ÕâÒ»½Ú×÷ΪÈëÃÅÕ½ڣ¬Ê×ÏÈÀ´½éÉÜPythonÖÐ×î»ù±¾µÄ¼¸¸ö¹¤¾ß°ü£¬Ò²Ï£Íû¶ÁÕß¿ÉÒÔÔÚÖ®ºó×ÔÐÐÁ·Ï°¡£
PIL£ºPythonͼÏñ´¦ÀíÀà¿â
PIL(Python Imaging Library)ΪͼÏñ´¦ÀíÀà¿â£¬ËüΪPythonÌṩÁË»ù±¾µÄͼÏñ´¦Àí¹¦Äܺͻù±¾²Ù×÷¡£PILÖÐ×îÖØÒªµÄÄ£¿éÓÖÊÇImage£¬ÏÂÃæ£¬ÎÒÃǾÍÀ´½²Ò»½²ImageÄ£¿éµÄһЩÓ÷¨¡£
¶Áȡһ·ùͼÏñ£º
ÎÒÃÇÓÃImageÄ£¿éÖеÄopen()·½·¨ÊµÏÖ
Ê×ÏÈÇ¿µ÷Ò»µã¾ÍÊǶÔÓÚPNG¡¢BMPºÍJPGµÈ²»Í¬¸ñʽµÄ²ÊɫͼÏñÖ®¼äµÄ»¥Ïàת»»¶¼¿ÉÒÔͨ¹ýImageÄ£¿éÀ´Íê³É£¬¾ßÌåÀ´Ëµ£¬ÔÚ´ò¿ªÕâЩͼÏñʱ£¬PIL»á½«ËüÃǽâÂëΪÈýͨµÀµÄ¡°RGB¡±Í¼Ïñ¡£Óû§¿ÉÒÔ»ùÓÚÕâ¸ö¡°RGB¡±Í¼Ïñ£¬¶ÔÆä½øÐд¦Àí¡£
from PIL import
Image #´ÓPIL°üÖе¼ÈëImageÄ£¿é
image = Image.open('test.jpg') #¶ÁÈ¡ÃûΪtestµÄͼƬ |
ÕâÊÇtest.jpgͼƬ
ͨ¹ýÉÏÊö´úÂ룬ÎÒÃǵķµ»ØÖµimage¾ÍÊÇÒ»¸öPIL¶ÔÏ󣬵±ÎÒÃÇÐèÒª¶ÔÒ»·ùͼÏñ½øÐи÷ÖÖ²Ù×÷ʱ£¬Ê×Ïȶ¼ÒªÍ¨¹ýÉÏÊö´úÂë¶ÁȡĿ±êͼÏñ¡£
ÉÏÊö´úÂëµÄÔËÐнá¹ûʵ¼ÊÉÏΪ£º
<PIL.JpegImagePlugin.JpegImageFile
image mode=RGB size=1000x1436 at 0x1826BF51D68>
|
ÔõÑù²ÅÄܽ«Ëü±äΪ¿ÉÊÓ»¯µÄͼÏñÄØ£¿
ÎÒÃÇÐèÒªµ÷ÓÃmatplotlib.pyplotº¯Êý¼¯ºÏµÄ imshow() ºÍshow()·½·¨£¬ÍêÕû´úÂëΪ£º
from PIL import
Image
import matplotlib.pyplot as plt
image = Image.open('test.jpg')
plt.imshow(image)
plt.show()# ÐèÒªµ÷ÓÃshow()·½·¨£¬²»È»Í¼ÏñÖ»»áÔÚÄÚ´æÖжø²»ÏÔʾ³öÀ´ |
½á¹ûÈçÏÂͼËùʾ£º
½«Í¼Ïñת»»Îª»Ò¶ÈͼÏñ£º
ÎÒÃÇʹÓÃconvert()·½·¨À´ÊµÏÖͼÏñµÄ»Ò¶Èת»¯
Convert()º¯Êý»á¸ù¾Ý´«Èë²ÎÊýµÄ²»Í¬½«Í¼Æ¬±ä³É²»Í¬µÄģʽ£¬Í¨¹ýÏà¹Ø×ÊÁÏÎÒÃÇÖªµÀPILÖÐÓоÅÖÖ²»Í¬Ä£Ê½¡£·Ö±ðΪ1£¬L£¬P£¬RGB£¬RGBA£¬CMYK£¬YCbCr£¬I£¬F¡£
ģʽ¡°1¡±Îª¶þֵͼÏñ£¬·ÇºÚ¼´°×¡£µ«ÊÇËüÿ¸öÏñËØÓÃ8¸öbit±íʾ£¬0±íʾºÚ£¬255±íʾ°×¡£
