1. python处理图片数据
生成一张纯色的图片
先设置图片的颜色，接着利用Image模块的new方法新生成一张图片，png格式的图片需要设置成rgba，类似的还有rgb，L(灰度图等)，尺寸设定为640，480，这个可以根据自己的情况设定，颜色同样如此。
2. 用python写识别图片主要颜色的程序
#-*-coding:utf-8-*-
importcolorsys
defget_dominant_color(image):
#颜色模式转换，以便输出rgb颜色值
image=image.convert('RGBA')
#生成缩略图，减少计算量，减小cpu压力
image.thumbnail((200,200))
max_score=None
dominant_color=None
forcount,(r,g,b,a)inimage.getcolors(image.size[0]*image.size[1]):
#跳过纯黑色
ifa==0:
continue
saturation=colorsys.rgb_to_hsv(r/255.0,g/255.0,b/255.0)[1]
y=min(abs(r*2104+g*4130+b*802+4096+131072)>>13,235)
y=(y-16.0)/(235-16)
#忽略高亮色
ify>0.9:
continue
#Calculatethescore,.
#Add0.1tothesaturationsowedon'tcompletelyignoregrayscale
#,butstillgivethemalow
#weight.
score=(saturation+0.1)*count
ifscore>max_score:
max_score=score
dominant_color=(r,g,b)
returndominant_color
if__name__=="__main__":
fromPILimportImage
importos
path=r'.\pics\'
fp=open('file_color.txt','w')
forfilenameinos.listdir(path):
printpath+filename
try:
color=get_dominant_color(Image.open(path+filename))
fp.write('Thecolorof'+filename+'is'+str(color)+' ')
except:
print"Thisfileformatisnotsupport"
fp.close()
pics文件夹和python程序在一个目录下，产生的文件名file_color.txt也在这个目录下。
看看能否帮到你
3. python 如何只选中图片里的一种颜色 变更为另一个种颜色
importImage
img=Image.open("pic.jpg")
foriinxrange(300):
forjinxrange(300):
r,g,b=img.getpixel((i,j))
if(b>gandb>r):#对蓝色进行判断
b=127
g=127
r=127
img.putpixel((i,j),(r,g,b))
img.show()
4. 用python K值聚类识别图片主要颜色的程序，算法python代码已经有了
难得被人求助一次, 这个必须回答一下. 不过你的需求确实没有写得太清楚. 根据k值算法出来的是主要颜色有三个, 所以我把三个颜色都打在记事本里了. 如果和你的需求有误, 请自行解决吧.
另外这里需要用到numpy的库, 希望你装了, 如果没装, 这个直接安装也比较麻烦, 可以看一下portablepython的绿色版。
代码如下：
#-*-coding:utf-8-*-
importImage
importrandom
importnumpy
classCluster(object):
def__init__(self):
self.pixels=[]
self.centroid=None
defaddPoint(self,pixel):
self.pixels.append(pixel)
defsetNewCentroid(self):
R=[colour[0]forcolourinself.pixels]
G=[colour[1]forcolourinself.pixels]
B=[colour[2]forcolourinself.pixels]
R=sum(R)/len(R)
G=sum(G)/len(G)
B=sum(B)/len(B)
self.centroid=(R,G,B)
self.pixels=[]
returnself.centroid
classKmeans(object):
def__init__(self,k=3,max_iterations=5,min_distance=5.0,size=200):
self.k=k
self.max_iterations=max_iterations
self.min_distance=min_distance
self.size=(size,size)
defrun(self,image):
self.image=image
self.image.thumbnail(self.size)
self.pixels=numpy.array(image.getdata(),dtype=numpy.uint8)
self.clusters=[Noneforiinrange(self.k)]
self.oldClusters=None
randomPixels=random.sample(self.pixels,self.k)
foridxinrange(self.k):
self.clusters[idx]=Cluster()
self.clusters[idx].centroid=randomPixels[idx]
iterations=0
whileself.shouldExit(iterations)isFalse:
self.oldClusters=[cluster.centroidforclusterinself.clusters]
printiterations
forpixelinself.pixels:
self.assignClusters(pixel)
forclusterinself.clusters:
cluster.setNewCentroid()
iterations+=1
return[cluster.centroidforclusterinself.clusters]
defassignClusters(self,pixel):
shortest=float('Inf')
forclusterinself.clusters:
distance=self.calcDistance(cluster.centroid,pixel)
ifdistance<shortest:
shortest=distance
nearest=cluster
nearest.addPoint(pixel)
defcalcDistance(self,a,b):
result=numpy.sqrt(sum((a-b)**2))
returnresult
defshouldExit(self,iterations):
ifself.oldClustersisNone:
returnFalse
foridxinrange(self.k):
dist=self.calcDistance(
numpy.array(self.clusters[idx].centroid),
numpy.array(self.oldClusters[idx])
)
ifdist<self.min_distance:
returnTrue
ifiterations<=self.max_iterations:
returnFalse
returnTrue
#############################################
#
defshowImage(self):
self.image.show()
defshowCentroidColours(self):
forclusterinself.clusters:
image=Image.new("RGB",(200,200),cluster.centroid)
image.show()
defshowClustering(self):
localPixels=[None]*len(self.image.getdata())
foridx,pixelinenumerate(self.pixels):
shortest=float('Inf')
forclusterinself.clusters:
distance=self.calcDistance(
cluster.centroid,
pixel
)
ifdistance<shortest:
shortest=distance
nearest=cluster
localPixels[idx]=nearest.centroid
w,h=self.image.size
localPixels=numpy.asarray(localPixels)
.astype('uint8')
.reshape((h,w,3))
colourMap=Image.fromarray(localPixels)
colourMap.show()
if__name__=="__main__":
fromPILimportImage
importos
k_image=Kmeans()
path=r'.\pics\'
fp=open('file_color.txt','w')
forfilenameinos.listdir(path):
printpath+filename
try:
color=k_image.run(Image.open(path+filename))
fp.write('Thecolorof'+filename+'is'+str(color)+' ')
except:
print"Thisfileformatisnotsupport"
fp.close()