hugin-devs team mailing list archive

[Neolexious <seven211690@xxxxxxxxxxx>]

Public bug reported:

I had a project where automatic control point creation managed to
connect virtually all overlapping images together, but stitching was
rendered impossible due to each image also having a high number of low
quality connections with completely unrelated images.

Example 1 - low quality control points: http://i.imgur.com/weP0mRG.png
Example 2 - note that none of the images with less than six control points actually overlap: http://i.imgur.com/5igA2VZ.png
Example 3 - the best stitch I could get using built-in cp cleaning and optimization tools: http://i.imgur.com/dSm7LFW.png

By writing a python script to delete all control points between any
image pairs with a lower-than-typical control point count, I managed to
get it to stitch properly.

http://i.imgur.com/ycUqr30.png
http://i.imgur.com/qsHhv6r.png

** Affects: hugin
     Importance: Undecided
         Status: New

** Attachment added: "Screenshot from 2015-09-25 12-43-47.png"
   https://bugs.launchpad.net/bugs/1499871/+attachment/4474831/+files/Screenshot%20from%202015-09-25%2012-43-47.png

** Description changed:

  I had a project where automatic control point creation managed connect
  virtually all overlapping images together, but stitching was rendered
  impossible due to each image also having a high number of low quality
  connections with completely unrelated images.
  
  Example 1 - low quality control points: http://i.imgur.com/weP0mRG.png
- Example 2 - note that none of the images with only a few control points actually overlap: http://i.imgur.com/5igA2VZ.png
+ Example 2 - note that none of the images with less than six control points actually overlap: http://i.imgur.com/5igA2VZ.png
  Example 3 - the best stitch I could get using built-in cp cleaning and optimization tools: http://i.imgur.com/dSm7LFW.png
  
- 
- By writing a python script to delete all control points between any image pairs with a lower-than-typical control point count, I managed to get it to stitch properly.
+ By writing a python script to delete all control points between any
+ image pairs with a lower-than-typical control point count, I managed to
+ get it to stitch properly.
  
  http://i.imgur.com/ycUqr30.png
  http://i.imgur.com/qsHhv6r.png

** Attachment removed: "Screenshot from 2015-09-25 12-43-47.png"
   https://bugs.launchpad.net/hugin/+bug/1499871/+attachment/4474831/+files/Screenshot%20from%202015-09-25%2012-43-47.png

** Description changed:

- I had a project where automatic control point creation managed connect
- virtually all overlapping images together, but stitching was rendered
- impossible due to each image also having a high number of low quality
- connections with completely unrelated images.
+ I had a project where automatic control point creation managed to
+ connect virtually all overlapping images together, but stitching was
+ rendered impossible due to each image also having a high number of low
+ quality connections with completely unrelated images.
  
  Example 1 - low quality control points: http://i.imgur.com/weP0mRG.png
  Example 2 - note that none of the images with less than six control points actually overlap: http://i.imgur.com/5igA2VZ.png
  Example 3 - the best stitch I could get using built-in cp cleaning and optimization tools: http://i.imgur.com/dSm7LFW.png
  
  By writing a python script to delete all control points between any
  image pairs with a lower-than-typical control point count, I managed to
  get it to stitch properly.
  
  http://i.imgur.com/ycUqr30.png
  http://i.imgur.com/qsHhv6r.png

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https://bugs.launchpad.net/bugs/1499871

Title:
  Add feature to dissociate image pairs based off of total control point
  count

Status in Hugin:
  New

Bug description:
  I had a project where automatic control point creation managed to
  connect virtually all overlapping images together, but stitching was
  rendered impossible due to each image also having a high number of low
  quality connections with completely unrelated images.

  Example 1 - low quality control points: http://i.imgur.com/weP0mRG.png
  Example 2 - note that none of the images with less than six control points actually overlap: http://i.imgur.com/5igA2VZ.png
  Example 3 - the best stitch I could get using built-in cp cleaning and optimization tools: http://i.imgur.com/dSm7LFW.png

  By writing a python script to delete all control points between any
  image pairs with a lower-than-typical control point count, I managed
  to get it to stitch properly.

  http://i.imgur.com/ycUqr30.png
  http://i.imgur.com/qsHhv6r.png

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