Pytorch-Pose

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pytorch-pose is an Open Source & Models tool that provides a PyTorch toolkit for 2D human pose estimation. It offers interfaces for training, inference, and evaluation, supporting popular human pose databases.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is pytorch-pose?

pytorch-pose is an open-source PyTorch toolkit designed for 2D single human pose estimation. It offers a comprehensive pipeline for training, inference, and evaluation, making it a valuable resource for researchers and developers in computer vision. The toolkit includes a robust dataloader with various data augmentation options, compatible with popular human pose databases such as MPII, LSP, and FLIC. Key features include multi-thread data loading, multi-GPU training support, a logger for tracking progress, and visualization of training and testing results. It is compatible with PyTorch 0.4.1/1.0 and provides detailed instructions for installation, data preparation, and usage, including testing with pre-trained models and evaluating PCKh@0.5 scores.

Best used for

Ideal for developers and researchers who need to implement and evaluate 2D human pose estimation models, train custom models on various datasets, and visualize their results. Especially valuable for those working with MPII, LSP, or MSCOCO datasets and requiring multi-GPU training capabilities.

Common actions

estimate human pose

train pose models

evaluate pose algorithms

visualize pose results

low-code/no-codeopen-sourcecollaborationworkflowsautomated workflowdeepfakegithub copilot"AI Agents"face swapping

Capabilities

Key features

2D human pose estimation
Multi-thread data loading
Multi-GPU training
Training/testing visualization
MPII, LSP, MSCOCO support
Pre-trained models available

Target Audience

developer

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What PyTorch versions are compatible with pytorch-pose?

pytorch-pose is compatible with PyTorch versions 0.4.1 and 1.0. While the code was developed with Python 2, it has not been officially tested with Python 3, so users should be aware of potential compatibility issues.

Which human pose datasets does pytorch-pose support?

The toolkit provides data loaders and support for several popular human pose databases, including the MPII human pose dataset, Leeds Sports Pose (LSP), and MSCOCO (specifically for single-person estimation).

How can I evaluate my model's performance using pytorch-pose?

You can evaluate your model's performance by running a testing command that generates a prediction file. This file can then be evaluated for PCKh@0.5 score using either a provided MATLAB script or a Python script, yielding identical results.

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AI Agents & Automation › AI Frameworks & Infra Data & Analytics › Data Labeling & Annotation Research & Education › Scientific Computing

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