Areas of contours

Wed Sep 10 10:08:30 EDT 2014

Forget what I said, that’s certainly not the area, but can you show some code for that, please?

Johannes Schönberger

On Sep 10, 2014, at 10:07 AM, Johannes Schönberger <jsch at demuc.de> wrote:

> How do you calculate the are in case of the 0.13 seconds? Just the sum of the True pixels?
> 
> Johannes Schönberger
> 
> On Sep 10, 2014, at 10:05 AM, Maik Riechert <maik.riechert at arcor.de> wrote:
> 
>> I just did a test on a 3000x3000 image comparing both approaches. Note that I have very few (one to three) contours where there is one big that is typically 50-70% of the whole image. My contour-only way takes 0.13secs, the other one that you suggested takes 4secs where 95% of the time is spent on accessing the area property of a single region prop. Why is that so slow?
>> 
>> Am Mittwoch, 10. September 2014 15:26:43 UTC+2 schrieb Juan Nunez-Iglesias:
>> p.image contains an image of just that one region, within bbox. Note that regionprops have lazy evaluation, so the code mentioned above should be reasonably fast — possibly faster than evaluating contours for the whole image first. Also note that unless you port it to Cython, your area function on the contours will be pretty slow.
>> —
>> Sent from Mailbox
>> 
>> 
>> On Wed, Sep 10, 2014 at 11:20 PM, Maik Riechert <maik.r... at arcor.de> wrote:
>> 
>> Hi Juan,
>> 
>> how would I do step 5? Even if I know the bounding box it could still be that parts of other regions are in the box, right?
>> 
>> I'm not sure if all that would be a bit too slow if it worked. My images are 4000x3000 and I guess there's a noticeable performance advantage of doing all further calculations just on the contours instead of the image itself.
>> 
>> Cheers
>> Maik
>> 
>> Am Mittwoch, 10. September 2014 15:04:27 UTC+2 schrieb Juan Nunez-Iglesias:
>> Hey Maik,
>> 
>> But what about:
>> 
>> 1) Do a scipy.ndimage.binary_fill_holes to ensure that objects constitute the full area from a contour
>> 2) Do a scipy.ndimage.label to give a unique ID to each blob of 1s in the image.
>> 3) get props = skimage.regionprops(im) to get the properties of each blob
>> 4) you can then find the argmax of [p.area for p in props]
>> 5) you can then compute the contour of just that object, and offset the coordinates using the .bbox property
>> 
>> Would this work? It all depends on your purposes, and I’m also not sure which would be most efficient.
>> 
>> Juan.
>> —
>> Sent from Mailbox
>> 
>> 
>> On Wed, Sep 10, 2014 at 10:29 PM, Maik Riechert <maik.r... at arcor.de> wrote:
>> 
>> My goal is to determine the biggest contour that covers 1's in the binary image and return it, therefore I thought I first use find_contours and then calculate the area of each contour to get the right one. I'm not sure if regionprops helps me here. In the meantime I adapted a function from stackoverflow:
>> 
>> def polygonArea(poly):
>>    """
>>    Return area of an unclosed polygon.
>> 
>>    :see: https://stackoverflow.com/a/451482
>>    :param poly: (n,2)-array
>>    """
>>    # we need a plain list for the following operations
>>    if isinstance(poly, np.ndarray):
>>        poly = poly.tolist()
>>    segments = zip(poly, poly[1:] + [poly[0]])
>>    return 0.5 * abs(sum(x0*y1 - x1*y0
>>                         for ((x0, y0), (x1, y1)) in segments))
>> 
>> Before using that function I un-close the returned contours.
>> 
>> Cheers
>> Maik
>> 
>> Am Mittwoch, 10. September 2014 11:43:59 UTC+2 schrieb Juan Nunez-Iglesias:
>> Hey Maik,
>> 
>> Can you be a bit more specific? The pipeline may need to be a bit different, but this seems doable. In particular, regionprops(image)[i].area will return the area of all binary-labeled regions.
>> 
>> If that doesn’t help, if you have an example image with code it might be easier to translate your workflow.
>> 
>> Note that we don’t attempt to offer feature parity with OpenCV, which has a lot of hard computer vision algorithms that we lack. But this in particular should be doable.
>> 
>> Juan.
>> —
>> Sent from Mailbox
>> 
>> 
>> On Wed, Sep 10, 2014 at 7:40 PM, Maik Riechert <maik.r... at arcor.de> wrote:
>> 
>> Hi,
>> 
>> I'm currently switching from OpenCV to scikit-image and came to a point where I miss a certain feature.
>> 
>> In OpenCV I used findContours() and then contourArea() to calculate the area of each contour. I couldn't find this in scikit-image. If I didn't miss it somewhere, could that be added as a new function?
>> 
>> Thanks
>> Maik
>> 
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