great news with regards to OpenCV support...

[Chris Colbert]

So my next question is: how much hand holding should I do on my end
for the user?

There are several things I would like to address here:

- opencv makes extensive use of *out arguments, should we require the user to
  preallocate their out array or should we make it for them and return it.
  The latter option is more pythonic, but comes with a small overhead for
  determining a proper return dtype

- how much checking should I do on the input array. OpenCV images can accept
  6 different dtypes.  If the user passes an incorrect dtype, should I
raise an exception
  or just let it fail with a KeyError during the dtype lookup?

  How much checking should I do on the array dimensions. We can use 2D
or 3D arrays
  with the third dimension equal to 2, 3, or 4. Should I check that
the passed arrays conform to
  this, or just let everything fail? Again, how much validation
overhead should we allow


On the technical side, I'm wondering if I should INCREF the numpy
array when I pass it to OpenCV. If Python somehow gc'ed the array
while OpenCV is working on it, that could be nasty.  The only way I
see this happening is if I start releasing the GIL on opencv calls.
This brings the advantage of performance during threading but will not
at all be thread safe since I'm "borrowing" the numpy data pointer.

Cheers!

Chris

On Thu, Oct 8, 2009 at 10:59 PM, Zachary Pincus <zachary.pincus at yale.edu> wrote:
>
> Fantastic! This is great news.
>
>
> On Oct 8, 2009, at 3:37 PM, Chris Colbert wrote:
>
>> At least I think it is great!
>>
>> I've managed (with the help of the community) to get ctypes function
>> pointers to play nice with cython.
>>
>> I've also re-implented the IplImage struct in cython and figured out
>> how to populate the struct with numpy stride information and the numpy
>> data pointer.
>>
>> This all means that we now have the ability to to call OpenCV
>> functions with plain numpy arrays as arguments, and the array gets
>> modified in place!. And since i'm using ctypes to grab the function
>> handle, OpenCV is not required to be on the users machine during build
>> time, but if and when  they install the opencv lib, they automagically
>> work!
>>
>> I've a got a working (albeit ugly) example attached. You'll obviously
>> need opencv installed if you want to test it.
>>
>> Just use PIL to open any image on your system then dump it into a
>> numpy array then call testnumpy.test(arr) on that array.
>>
>> Dump the array back into a PIL image and call show() on it. Voila!
>> your image has been guassianed blurred courtesy of OpenCV.
>>
>>
>> So, now that I have the logistics of this figured out and I know it
>> actually works, looks like I'll have plenty to implement during the
>> upcoming sprint.
>>
>> Cheers!
>>
>> Chris
>> <testnumpy.pyx>
>
>