ģʽL¡±Îª»ÒɫͼÏñ£¬ËüµÄÿ¸öÏñËØÓÃ8¸öbit±íʾ£¬0±íʾºÚ£¬255±íʾ°×£¬ÆäËûÊý×Ö±íʾ²»Í¬µÄ»Ò¶È¡£ÔÚPILÖУ¬´Óģʽ¡°RGB¡±×ª»»Îª¡°L¡±Ä£Ê½Êǰ´ÕÕÏÂÃæµÄ¹«Ê½×ª»»µÄ£º
L = R * 299/1000 + G * 587/1000+ B
* 114/1000
ģʽ¡°P¡±Îª8λ²ÊɫͼÏñ£¬ËüµÄÿ¸öÏñËØÓÃ8¸öbit±íʾ£¬Æä¶ÔÓ¦µÄ²ÊɫֵÊǰ´ÕÕµ÷É«°å²éѯ³öÀ´µÄ¡£
ģʽ¡°RGBA¡±Îª32λ²ÊɫͼÏñ£¬ËüµÄÿ¸öÏñËØÓÃ32¸öbit±íʾ£¬ÆäÖÐ24bit±íʾºìÉ«¡¢ÂÌÉ«ºÍÀ¶É«Èý¸öͨµÀ£¬ÁíÍâ8bit±íʾalphaͨµÀ£¬¼´Í¸Ã÷ͨµÀ¡£
ģʽ¡°CMYK¡±Îª32λ²ÊɫͼÏñ£¬ËüµÄÿ¸öÏñËØÓÃ32¸öbit±íʾ¡£Ä£Ê½¡°CMYK¡±¾ÍÊÇÓ¡Ë¢ËÄ·Öɫģʽ£¬ËüÊDzÊɫӡˢʱ²ÉÓõÄÒ»ÖÖÌ×ɫģʽ£¬ÀûÓÃÉ«ÁϵÄÈýÔÉ«»ìÉ«ÔÀí£¬¼ÓÉϺÚÉ«ÓÍÄ«£¬¹²¼ÆËÄÖÖÑÕÉ«»ìºÏµþ¼Ó£¬ÐγÉËùν¡°È«²ÊÓ¡Ë¢¡±¡£
ģʽ¡°YCbCr¡±Îª24λ²ÊɫͼÏñ£¬ËüµÄÿ¸öÏñËØÓÃ24¸öbit±íʾ¡£YCbCrÆäÖÐYÊÇÖ¸ÁÁ¶È·ÖÁ¿£¬CbÖ¸À¶É«É«¶È·ÖÁ¿£¬¶øCrÖ¸ºìɫɫ¶È·ÖÁ¿¡£È˵ÄÈâÑÛ¶ÔÊÓÆµµÄY·ÖÁ¿¸üÃô¸Ð£¬Òò´ËÔÚͨ¹ý¶ÔÉ«¶È·ÖÁ¿½øÐÐ×Ó²ÉÑùÀ´¼õÉÙÉ«¶È·ÖÁ¿ºó£¬ÈâÑÛ½«²ì¾õ²»µ½µÄͼÏñÖÊÁ¿µÄ±ä»¯¡£
ģʽ¡°RGB¡±×ª»»Îª¡°YCbCr¡±µÄ¹«Ê½ÈçÏ£º
Y= 0.257*R+0.504*G+0.098*B+16
Cb = -0.148*R-0.291*G+0.439*B+128
Cr = 0.439*R-0.368*G-0.071*B+128
ģʽ¡°I¡±Îª32λÕûÐÍ»ÒɫͼÏñ£¬ËüµÄÿ¸öÏñËØÓÃ32¸öbit±íʾ£¬0±íʾºÚ£¬255±íʾ°×£¬(0,255)Ö®¼äµÄÊý×Ö±íʾ²»Í¬µÄ»Ò¶È¡£ÔÚPILÖУ¬´Óģʽ¡°RGB¡±×ª»»Îª¡°I¡±Ä£Ê½Êǰ´ÕÕÏÂÃæµÄ¹«Ê½×ª»»µÄ£º
I = R * 299/1000 + G * 587/1000 +
B * 114/1000
ģʽ¡°F¡±Îª32λ¸¡µã»ÒɫͼÏñ£¬ËüµÄÿ¸öÏñËØÓÃ32¸öbit±íʾ£¬0±íʾºÚ£¬255±íʾ°×£¬(0,255)Ö®¼äµÄÊý×Ö±íʾ²»Í¬µÄ»Ò¶È¡£ÔÚPILÖУ¬´Óģʽ¡°RGB¡±×ª»»Îª¡°F¡±Ä£Ê½Êǰ´ÕÕÏÂÃæµÄ¹«Ê½×ª»»µÄ£º
F = R * 299/1000+ G * 587/1000 + B
* 114/1000
ÎÒÃÇÒÔ»Ò¶ÈͼÏñΪÀý£¬½«Ä¿±êͼÏñת»»³É»Ò¶ÈͼÏñ£¬ÓÉÉÏ¿ÉÖª£¬ÎÒÃÇÒª¸øconvert()·½·¨´«Èë²ÎÊý¡°L¡±,¾ßÌå´úÂëÈçÏ£º
from PIL import
Image
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.cm as cm
