GraphTERN | Official Code for `` A Set of Control Points

by InhwanBae Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | GraphTERN Summary

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

Official Code for "A Set of Control Points Conditioned Pedestrian Trajectory Prediction (AAAI 2023)"

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Quality

Security

License

Reuse

Support

GraphTERN has a low active ecosystem.

It has 2 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

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

It has a neutral sentiment in the developer community.

The latest version of GraphTERN is current.

Quality

GraphTERN has no bugs reported.

Security

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

License

GraphTERN 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

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

GraphTERN 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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GraphTERN Key Features

No Key Features are available at this moment for GraphTERN.

GraphTERN Examples and Code Snippets

No Code Snippets are available at this moment for GraphTERN.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install GraphTERN

Environment All models were trained and tested on Ubuntu 18.04 with Python 3.7 and PyTorch 1.6.0 with CUDA 10.1. Dataset Preprocessed ETH and UCY datasets are included in this repository, under ./dataset/. The train/validation/test splits are the same as those fond in Social-GAN.

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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