Updated GSOC Ideas (markdown)

Alex Clark ☺ 2014-02-14 01:56:53 -08:00
parent 3885690d5a
commit bcb65a3469

@ -6,7 +6,7 @@ _From Prashant Shrivastava, a potential GSOC participant who contacted Alex Clar
> Sir, First of all i would like to thank you for developing a very good Imaging Library for Python. It works wonders. I have been using the "Pillow" for a while now as my current project deals with computer vision and image processing. It has helped me alot and i would like to contribute to its development and get it more recognition. There are libraries like opencv which are more famous due its portability on different platforms. I feel that if a proper documentation in form a book with examples are provided to a budding user then more and more programmers will be attracted to this very good library. I was wondering if the "Pillow" is going to provide mentor-ship for a GSOC project. It would be very well recognized platform to showcase the power of image processing through python. I eagerly await your response and views about my idea. Regards, Prashant > Sir, First of all i would like to thank you for developing a very good Imaging Library for Python. It works wonders. I have been using the "Pillow" for a while now as my current project deals with computer vision and image processing. It has helped me alot and i would like to contribute to its development and get it more recognition. There are libraries like opencv which are more famous due its portability on different platforms. I feel that if a proper documentation in form a book with examples are provided to a budding user then more and more programmers will be attracted to this very good library. I was wondering if the "Pillow" is going to provide mentor-ship for a GSOC project. It would be very well recognized platform to showcase the power of image processing through python. I eagerly await your response and views about my idea. Regards, Prashant
## Speed ## Performance
Investigate speeding up core operations by vectorizing core functionality. This could be a combination of autovectorization in the compiler, manual recoding of tight loops in vector form, or writing kernels for OpenCL. Investigate speeding up core operations by vectorizing core functionality. This could be a combination of autovectorization in the compiler, manual recoding of tight loops in vector form, or writing kernels for OpenCL.