image = Image.open('test.jpg') # ¶ÁÈ¡ÃûΪtestµÄͼƬ
image_gray = image.convert("L") #
½«Í¼Æ¬×ª»»Îª»Ò¶ÈͼÏñ
data = np.array(image_gray)
plt.imshow(data, cmap=cm.gray)
plt.show() |
»æÖƳöµÄ»Ò¶ÈͼÏñΪ£º
ÎÒÃÇÒ²¿ÉÒÔÓÃÒ»ÐдúÂë
image = Image.open(¡®test.jpg¡¯).convert(¡°L¡±)
|
´úÌæÉÏÃæµÄÁ½ÐÐ×¢ÊÍ´úÂë¡£
ÔÚÉÏÊö´úÂëÖÐÎÒÃÇÒýÈëÁËmatplotlib.cmÄ£¿éºÍnumpyÄ£¿é¡£
cmÊÇcolormapµÄËõд£¬Õâ¸öÄ£¿éÌṩÁË´óÁ¿µÄcolormaps£¬ÓÃÓÚ×¢²áеÄcolormaps£¬²¢Í¨¹ýÃû³Æ»ñµÃÒ»¸öcolormap£¬ÒÔ¼°ÓÃÓÚÌí¼ÓÑÕɫӳÉ书ÄܵÄmixinÀà¡£
¶øÔÚ»æÖƻҶÈͼÏñµÄimshow()·½·¨¸øcmap´«ÈëÁËcm.gray²ÎÊý¡£cmap:´ú±íÑÕɫͼÆ×£¨colormap),
ĬÈÏ»æÖÆÎªRGB(A)ÑÕÉ«¿Õ¼ä¡£
Ϊʲôµ÷È¡»Ò¶ÈͼÏñ¼ÓÁËÕâôһÐдúÂëÄØ£¿ÔÒòÔÚÓÚÈç¹ûÊDzÊɫͼÏñ£¬ÉÏÃæµÄ·½·¨Ã»ÓÐÈκÎÎÊÌ⣬µ«ÊÇÈç¹ûÊǻҶÈͼÏñ£¬ÓÃÉÏÃæµÄÓï¾ä¾Í²»ÄÜÕýÈ·ÏÔʾ£¬Ö÷ÒªÊÇûÓмӵ÷É«°å¡£
³ý´ËÖ®Í⣬ÎÒÃÇ¿ÉÒÔÓÃÒ»ÐдúÂëplt.gray()À´´úÌæÉÏÊö´úÂëÕâÑùд»áʹ´úÂë¿´ÉÏÈ¥¸ü¼Ó¼ò½à¡£
NumPyÊÇÒ»¸ö·Ç³£ÓÐÃûµÄ Python ¿ÆÑ§¼ÆË㹤¾ß°ü,ÆäÖаüº¬ÁË´óÁ¿ÓÐÓõŤ¾ß,±ÈÈçÊý×é¶ÔÏó(ÓÃÀ´±íʾÏòÁ¿¡¢¾ØÕó¡¢Í¼ÏñµÈ)ÒÔ¼°ÏßÐÔ´úÊýº¯Êý¡£ÔÚÏÔʾ»Ò¶ÈͼÏñʱarray()·½·¨½«Í¼Ïñת»»³ÉNumPyµÄÊý×é¶ÔÏó£¬Í¼Æ¬µÃÒÔÏÔʾ£¬·ñÔò»á³öÏÖAttributeErrorµÄ´íÎó¡£
ת»»Í¼ÏñµÄ¸ñʽ£º
ͨ¹ýsave()·½·¨£¬PIL¿ÉÒÔ½«Í¼Ïñ±£´æ³É¶àÖÖ¸ñʽµÄÎļþ£¬µ±´«È벻ͬµÄÀ©Õ¹Ãûʱ£¬Ëü»á¸ù¾ÝÀ©Õ¹Ãû×Ô¶¯×ª»»Í¼ÏñµÄ¸ñʽ¡£
from PIL import Image
image = Image.open("smallpi.jpg")
# ´ò¿ªjpgͼÏñÎļþ
image.save("smallpi.png") # ±£´æÍ¼Ïñ£¬²¢×ª»»³Épng¸ñʽ
|
ÏÂÃæ³ÌÐò´ÓÎļþÃûÁÐ±í£¨filelist£©ÖжÁÈ¡ËùÓеÄͼÏñÎļþ£¬²¢×ª»»³ÉJPEG¸ñʽ£º
from PIL import
Image
import os
for infile in filelist:
