It was quick to convert the Python code into a tool that could be run with a simple double click. To test it rather than running it over and over in the Python environment I opted to convert it to an executable using py2exe.
PIL gives all of this and more and seemed to be incredibly quick at pixel sampling If there is no disparity a match has been found. As long as the values match then the compare continues until the end of the image is reached. I wanted to be able to open an image and then provided it's dimensions matched the source return the pixel RGB values based on a sample rate, for instance every tenth pixel. The links above give you enough to get you up and writing tools without much hassle and as all of the above are installers they will be setup automatically skipping the more complicated requirements of the PyQt manual install that includes fiddling with sip.Īs this tool was intended for finding duplicate images I needed an extra library referred to as Pil, Python imaging library. After some false starts I found a good combination that worked well for me although I guess that depending on requirements you may need different versions of the software. 64 Bit or 32 Bit? 2.7, 3.3, source, binary, exe, tar.blah, blah, blah. When I first approached the most confusing thing was looking at all the different versions of the software and libraries there were and working out which one was applicable. In the end I went for one that would find similar or the same images based on a source image giving you the option of checking or deleting the duplicates. For my first foray into the world of standalone applications I decided to write a simple tool with the aim of getting me used to things.
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