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Feature Requests / Re: Multiple-Camera Rig with Python API
« on: November 21, 2023, 07:00:37 PM »
Thanks a lot Alexey, i will try this soon.
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Feature Requests / Multiple-Camera Rig with Python API
« on: November 21, 2023, 03:33:16 PM »
Hello,
i'm using a Stereo camera rig and i'm using Metashape in order to process models.
At this time, here is the process i follow:
1. Set up on my hard drive a folder named "images" that contains 2 sub-folders named "SL" that contains the left images and "SR" that contains the right images from my stereo system (each left / right image of a stereo pair have the same filename).
2. Open Metashape
1. Create a chunk
2. Click on Workflow -> Add Folder and select the images folder that contains SL and SR subfolder
3. Metashape is detecting that the folder contain a stereo camera rig
4. Click on "Tools -> Camera calibration"
5. Within the new windows, click on the second camera and select the "Slave" pane
6. Within the pane, set up the X, Y, Z, O, P, K values
7. Click on Workflow -> Align Photos
My question is that i would like to automatize the chunk preparation (from a given folder and a given slave calibration, i would like that the steps 1-6 of the process be achieved automatically). However, i've not be able to find any function related to stereo or multiple camera rig processing within the Python or Java API.
Is it possible to integrate these functionnalities within the API ?
Thanks a lot.
i'm using a Stereo camera rig and i'm using Metashape in order to process models.
At this time, here is the process i follow:
1. Set up on my hard drive a folder named "images" that contains 2 sub-folders named "SL" that contains the left images and "SR" that contains the right images from my stereo system (each left / right image of a stereo pair have the same filename).
2. Open Metashape
1. Create a chunk
2. Click on Workflow -> Add Folder and select the images folder that contains SL and SR subfolder
3. Metashape is detecting that the folder contain a stereo camera rig
4. Click on "Tools -> Camera calibration"
5. Within the new windows, click on the second camera and select the "Slave" pane
6. Within the pane, set up the X, Y, Z, O, P, K values
7. Click on Workflow -> Align Photos
My question is that i would like to automatize the chunk preparation (from a given folder and a given slave calibration, i would like that the steps 1-6 of the process be achieved automatically). However, i've not be able to find any function related to stereo or multiple camera rig processing within the Python or Java API.
Is it possible to integrate these functionnalities within the API ?
Thanks a lot.
3
Python and Java API / Autonomous Metashape Java Wrapper with MAVEN
« on: July 28, 2022, 06:32:06 PM »
Hello,
I've released a Metashape(c) Java wrapper that is compliant with Maven projects. The aim of this bundle is to provide a way for java developers to integrate Aghisoft Metashape(c) processing into various java projects that are managed with Maven.
More over, this bundle is autonomous: it embeds all required native libraries for systems that are supported by Metashape and deploy and load them in an autonomous way, without the need of managing the libraries.
for more information you can check the github repository of the project: https://github.com/jseinturier/metashape-java-maven.
At this time, bundles are available from Metashape 1.7.6 to 1.8.4.
Hope it will be helpfull.
I've released a Metashape(c) Java wrapper that is compliant with Maven projects. The aim of this bundle is to provide a way for java developers to integrate Aghisoft Metashape(c) processing into various java projects that are managed with Maven.
More over, this bundle is autonomous: it embeds all required native libraries for systems that are supported by Metashape and deploy and load them in an autonomous way, without the need of managing the libraries.
for more information you can check the github repository of the project: https://github.com/jseinturier/metashape-java-maven.
At this time, bundles are available from Metashape 1.7.6 to 1.8.4.
Hope it will be helpfull.
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