sornet | Spatial Object-Centric Representations

by wentaoyuan Python Version: Current License: MIT

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kandi X-RAY | sornet Summary

sornet is a Python library. sornet has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However sornet build file is not available. You can download it from GitHub.

SORNet (Spatial Object-Centric Representation Network) is a framework for extracting object-centric representations from RGB observations conditioned on canonical views of the objects of interest. The object embeddings learned by SORNet generalize zero-shot to unseen object entities on spatial reasoning tasks such as spatial relation prediction, skill precondition classification and relative direction regression, significantly outperforming baselines. This repository contains a basic PyTorch implementation for training and evaluating SORNet. Please refer to our project website or our publication at CORL 2021 for more details.

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Quality

Security

License

Reuse

Support

sornet has a low active ecosystem.

It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

sornet has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of sornet is current.

Quality

sornet has no bugs reported.

Security

sornet has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

sornet is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

sornet releases are not available. You will need to build from source code and install.

sornet has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

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sornet Key Features

No Key Features are available at this moment for sornet.

sornet Examples and Code Snippets

No Code Snippets are available at this moment for sornet.

Community Discussions

No Community Discussions are available at this moment for sornet.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install sornet

Install dependencies by conda create -f environment.yml.
Activate virtual environment by conda activate sornet.
Download data (clevr and leonardo) and copy or sym link to data/.
Download pre-trained models and copy or sym link to models/.
Example environment specs (doesn't have to match exactly to run the models): Ubuntu 18.04 Pytorch 1.10.0 CUDA 11.3

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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