outfile = os.path.splitext(infile)[0] + ¡°.jpg¡±
if infile != outfile:
try:
Image.open(infile).save(outfile)
except IOError:
print(¡®cannot convert¡¯, infile) |
PILµÄopen()·½·¨ÓÃÓÚ´´½¨PILͼÏñ¶ÔÏó£¬save()·½·¨ÓÃÓÚ±£´æÍ¼Ïñµ½¾ßÓÐÖ¸¶¨ÎļþÃûµÄÎļþ£¬ºó׺±äΪ¡°.jpg¡±£¬ÉÏÊö´úÂëµÄÐÂÎļþÃûºÍÔÎļþÃûÏàͬ¡£PILÊǸö×ã¹»ÖÇÄܵÄÀà¿â£¬¿ÉÒÔ¸ù¾ÝÎļþÀ©Õ¹ÃûÀ´Åж¨Í¼Ïñ¸ñʽPILº¯Êý»á½øÐмòµ¥µÄ¼ì²é£¬Èç¹ûÎļþÃû²»ÊÇJPEG¸ñʽ£¬»á×Ô¶¯½«ÆäתΪJPEG¸ñʽ£¬Èç¹ûת»»Ê§°Ü£¬Ôò»á±¨´í¡£
´´½¨ËõÂÔͼ
ʹÓÃPIL¿ÉÒԺܷ½±ãµØ´´½¨Í¼ÏñµÄËõÂÔͼ£¬thumbnail()·½·¨½ÓÊÜÒ»¸öÒ»Ôª×é²ÎÊý£¬È»ºó½«Í¼Ïñת»»³É·ûºÏÔª×é²ÎÊýÖ¸¶¨´óСµÄËõÂÔͼ¡£ÀýÈ磺
image.thumbnail((128,128))
|
thumbnailº¯Êý½ÓÊÜÒ»¸öÔª×é×÷Ϊ²ÎÊý£¬·Ö±ð¶ÔÓ¦×ÅËõÂÔͼµÄ¿í¸ß£¬ÔÚËõÂÔʱ£¬º¯Êý»á±£³ÖͼƬµÄ¿í¸ß±ÈÀý¡£Èç¹ûÊäÈëµÄ²ÎÊý¿í¸ßºÍÔͼÏñ¿í¸ß±È²»Í¬£¬Ôò»áÒÀ¾Ý×îС¶ÔÓ¦±ß½øÐÐÔ±ÈÀýËõ·Å¡£
±ÈÈç:
Ò»ÕÅͼƬΪ300*420´óСµÄͼƬ
µ±²ÎÊýΪ£¨200,200£©Ê±£¬Éú³ÉµÄËõÂÔͼ´óСΪ71*100£¬±£³ÖÔͼµÄ¿í¸ß±È
²Ã¼ôͼÏñÇøÓò
ʹÓÃPILÖеÄcrop()·½·¨¿ÉÒÔ´ÓÒ»·ùͼÏñÖвüôÖ¸¶¨ÇøÓò£¬¸ÃÇøÓòʹÓÃËÄÔª×éÀ´Ö¸¶¨£¬ËÄÔª×éµÄ×ø±êÒÀ´ÎÊÇ£¨×ó£¬ÉÏ£¬ÓÒ£¬Ï£©PILÖÐÖ¸¶¨×ø±êϵµÄ×óÉϽÇ×ø±êΪ£¨0£¬0£©¡£
¾ßÌå´úÂëΪ£º
from PIL import
Image
import matplotlib.pyplot as plt
import numpy as np
image = Image.open('test.jpg')
box = (500, 500, 1000, 1000)
region = image.crop(box)
data = np.array(region)
plt.imshow(data)
plt.show() |
µÃµ½µÄ½á¹ûΪ£º
µ÷Õû³ß´çºÍÐýת
Òªµ÷ÕûÒ»·ùͼÏñµÄ³ß´ç£¬ÎÒÃÇ¿ÉÒÔµ÷ÓÃresize()·½·¨¡£¸Ã·½·¨µÄ²ÎÊýÊÇÒ»¸öÔª×飬ÓÃÀ´Ö¸¶¨ÐÂͼÏñµÄ´óС£º
out = image.resize((32,32))
|
½á¹ûΪÏÂͼËùʾ£º
ÒªÐýתһ·ùͼÏñ£¬¿ÉÒÔʹÓÃÄæÊ±Õ뷽ʽ±íʾÐýת½Ç¶È£¬È»ºóµ÷ÓÃrotate()·½·¨£º
½á¹ûΪÏÂͼËùʾ£º
|