On 27 Feb 2014, at 07:41, Vighnesh Birodkar <vighneshbirodkar@gmail.com> wrote:

Hello

I am applying as a GSoC student for scikit-image this year. Last year I was a GSoC student for SimpleCV. To start contributing I wanted to implement Blob Detection ( DOG and LOG initially ).

I wanted to have some guidelines as to where to put the code and how to structure it.Is there any piece of code lying around in scikit-image which I can use as a template for Blob Detection ?

I would put the new code inside a new .py file inside features. I think it would be a good idea to keep the prototypes identical for all blob detection algorithms. My first intuition is to return a class ( or a dictionary ) with some attributes set. Some blob detection algorithms may compute the area of the blobs as well while some might not. Or I can just return the (x,y) coordinates.

Please point out if I am mistaken somewhere.

Thanks Vighnesh

Hi Vighnesh, I think it would be great if blob detection became available in scikit-image! There’s a Python blob detection implementation by Axel Donath here: https://github.com/adonath/blob_detection/tree/master/blob_detection It needs tests / docstrings and probably the API can be improved, I just wanted to mention it in case it could be a useful starting point. I’m not a scikit-image dev, so I can’t comment on what the appropriate location and API would be, but please CC us (@cdeil, @adonath) when you create a github issue or pull request for this. Cheers, Christoph

Hi Vighnesh, I'm not familiar with blob detection algorithms, but I will say that in general in scikit-image we try to shy away from new classes, and prefer to represent things with numpy arrays wherever possible. I think an integer image with one labeled region per blob would be appropriate (and could be piped into regionprops). Juan. On Thu, Feb 27, 2014 at 5:41 PM, Vighnesh Birodkar < vighneshbirodkar@gmail.com> wrote:

Hello

I am applying as a GSoC student for scikit-image this year. Last year I was a GSoC student for SimpleCV. To start contributing I wanted to implement Blob Detection ( DOG and LOG initially ).

I wanted to have some guidelines as to where to put the code and how to structure it.Is there any piece of code lying around in scikit-image which I can use as a template for Blob Detection ?

I would put the new code inside a new .py file inside features. I think it would be a good idea to keep the prototypes identical for all blob detection algorithms. My first intuition is to return a class ( or a dictionary ) with some attributes set. Some blob detection algorithms may compute the area of the blobs as well while some might not. Or I can just return the (x,y) coordinates.

Please point out if I am mistaken somewhere.

Thanks Vighnesh

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