scikit-image February 2019

scikit-image@python.org

5 participants
4 discussions

Scikit Blob detection, Not properly working on 3D image
by Francesco Alemanno 15 May '19

15 May '19

Hello everyone, recently (and for the first time) i had to deal with image processing, my problem is detecting sferical blobs in a 3D grayscale image shaped like this (20,1000,1000). So i looked inside scikit, and i found the function blob_dog&log&doh (the three main algorithms), the procedure is working perfectly for the X and Y coordinates (x,y in [0,1000]x[0,1000]) but failing miserably at identifying the correct Z coord (Z in [0,20]). I think this has to do with: the blobs occupy rougly 30x30 pixels in X,Y, but only 3/4 pixels in Z (since my 3D images have to be taken with a lower resolution in Z). Moreover the algorithms apparently use isotropic gaussian filtering so the variance is the same in all directions (at a given sigma scale) according to the algorithm (Unfortunately not according to my data). Is there any reasonable/sane way to fix for this? What do you guys suggest?

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graph MCP_Flexible
by Rafael Carlquist Rabelo de Araujo 18 Mar '19

18 Mar '19

Hello everyone, I was hoping to get some advice on dealing with the MCP_flexible class. Sorry if the e-mail is too big, I tried to be as clear as possible. I will use an example that I think will help me explaining the problem. I have a road network and a subway network in a raster format and I want to calculate least cost paths on them. To simplify it, consider this small example: ------------------------------------------------------------------------------------------------------------------------------- # Piece of code (1) # (1) Roads network: roads = np.array([[2,5,10,10,10],[10,5,10,10,10],[10,5,10,10,10],[10,5,10,10,10], [10,5,10,10,10],[10,5,10,10,10],[10,5,10,10,10],[10,5,10,10,10], [10,5,10,10,10],[10,5,10,10,10],[10,5,10,10,10],[10,5,5,5,2]]) #The idea here is that 5 denotes a road, 10 denotes a place where you can walk and 2 denotes #a subway station. # (2) Subway network: subway = np.array([[1,-1,-1,-1,-1],[-1,1,-1,-1,-1],[-1,-1,1,-1,-1],[-1,-1,-1,1,-1], [-1,-1,-1,1,-1],[-1,-1,-1,1,-1],[-1,-1,-1,1,-1],[-1,-1,-1,1,-1], [-1,-1,-1,1,-1],[-1,-1,-1,1,-1],[-1,-1,-1,1,-1],[-1,-1,-1,-1,1]]) # here the value 1 denotes a piece of the subway and the value -1 denotes a cell you cannot reach. # So, my whole network is given by: network = np.array([roads,subway]) # End of piece of code (1) ------------------------------------------------------------------------------------------------------------------------------- This I my input, and what I want to do is to calculate least cost path between the point (0,0,1) and (0,11,4). Why can't I use MCP or MCP_Geometric? Because I want to allow my agent to enter the subway only by going through a subway station. My solution so far is to use MCP_flexible and overload the 'travel_cost' method. ------------------------------------------------------------------------------------------------------------------------------ # Piece of code (2) # First, I write a offset that constraints moves in the third dimension (I want diagonal moves if #the agent is walking on the roads network or on the subway network, but not when he is #moving across those networks) offsets = [np.array([-1, 0, 0]), np.array([ 0, -1, -1]), np.array([ 0, -1, 0]), np.array([ 0, -1, 1]), np.array([ 0, 0, -1]), np.array([0, 0, 1]), np.array([ 0, 1, -1]), np.array([0, 1, 0]), np.array([0, 1, 1]), np.array([1, 0, 0])] # Second, I create my own class, overloading the 'travel_cost' method: @cython.boundscheck(True) @cython.wraparound(True) class MCP_subway(skimg.MCP_Flexible): def travel_cost(self, old_cost, new_cost, offset_length): """ travel_cost(old_cost, new_cost, offset_length) This method calculates the travel cost for going from the current node to the next. In this method, if an agent tries to go from road to subway or from subway to road without going through a subway station he gets a infinity cost. """ if (new_cost == 1 and old_cost not in [1,2]) or (old_cost == 1 and new_cost not in [1,2]): return np.inf else: return new_cost # End of piece of code (2) ------------------------------------------------------------------------------------------------------------------------------ So far it gave me the correct answer, but I want to use it with bigger problems. So my questions are: (1) Am I doing it right? I do not know Cython very well, so I overloaded the 'travel_cost' method with a method in pure python. (2) Does anyone have a better idea to solve this problem? Reading suggestions? Thank you very much, Best regards, Rafael

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Re: Regarding new working implementation of BM3D preferrably in Matlab
by Stefan van der Walt 08 Feb '19

08 Feb '19

Hi Zaied, On Fri, 08 Feb 2019 19:27:49 +0000, Zaied Zaman wrote: > Do any one is currently working in BM3D? If anyone is, do you have any > perfectly working implementation of BM3D, preferably, in Matlab, can > you kindly share if you have? I am not aware of any such efforts, although it would certainly be of interest. It is on our list of requested features: https://github.com/scikit-image/scikit-image/wiki/Requested-features Best regards, Stéfan

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Regarding new working implementation of BM3D preferrably in Matlab
by Zaied Zaman 08 Feb '19

08 Feb '19

Hello, Do any one is currently working in BM3D? If anyone is, do you have any perfectly working implementation of BM3D, preferably, in Matlab, can you kindly share if you have? Please accept my apology if i did any mistake regarding this post. Thanks, Z

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scikit-image February 2019