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Source channel @githubtrending · Post #15062 · Aug 15
#python#mllm#point_clouds#scene_understanding#spatial_intelligence SpatialLM is a powerful 3D language model that turns complex 3D point cloud data from videos, RGBD images, or LiDAR into clear, structured 3D scene layouts showing walls, doors, windows, and objects with labels. It works without needing special equipment and can detect user-specified object categories. This helps you understand and analyze indoor spaces better, useful for robotics, navigation, and 3D design. You can run it on your data, visualize results, and even customize detection tasks easily, making 3D scene understanding more accessible and flexible for many applications. https://github.com/manycore-research/SpatialLM
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@djangoproject · Post #346 · 06/21/2017, 07:24 AM
http://mongoengine.org To get to grips with MongoEngine, there is extensive documentation, API references and a tutorial. You can find help by joining the MongoEngine Users mailing list or by chatting with other users on the #mongoengine IRC channel.
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@djangoproject · Post #364 · 07/04/2017, 03:25 AM
http://mongoengine.readthedocs.io/en/latest/index.html #MongoEngine is an Object-Document Mapper, written in #Python for working with #MongoDB. To install it, simply run #Django
@djangoproject · Post #373 · 07/05/2017, 06:39 AM
https://realpython.com/blog/python/introduction-to-mongodb-and-python/#.WMfv6BURLc4.linkedin #SQL vs #NoSQL #MongoDB #PyMongo #MongoEngine Conclusion
@djangoproject · Post #421 · 08/21/2017, 10:39 AM
https://alysivji.github.io/flask-part1-generating-html-pages-with-mongoengine-jinja2.html Generating HTML Pages from #MongoDB with #MongoEngine and #Jinja2 (Flask Part 1) Summary Overview of MongoDB Discussion of Object-Relational Mapping (#ORM) Use MongoEngine to get items out of MongoDB Render #HTML pages using Jinja2 Interact with #REST API to send emails with #Requests