git-dive
mediapipe
git-dive | mediapipe | |
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1 | 49 | |
57 | 25,487 | |
- | 1.1% | |
8.7 | 9.9 | |
6 days ago | 5 days ago | |
Rust | C++ | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
git-dive
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Google Summer of code 2023 is coming
> Some advices for a first timer?
Sure[0]:
* Send a proposal to strace. :)
Additionally:
(a) As others have mentioned, it's entirely normal to initially feel like one doesn't understand a new code-base of non-trivial size enough to modify it. One of the skills that participating in a programme like GSoC can provide is learning the tools & strategies that you can use to assist in growing your understanding of new code bases.[1]
(b) From an outside perspective, the fact you're aware of the existence of `strace`, have an interest in contributing to the project & have already poked around in the source code in an attempt to understand it are big positive indicators & differentiate you.
(c) That you're using a tool like `git blame` to assist in your exploration indicates that you've already learned some of the tools/strategies you can use which is also a positive. (As an aside, today I learned about the tool `git-dive` which is intended to be a more powerful form of `git blame`, you might be interested in checking it out: <https://github.com/gitext-rs/git-dive>)
(d) Also, with regard to `strace` specifically, you might gain some insight from this recent video: "strace feels like magic — let's fix that (with Rust)" <https://www.youtube.com/watch?v=engduNoI6DE>. While the video uses Rust for the implementation it also provides a general overview of how `strace` works. (This might be a useful intro to Rust syntax, if you're not currently familiar: <https://fasterthanli.me/articles/a-half-hour-to-learn-rust> (BTW, it is also extremely normal to not understand everything/anything about Rust code on first sight. :) ))
(e) Personally, in the past I've found it extremely easy to talk myself out of submitting proposals for opportunities such as this but my current perspective is: if I have doubts about whether or not I'm experienced/qualified enough to submit a proposal then I'm definitely not qualified to evaluate whether I should submit a proposal--so I definitely should submit a proposal to give those who are qualified the opportunity to evaluate it. (After all, if you don't currently maintain the `strace` project you have no idea what their experience has taught them is important in order for people to successfully contribute.)
Hope some of that is useful.
[0] re: "advices" -- in this context, "advice" is the preferred word[2]. I mention this as written communication is important & based on your previous HN comments this seems to be a pattern of incorrect pluralization rather than a typo. Note: I do not have perfect grammar. :)
[1] Also, I would encourage you to take notes of what you don't understand or issues you ran into when you start exploring a project. You can then document these hurdles/barriers to new contributors for the project so that maintainers are (at least) aware of them. This is one situation where your relative inexperience with a project is in itself valuable because your perspective is one maintainers no longer have. (And such hurdles are important to identify for projects that are actively looking to attract & nurture new contributors.)
[2] <https://en.wiktionary.org/wiki/advices>
mediapipe
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Mediapipe openpose Controlnet model for SD
mediapipe/docs/solutions/pose.md at master · google/mediapipe · GitHub
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MEDIAPIPE on-device diffusion plugins for conditioned text-to-image generation
Today, we announce MediaPipe diffusion plugins, which enable controllable text-to-image generation to be run on-device. Expanding upon our prior work on GPU inference for on-device large generative models, we introduce new low-cost solutions for controllable text-to-image generation that can be plugged into existing diffusion models and their Low-Rank Adaptation (LoRA) variants.
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Running a TensorFlow object detector model and drawing boxes around objects at 60 FPS - all in React Native / JavaScript!
You can just grab the TFLite version! https://github.com/google/mediapipe/blob/master/docs/solutions/models.md
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OpenAI came after our domain because we use GPT in it
I believe Google already released transformers under an apache 2 license with a patent grant:
https://github.com/google/mediapipe/blob/master/mediapipe/mo...
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Open source Background Remover: Remove Background from images and video using AI
I was going to say that I like the MediaPipe Selfie Segmentation model for doing this sort of thing in a web page, but I've just noticed (when getting the GitHub link[1]) that Google have marked the code as legacy[2] ... no idea if the new solution is better/easier to use[3].
For what it's worth, my CodePen using the old model is here: https://codepen.io/kaliedarik/pen/PopBxBM
[1] - https://github.com/google/mediapipe/blob/master/docs/solutio...
[2] - "Attention: Thank you for your interest in MediaPipe Solutions. As of April 4, 2023, this solution was upgraded to a new MediaPipe Solution."
[3] - https://developers.google.com/mediapipe/solutions/vision/ima...
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[P] Pattern recognition
I have used mediapipe very successfully in multiple projects and it's very easy to get running. You can choose from many different vision tasks including hand landmarks ( https://github.com/google/mediapipe/blob/master/docs/solutions/hands.md )
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Getting face feature pose statistics
I found MediaPipe's Face Mesh and was impressed with how simple it was to get going, but it just gives you the landmark points and I've not gone any further yet.
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New ControlNet Face Model
We've trained ControlNet on a subset of the LAION-Face dataset using modified output from MediaPipe's face mesh annotator to provide a new level of control when generating images of faces.
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Trained an ML model using TensorFlow.js to classify American Sign Language (ASL) alphabets on browser. We are creating an open-source platform and would love to receive your feedback on our project.
Medipaipe library link: https://mediapipe.dev/
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mediapipe VS daisykit - a user suggested alternative
2 projects | 24 Mar 2023
What are some alternatives?
rekordcrate - Library for parsing Pioneer Rekordbox device exports
openpose - OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
ue4-mediapipe-plugin - UE4 MediaPipe plugin
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
AlphaPose - Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System
BlazePose-tensorflow - A third-party Tensorflow Implementation for paper "BlazePose: On-device Real-time Body Pose tracking".
jeelizFaceFilter - Javascript/WebGL lightweight face tracking library designed for augmented reality webcam filters. Features : multiple faces detection, rotation, mouth opening. Various integration examples are provided (Three.js, Babylon.js, FaceSwap, Canvas2D, CSS3D...).
pifuhd - High-Resolution 3D Human Digitization from A Single Image.
flutter_hand_tracking_plugin - 这是一个 Flutter Packge 以实现摄像头精确追踪并识别十指的运动路径/轨迹和手势动作, 且输出22个手部关键点以支持更多手势自定义. 基于这个包可以编写业务逻辑将手势信息实时转化为指令信息: 一二三四五, rock, spiderman...还可以对不同手势编写不同特效. 可用于短视频直播特效, 智能硬件等领域, 为人机互动带来更自然丰富的体验
tfjs-models - Pretrained models for TensorFlow.js
bevy - A refreshingly simple data-driven game engine built in Rust
Unity-Robotics-Hub - Central repository for tools, tutorials, resources, and documentation for robotics simulation in Unity.