mediapipe-model-maker

v0.2.1.4

MediaPipe Model Maker is a simple, low-code solution for customizing on-device ML models For more information about how to use this package see README

Latest version published 13 days ago

License: Apache-2.0

PyPI

GitHub

Package Health Score

78 / 100

security
Security review needed
popularity
Recognized
maintenance
Healthy
community
Active

Popularity

Recognized

GitHub Stars: 25.45K
Forks: 4.96K
Contributors: 60

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package mediapipe-model-maker, we found that it has been starred 25,453 times.

Security

Security review needed

Security and license risk for latest version

Release Date: Apr 22, 2024
Direct Vulnerabilities: 0
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0
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0
M
0
L
Indirect Vulnerabilities: 0
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0
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0
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License Risk: 0
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14
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0
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All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

Apache-2.0

Security Policy

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Maintenance

Healthy

Commit Frequency

Open Issues: 266
Open PR: 110
Last Release: 13 days ago
Last Commit: 11 days ago

Further analysis of the maintenance status of mediapipe-model-maker based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Healthy.

We found that mediapipe-model-maker demonstrates a positive version release cadence with at least one new version released in the past 3 months.

As a healthy sign for on-going project maintenance, we found that the GitHub repository had at least 1 pull request or issue interacted with by the community.

Community

Active

Readme: Yes
Contributing.md: Yes
Code of Conduct: Yes
Contributors: 60
Funding: No

With more than 10 contributors for the mediapipe-model-maker repository, this is possibly a sign for a growing and inviting community.

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Package

Python Versions Compatibility: ==3.10.*, ==3.8.*, ==3.9.*

Age: 1 year
Latest Release: 13 days ago
Dependencies: 7 Direct / 102 Total
Versions: 11
Maintainers: 1
Wheels: OS Independent

Readme

layout: forward target: https://developers.google.com/mediapipe title: Home nav_order: 1

Attention: We have moved to https://developers.google.com/mediapipe as the primary developer documentation site for MediaPipe as of April 3, 2023.

MediaPipe

Attention: MediaPipe Solutions Preview is an early release. Learn more.

On-device machine learning for everyone

Delight your customers with innovative machine learning features. MediaPipe contains everything that you need to customize and deploy to mobile (Android, iOS), web, desktop, edge devices, and IoT, effortlessly.

Get started

You can get started with MediaPipe Solutions by by checking out any of the developer guides for vision, text, and audio tasks. If you need help setting up a development environment for use with MediaPipe Tasks, check out the setup guides for Android, web apps, and Python.

Solutions

MediaPipe Solutions provides a suite of libraries and tools for you to quickly apply artificial intelligence (AI) and machine learning (ML) techniques in your applications. You can plug these solutions into your applications immediately, customize them to your needs, and use them across multiple development platforms. MediaPipe Solutions is part of the MediaPipe open source project, so you can further customize the solutions code to meet your application needs.

These libraries and resources provide the core functionality for each MediaPipe Solution:

MediaPipe Tasks: Cross-platform APIs and libraries for deploying solutions. Learn more.
MediaPipe models: Pre-trained, ready-to-run models for use with each solution.

These tools let you customize and evaluate solutions:

MediaPipe Model Maker: Customize models for solutions with your data. Learn more.
MediaPipe Studio: Visualize, evaluate, and benchmark solutions in your browser. Learn more.

Legacy solutions

We have ended support for these MediaPipe Legacy Solutions as of March 1, 2023. All other MediaPipe Legacy Solutions will be upgraded to a new MediaPipe Solution. See the Solutions guide for details. The code repository and prebuilt binaries for all MediaPipe Legacy Solutions will continue to be provided on an as-is basis.

For more on the legacy solutions, see the documentation.

Framework

To start using MediaPipe Framework, install MediaPipe Framework and start building example applications in C++, Android, and iOS.

MediaPipe Framework is the low-level component used to build efficient on-device machine learning pipelines, similar to the premade MediaPipe Solutions.

Before using MediaPipe Framework, familiarize yourself with the following key Framework concepts:

Community

Slack community for MediaPipe users.
Discuss - General community discussion around MediaPipe.
Awesome MediaPipe - A curated list of awesome MediaPipe related frameworks, libraries and software.

Contributing

We welcome contributions. Please follow these guidelines.

We use GitHub issues for tracking requests and bugs. Please post questions to the MediaPipe Stack Overflow with a mediapipe tag.

Resources

Publications

Bringing artworks to life with AR in Google Developers Blog
Prosthesis control via Mirru App using MediaPipe hand tracking in Google Developers Blog
SignAll SDK: Sign language interface using MediaPipe is now available for developers in Google Developers Blog
MediaPipe Holistic - Simultaneous Face, Hand and Pose Prediction, on Device in Google AI Blog
Background Features in Google Meet, Powered by Web ML in Google AI Blog
MediaPipe 3D Face Transform in Google Developers Blog
Instant Motion Tracking With MediaPipe in Google Developers Blog
BlazePose - On-device Real-time Body Pose Tracking in Google AI Blog
MediaPipe Iris: Real-time Eye Tracking and Depth Estimation in Google AI Blog
MediaPipe KNIFT: Template-based feature matching in Google Developers Blog
Alfred Camera: Smart camera features using MediaPipe in Google Developers Blog
Real-Time 3D Object Detection on Mobile Devices with MediaPipe in Google AI Blog
AutoFlip: An Open Source Framework for Intelligent Video Reframing in Google AI Blog
MediaPipe on the Web in Google Developers Blog
Object Detection and Tracking using MediaPipe in Google Developers Blog
On-Device, Real-Time Hand Tracking with MediaPipe in Google AI Blog
MediaPipe: A Framework for Building Perception Pipelines

Videos

YouTube Channel

mediapipe-model-maker dependencies

absl-py numpy opencv-python tensorflow-addons tensorflow-datasets tensorflow-hub tensorflow-text

FAQs

What is mediapipe-model-maker?

MediaPipe Model Maker is a simple, low-code solution for customizing on-device ML models. Visit Snyk Advisor to see a full health score report for mediapipe-model-maker, including popularity, security, maintenance & community analysis.

Is mediapipe-model-maker popular?

The python package mediapipe-model-maker receives a total of 3,213 weekly downloads. As such, mediapipe-model-maker popularity was classified as a recognized. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is mediapipe-model-maker well maintained?

We found that mediapipe-model-maker demonstrated a healthy version release cadence and project activity. It has a community of 60 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is mediapipe-model-maker safe to use?

While scanning the latest version of mediapipe-model-maker, we found that a security review is needed. A total of 0 vulnerabilities or license issues were detected. See the full security scan results.

Last updated on 2 May-2024, at 00:02 (UTC).

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Readme

layout: forward target: https://developers.google.com/mediapipe title: Home nav_order: 1

Get started

Solutions

Legacy solutions

Framework

Community

Contributing

Resources

Publications

Videos

mediapipe-model-maker dependencies

FAQs

What is mediapipe-model-maker?

Is mediapipe-model-maker popular?

Is mediapipe-model-maker well maintained?

Is mediapipe-model-maker safe to use?

Build a secure application checklist

Select a recommended open source package

Scan your app for vulnerabilities

Source Code

Open Source

Container

Config

Fix identified vulnerabilities

Monitor for new issues