# Quick Test for "are images in the same space" aka "overalpping" (SimpleITK)?
**URL:** https://discourse.itk.org/t/quick-test-for-are-images-in-the-same-space-aka-overalpping-simpleitk/5249
**Category:** Algorithms
**Tags:** python, simpleitk
**Created:** [August 8, 2022, 6:56pm UTC](https://discourse.itk.org/t/quick-test-for-are-images-in-the-same-space-aka-overalpping-simpleitk/5249 "2022-08-08T18:56:59Z")
**Posts on this page:** 8
**Page:** 1
### Author:  [@gdevenyi](https://discourse.itk.org/u/gdevenyi)
#### Post date: [August 8, 2022, 6:56pm UTC](https://discourse.itk.org/t/quick-test-for-are-images-in-the-same-space-aka-overalpping-simpleitk/5249/1 "2022-08-08T18:56:59Z")
If I have a collection of images and I’d like to quickly check that they’re “overlapping”, that is, have the same origin, pixel dimensions and direction cosines, is there a filter/test which does this other than comparing the GetSpacing(), GetOrigin() and GetDirection() vectors directly?
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### Author:  [@zivy](https://discourse.itk.org/u/zivy)
#### Post date: [August 8, 2022, 7:21pm UTC](https://discourse.itk.org/t/quick-test-for-are-images-in-the-same-space-aka-overalpping-simpleitk/5249/2 "2022-08-08T19:21:26Z")
Hello @gdevenyi,
Here’s what I do (it isn’t the nicest code in the world but maintains consistency with the internals of ITK/SimpleITK):
```auto
if not np.array_equal(np.array(image1.GetSize()), np.array(image2.GetSize())):
raise ValueError("Sizes don't match")
image1_proxy = image1[0:1,0:1,0:1]
image2_proxy = image2[0:1,0:1,0:1]
try: # comparison of origin, spacing and direction using ITK/SimpleITK epsilon
image1_proxy + image2_proxy
except Exception:
raise ValueError("Origin, spacing or direction do not match.")
```
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### Author:  [@gdevenyi](https://discourse.itk.org/u/gdevenyi)
#### Post date: [August 8, 2022, 7:26pm UTC](https://discourse.itk.org/t/quick-test-for-are-images-in-the-same-space-aka-overalpping-simpleitk/5249/3 "2022-08-08T19:26:19Z")
Ha! That’s a very clever hack relying on the exception checks inside SimpleITK to achieve it.
I don’t think this will work out for me, as I want to avoid loading the image data as there could be a large number of high resolution images, and I need to test each one before I go downstream with my processing choices. Thanks for the suggestion!
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### Author:  [@zivy](https://discourse.itk.org/u/zivy)
#### Post date: [August 8, 2022, 7:38pm UTC](https://discourse.itk.org/t/quick-test-for-are-images-in-the-same-space-aka-overalpping-simpleitk/5249/4 "2022-08-08T19:38:05Z")
Still doable if the file format supports streaming:
```auto
file_reader = sitk.ImageFileReader()
file_reader.SetFileName(file_name1)
file_reader.ReadImageInformation()
image1_size = np.array(file_reader.GetSize())
# read the first voxel to get the image's origin, spacing, direction cosine
file_reader.SetExtractIndex([0,0,0])
file_reader.SetExtractSize([1,1,1])
image1_proxy = file_reader.Execute()
```
If it doesn’t support streaming, then you’ll just have to read the image information and construct the “proxy” images from that information.
---
### Author:  [@dzenanz](https://discourse.itk.org/u/dzenanz)
#### Post date: [August 8, 2022, 8:04pm UTC](https://discourse.itk.org/t/quick-test-for-are-images-in-the-same-space-aka-overalpping-simpleitk/5249/5 "2022-08-08T20:04:44Z")
> [@zivy](#):
>
> read the image information and construct the “proxy” images
… and that might be more trouble than directly comparing size, spacing, origin and direction. Invoking code in [ImageToImageFilter::VerifyInputInformation()](https://github.com/InsightSoftwareConsortium/ITK/blob/v5.3rc04/Modules/Core/Common/include/itkImageToImageFilter.hxx#L146-L223) is probably not feasible, but stealing code from it totally is 😃
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### Author:  [@gdevenyi](https://discourse.itk.org/u/gdevenyi)
#### Post date: [August 8, 2022, 8:25pm UTC](https://discourse.itk.org/t/quick-test-for-are-images-in-the-same-space-aka-overalpping-simpleitk/5249/6 "2022-08-08T20:25:34Z")
Since I’m already using numpy, I went with this test in my reader loop
```python
if not (np.allclose(img.GetSpacing(), reader.GetSpacing(), atol=1e-6) and
np.allclose(img.GetOrigin(), reader.GetOrigin(), atol=1e-6) and
np.allclose(img.GetDirection(), reader.GetDirection())):
```
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### Author:  [@lassoan](https://discourse.itk.org/u/lassoan)
#### Post date: [August 8, 2022, 8:53pm UTC](https://discourse.itk.org/t/quick-test-for-are-images-in-the-same-space-aka-overalpping-simpleitk/5249/7 "2022-08-08T20:53:01Z")
There are good reasons why `ImageToImageFilter::VerifyInputInformation()` is so complex. The proposed simple check (based on a fixed absolute tolerance value) will cause trouble by either incorrectly rejecting some images that have actually matching geometries or not catching some actual mismatches.
The current `ImageToImageFilter::VerifyInputInformation()` implementation should be exposed in Python, otherwise it would be very hard to ensure consistent behavior.
---
### Author:  [@gdevenyi](https://discourse.itk.org/u/gdevenyi)
#### Post date: [August 8, 2022, 9:10pm UTC](https://discourse.itk.org/t/quick-test-for-are-images-in-the-same-space-aka-overalpping-simpleitk/5249/8 "2022-08-08T21:10:49Z")
Issue opened, [Expose ImageToImageFilter::VerifyInputInformation() as a usable True/False function · Issue #3536 · InsightSoftwareConsortium/ITK · GitHub](https://github.com/InsightSoftwareConsortium/ITK/issues/3536)