3pp-mirror/Meshroom
1
0
Fork 0
mirror of https://github.com/alicevision/Meshroom.git synced 2025-06-04 11:51:58 +02:00
Code Issues Projects Releases Packages Wiki Activity

[nodes] ImageMatching: add option FrustumOrVocabularyTree

Browse source
This commit is contained in:
Fabien Castan 2020-03-26 20:51:37 +01:00
parent bb683b6e32
commit 6a62644a68
2 changed files with 14 additions and 3 deletions
Download patch file Download diff file Expand all files Collapse all files

3
meshroom/multiview.py
View file

@ -152,7 +152,8 @@ def hdriPipeline(graph):
imageMatching = graph.addNewNode('ImageMatching', imageMatching = graph.addNewNode('ImageMatching',
input=panoramaInit.outSfMDataFilename, input=panoramaInit.outSfMDataFilename,
featuresFolders=[featureExtraction.output]) featuresFolders=[featureExtraction.output],
method='FrustumOrVocabularyTree')
featureMatching = graph.addNewNode('FeatureMatching', featureMatching = graph.addNewNode('FeatureMatching',
input=imageMatching.input, input=imageMatching.input,
featuresFolders=imageMatching.featuresFolders, featuresFolders=imageMatching.featuresFolders,

14
meshroom/nodes/aliceVision/ImageMatching.py
View file

@ -25,6 +25,8 @@ Combines sequential approach with Voc Tree to enable connections between keyfram
Export all image pairs. Export all image pairs.
* **Frustum** * **Frustum**
If images have known poses, computes the intersection between cameras frustums to create the list of image pairs. If images have known poses, computes the intersection between cameras frustums to create the list of image pairs.
* **FrustumOrVocabularyTree**
If images have known poses, use frustum intersection else use VocabularuTree.
## Online ## Online
[https://alicevision.org/#photogrammetry/image_matching](https://alicevision.org/#photogrammetry/image_matching) [https://alicevision.org/#photogrammetry/image_matching](https://alicevision.org/#photogrammetry/image_matching)
@ -53,9 +55,17 @@ If images have known poses, computes the intersection between cameras frustums t
desc.ChoiceParam( desc.ChoiceParam(
name='method', name='method',
label='Method', label='Method',
description='Method used to select the image pairs to match.', description='Method used to select the image pairs to match:\n'
' * VocabularyTree: It uses image retrieval techniques to find images that share some content without the cost of resolving all \n'
'feature matches in details. Each image is represented in a compact image descriptor which allows to compute the distance between all \n'
'images descriptors very efficiently. If your scene contains less than "Voc Tree: Minimal Number of Images", all image pairs will be selected.\n'
' * Sequential: If your input is a video sequence, you can use this option to link images between them over time.\n'
' * SequentialAndVocabularyTree: Combines sequential approach with VocTree to enable connections between keyframes at different times.\n'
' * Exhaustive: Export all image pairs.\n'
' * Frustum: If images have known poses, computes the intersection between cameras frustums to create the list of image pairs.\n'
' * FrustumOrVocabularyTree: If images have known poses, use frustum intersection else use VocabularuTree.\n',
value='VocabularyTree', value='VocabularyTree',
values=['VocabularyTree', 'Sequential', 'SequentialAndVocabularyTree','Exhaustive','Frustum'], values=['VocabularyTree', 'Sequential', 'SequentialAndVocabularyTree', 'Exhaustive', 'Frustum', 'FrustumOrVocabularyTree'],
exclusive=True, exclusive=True,
uid=[0], uid=[0],
), ),