ml-gmpi VS CenterSnap

Compare ml-gmpi vs CenterSnap and see what are their differences.

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ml-gmpi CenterSnap
4 4
335 269
0.6% -
2.6 4.0
2 months ago about 2 months ago
Python Jupyter Notebook
GNU General Public License v3.0 or later -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

ml-gmpi

Posts with mentions or reviews of ml-gmpi. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-09-07.

CenterSnap

Posts with mentions or reviews of CenterSnap. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-09-07.

What are some alternatives?

When comparing ml-gmpi and CenterSnap you can also consider the following projects:

text2mesh - 3D mesh stylization driven by a text input in PyTorch

text2voxels - Generate 3D voxels from text with AI

Text2LIVE - Official Pytorch Implementation for "Text2LIVE: Text-Driven Layered Image and Video Editing" (ECCV 2022 Oral)

virtual_drawing_board - Virtual whiteboard with hand pose estimation

eg3d

SynthDet - SynthDet - An end-to-end object detection pipeline using synthetic data

Clip-Forge

Robotics-Object-Pose-Estimation - A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.

rome - Realistic mesh-based avatars. ECCV 2022