Use Python to compare two different pictures

 fromPILImportImage fromPILImportImagechopsdefcompare_images (Path_one, Path_two, diff_save_location):"""Compare pictures, if there are different then generate show different pictures @ parameter one: Path_one: The path of the first picture @ parameter two: path_two: The path of the second picture @ parameter three: diff_save_location: Save road of different graphs Diameter"""Image_one=Image.open (path_one) image_two=Image.open (path_two)Try: diff=imagechops.difference (Image_one, Image_two)ifDiff.getbbox () isNone:#There's no difference between the pictures, just exit .            Print(""+" We are the same!")        Else: Diff.save (diff_save_location)exceptValueError as E:text= ("indicates that the picture size is inconsistent with the width of box, refer to API Description: Pastes another image to this image."                "The box argument is either a 2-tuple giving the upper left corner, a 4-tuple defining the left, Upper,"                "Right , and lower pixel coordinate, or None (same as (0, 0)). If a 4-tuple is given, the size of the pasted"                "image must match the size of the region. Use the 2-weft box to avoid the above problems")        Print("' {0} ' {1}". Format (e,text))if __name__=='__main__': Compare_images ('1.png',                   '2.png',                   'we're not the same. png')

Execution Result:

    

The second method:

 fromPILImportImageImportMathImportoperator fromFunctoolsImportReducedefimage_contrast (IMG1, Img2): Image1=Image.open (IMG1) image2=Image.open (IMG2) H1=Image1.histogram () H2=Image2.histogram () result= Math.sqrt (Reduce (Operator.add, list (map) (LambdaB: (a) **2, H1, H2))/Len (H1))returnresultif __name__=='__main__': Img1="./1.png"  #Specify picture PathImg2 ="./2.png"result=image_contrast (IMG1,IMG2)Print(Result)

If the two pictures are exactly equal, the returned result is a floating-point type of "0.0", and if not, the larger the result value is returned.

Also use the above two pictures, the execution result is 38, or relatively small:

 Image

This allows you to invoke the method in an automated test case to assert the result of the execution.

Detailed documentation on the Pillow Library:

Http://pillow.readthedocs.org/en/latest/index.html

Use Python to compare two different pictures