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Source channel @githubtrending · Post #14934 · Jul 9

#python#3d_reconstruction#3d_vision#monocular_depth_estimation#monocular_geometry_estimation MoGe-2 is a powerful tool for estimating 3D geometry from single images. It can create detailed point maps, depth maps, and normal maps with high precision. This model is especially useful because it can predict geometry in metric scale, meaning it provides accurate measurements. It also enhances visual sharpness, making it better than previous versions. Users benefit from MoGe-2 by getting precise 3D information from just one photo, which is helpful for applications like robotics or video games. It's fast and works well with different image sizes. https://github.com/microsoft/MoGe

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djangoproject

@djangoproject · Post #153 · 09/03/2016, 08:20 PM

http://wla.berkeley.edu/~cs61a/fa11/lectures/streams.html In this chapter, we continue our discussion of real-world applications by developing new tools to process #sequential#data. In Chapter 2, we introduced a sequence interface, implemented in Python by built-in data types such as #tuple and #list. #Sequences supported two operations: querying their length and accessing an element by index. In Chapter 3, we developed a user-defined implementations of the sequence interface, the Rlist class for representing recursive lists. These sequence types proved effective for representing and accessing a wide variety of sequential #datasets.