使用PIL和NumPy将图像转换为Lab数组,修改值,然后转换回 [英] Using PIL and NumPy to convert an image to Lab array, modify the values and then convert back
问题描述
我试图使用NumPy将PIL图像转换为数组。然后,我想将该数组转换为Lab值,修改值,然后将数组转换回图像并保存图像。我有以下代码:
import Image,color,numpy
#打开图像文件
src = Image.open(face-him.jpg)
#尝试确保图像是RGB
src = src.convert(mode =RGB)
#使用numpy创建图像数组
srcArray = numpy.asarray(src)
#将RGB数组转换为Lab
srcArray = color.rgb2lab srcArray)
#修改此处的数组
#将数组转换回Lab
end = color.lab2rgb(srcArray)
#Create image from array
final = Image.fromarray(end,RGB)
#保存
final.save(out.jpg)
此代码依赖于PIL,NumPy和颜色。颜色可以在SciPy树干中找到
测试所需的所有源文件 - colour-test.zip
没有尝试过,缩放错误在转换颜色时很常见:
RGB是字节0 .. 255,例如黄色[255,255,0],
,而 rgb2xyz()
等工作在三个浮点数,黄色[1.,1.,0]
( color.py
没有范围检查: lab2rgb(rgb2lab([255,255,0]))
是
在IPython中,%run main.py
,然后打印srcArray的两个角, / p>
添加13July:对于记录/ google,这里是NumPy成语,打包,解压缩和转换RGB图像数组:
#unpack image array,10 x 5 x 3 - > rgb -
img = np.arange(10 * 5 * 3).reshape((10,5,3))
printimg.shape:,img.shape
r, g,b = img.transpose(2,0,1)#3 10 5
printr.shape:,r.shape
#pack 10 x 5 rgb - 10 x 5 x 3再次
rgb = np.array((r,g,b))。transpose(1,2,0)#10 5 3再次
printrgb.shape: ,rgb.shape
assert(rgb == img).all()
#rgb 0 .. 255& float 0 .. 1 -
imgfloat = img.astype(np.float32)/ 255.
img8 =(imgfloat * 255).round()。astype(np.uint8)
assert(img == img8).all()
I am trying to convert a PIL image into an array using NumPy. I then want to convert that array into Lab values, modify the values and then convert the array back in to an image and save the image. I have the following code:
import Image, color, numpy
# Open the image file
src = Image.open("face-him.jpg")
# Attempt to ensure image is RGB
src = src.convert(mode="RGB")
# Create array of image using numpy
srcArray = numpy.asarray(src)
# Convert array from RGB into Lab
srcArray = color.rgb2lab(srcArray)
# Modify array here
# Convert array back into Lab
end = color.lab2rgb(srcArray)
# Create image from array
final = Image.fromarray(end, "RGB")
# Save
final.save("out.jpg")
This code is dependent on PIL, NumPy and color. color can be found in the SciPy trunk here. I downloaded the color.py file along with certain colordata .txt files. I modified the color.py so that it can run independently from the SciPy source and it all seems to work fine - values in the array are changed when I run conversions.
My problem is that when I run the above code which simply converts an image to Lab, then back to RGB and saves it I get the following image back:
What is going wrong? Is it the fact I am using the functions from color.py?
For reference:
Source Image - face-him.jpg
All source files required to test - colour-test.zip
Without having tried it, scaling errors are common in converting colors:
RGB is bytes 0 .. 255, e.g. yellow [255,255,0],
whereas rgb2xyz()
etc. work on triples of floats, yellow [1.,1.,0].
(color.py
has no range checks: lab2rgb( rgb2lab([255,255,0]) )
is junk.)
In IPython, %run main.py
, then print corners of srcArray and end ?
Added 13July: for the record / for google, here are NumPy idioms to pack, unpack and convert RGB image arrays:
# unpack image array, 10 x 5 x 3 -> r g b --
img = np.arange( 10*5*3 ).reshape(( 10,5,3 ))
print "img.shape:", img.shape
r,g,b = img.transpose( 2,0,1 ) # 3 10 5
print "r.shape:", r.shape
# pack 10 x 5 r g b -> 10 x 5 x 3 again --
rgb = np.array(( r, g, b )).transpose( 1,2,0 ) # 10 5 3 again
print "rgb.shape:", rgb.shape
assert (rgb == img).all()
# rgb 0 .. 255 <-> float 0 .. 1 --
imgfloat = img.astype(np.float32) / 255.
img8 = (imgfloat * 255).round().astype(np.uint8)
assert (img == img8).all()
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