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Thursday, 30 September 2010

Python Photogrammetry Toolbox

This project intend to create a python photogrammetry toolbox.
It provides an easy interface to run Bundler + Dense point cloud computation via PMVS2 and CMVS (as WIP).

The main drawbacks of Bundler is that people have to install cygwin to use it and windows.
The advantage of Python is that the scripting langage is multiplatform, so the same code will be ok to run Bundler and the other tools on windows, linux and mac ! No more cygwin... installation.

This project make the Sift detector from VLFeat library works with Bundler. So the toolchain is OpenSource from A to Z. Other modules could be plug into because of the modularity approach that have been choosen.

In a near future we could think in integrate a SIFTGpu matcher into the toolchain.

Running example :
Perform point cloud and camera calibration :
  • $ RunBundler.py --photos="./examples/MyPhotos"

Perform dense 3D point cloud computation :
  • $ RunPMVS.py --bundlerOutputPath="C:/temp/PreviousLineTempDirectoryPath"
Perform dense 3D point could computation by using Cluster 3D representation of the scene :
  • $ RunCMVS.py --bundlerOutputPath="C:/temp/PreviousLineTempDirectoryPath"

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  3. Hi, thanks for making this. I can see a lot of potential. But I have a problem with Bundler only generating a only few cameras instead of all of them. I have ran it multiple times and the cameras it chooses are random. Im running 64bit software and have 32GB ram. Sift also crashes when I use images above 2700 pixels. This all seem pretty buggy to me. Any suggestions? The images seem to work fine in Agisoft photoscan.

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  126. Creating a Python-based photogrammetry toolbox is a brilliant initiative, making complex tasks more accessible and cross-platform. Eliminating the need for cygwin simplifies the process, and the modularity approach promises versatility. Exciting prospects for enhancing photogrammetry workflows!
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  127. Hello Blogger,
    This Python Photogrammetry Toolbox is a game-changer for photogrammetry enthusiasts. Its multiplatform compatibility and elimination of cygwin make it accessible and efficient. The inclusion of open-source components and potential SIFTGpu integration promise even greater capabilities. It is a remarkable project.
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  128. This toolset is revolutionary! I appreciate you giving this great information. I'm eager to start using Python to delve into the area of photogrammetry.
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  129. Such an amazing post! Toolbox is a brilliant tool for those venturing into the realm of 3D reconstruction and image processing.
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  130. thank you for sharing insights about the Python Photogrammetry Toolbox! The blog effectively highlighted its potential in streamlining photogrammetric processes and creating precise 3D models
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  131. good blog
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  132. The Python Photogrammetry Toolbox is a powerful set of tools for generating 3D models from photographs, making it a valuable asset in fields like archaeology, geospatial analysis, and more. In the domain of data analytics, Glasgow's Data Analytics courses equip professionals with the skills needed to extract insights from diverse data sources. For more information on these courses, please also read Data Analytics courses in Glasgow .

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  133. "I am thoroughly impressed with the capabilities of the Python Photogrammetry Toolbox
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  134. I appreciate you sharing this information. The next time I encounter a blog, I'm hopeful that it will offer a more captivating and intellectually stimulating experience.
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  135. I appreciate your sharing of this information. I'm hopeful that my next encounter with a blog will offer a more captivating and stimulating experience.
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  136. I appreciate you sharing this information. I look forward to encountering another blog in the future that promises a more captivating and intellectually stimulating experience.
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  137. Thank you for sharing such practical insights into the capabilities of the Python Photogrammetry Toolbox."
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  138. The blog provides detaialed overview on the Python Photogrammetry Toolbox! Thanks' for sharing.
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  139. Thanks for providing excellent and informative guide on how to create python photogrammetry toolbox.
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  140. Great initiative! Simplifying photogrammetry with Python is a game-changer. Your toolbox is invaluable. Thanks for sharing

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  141. Moreover, your emphasis on the open-source nature of the toolbox aligns with the collaborative spirit of the Python ecosystem. The inclusion of resources and links for further exploration demonstrates your commitment to providing a comprehensive guide for readers interested in delving deeper into photogrammetry with Python. Digital marketing for business

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  142. Thank you for sharing excellent tutorial for how to create a python photogrammetry toolbox..
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