HandTracker | 3D Hand Tracking using input from a depth sensor | Computer Vision library

by FORTH-ModelBasedTracker Python Version: Current License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | HandTracker Summary

HandTracker is a Python library typically used in Artificial Intelligence, Computer Vision, OpenCV applications. HandTracker has no bugs, it has no vulnerabilities and it has low support. However HandTracker build file is not available and it has a Non-SPDX License. You can download it from GitHub.

This script uses the Model Based Vision (MBV) libraries created by the Computer Vision and Robotics Lab at ICS/FORTH. The libraries are free for academic and non-profit use under this licence. It implements a hand tracker pipeline described first in Oikonomidis et al: Efficient model-based 3D tracking of hand articulations using Kinect.

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Quality

Security

License

Reuse

Support

HandTracker has a low active ecosystem.

It has 276 star(s) with 78 fork(s). There are 33 watchers for this library.

It had no major release in the last 6 months.

There are 7 open issues and 78 have been closed. On average issues are closed in 135 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of HandTracker is current.

Quality

HandTracker has 0 bugs and 0 code smells.

Security

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

HandTracker code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

HandTracker has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

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

HandTracker 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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HandTracker Key Features

No Key Features are available at this moment for HandTracker.

HandTracker Examples and Code Snippets

No Code Snippets are available at this moment for HandTracker.

Community Discussions

Trending Discussions on HandTracker

PyTorch find keypoints: output nodes to be in a range and negative loss

Mediapipe: How to properly dealloc MPPGraph

QUESTION

PyTorch find keypoints: output nodes to be in a range and negative loss

Asked 2020-Aug-22 at 19:58

I am beginner in deep learning. I am using this dataset and I want my network to detect keypoints of a hand.

How can I make my output layer's nodes to be in range [-1, 1] (range of normalized 2D points)? Another problem is when I train for more than 1 epoch the loss gets negative values

criterion: torch.nn.MultiLabelSoftMarginLoss() and optimizer: torch.optim.SGD()

Here u can find my repo

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ANSWER

Answered 2020-Aug-21 at 15:13

One way I can think of is to use torch.nn.Sigmoid which produces outputs in [0,1] range and scale outputs to [-1,1] using 2*x-1 transformation.

Source https://stackoverflow.com/questions/63525242

QUESTION

Mediapipe: How to properly dealloc MPPGraph

Asked 2020-May-26 at 11:34

It is unclear to me how to properly stop and deallocate the MPPGraph. I created a framework very similar to this. Every time a dealloc is called in some way this exception is thrown. Thread 1: Exception: "waitUntilDoneWithError: should not be called on the main thread".

I don't know how to not call it in the main thread and was hoping someone had some insight on this.

Here you can find the swift code that is calling the mediapipe framework. This example has been created with the framework that can be found here.

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ANSWER

Answered 2020-May-26 at 11:34

For anyone experiencing same issue. This has been addressed here and a solution has been proposed.

Source https://stackoverflow.com/questions/61681734

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

Vulnerabilities

No vulnerabilities reported

Install HandTracker

Ubuntu 3D hand tracking
Windows 3D hand tracking
As a first step, download the package that matches your OS from the download section. Extract the downloaded package to a location and set an environment variable named MBV_LIBS to point to this location. For example, if the package is extracted to the path c:\Users\User\Documents\FORTH\HANDTRACKER (Windows) or /home/user/FORTH/HANDTRACKER (Ubuntu), do the following from the command line:. The provided package has some external dependencies, listed below. One such dependency is a working Python 2.7 environment. Notice: Make sure the Python version is 2.7 64bit. Notice: Binaries were build against CUDA 7.5. This might require the user to update the GPU driver to the latest version. In the lack of a supported driver, an error message of the form "CUDA driver version is insufficient for CUDA runtime version" is issued.