Top 23 C++ CPP Projects
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Project mention: Scripting with .exes - Can it be done with any and how to figure out syntax? | reddit.com/r/commandline | 2021-10-08
It looks like Matt is using x64dbg.
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Project mention: Is it realistically possible to add functionality to a desktop app? | reddit.com/r/learnprogramming | 2021-09-06
If the source code to the program has been published, like the Windows calculator, it's much easier to modify.
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openpose
OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
Project mention: Help finding an appropriate model for human pose estimation | reddit.com/r/computervision | 2021-09-29Openpose: This is supposedly realtime (I assume on a gpu, 24fps?) and they provide training code
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modern-cpp-tutorial
📚 Modern C++ Tutorial: C++11/14/17/20 On the Fly | https://changkun.de/modern-cpp/
Project mention: Computer science student. Just figured out what I want to do with my degree. Hacking. | reddit.com/r/hacking | 2021-05-01Work in this order: (1) -> (2) --> (3) ---> (4) --> (5) Next Steps: Modern C++11/14/17/20:(https://github.com/changkun/modern-cpp-tutorial)
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Project mention: Need a C++ roguelike engine w/up to date tutorials! | reddit.com/r/roguelikedev | 2021-09-28
May I also take a moment to recommend spdlog as a logging library. It's just one line of code to add it in to the project, and it's fast and flexible.
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Ethereum's smart contracts are written in Solidity language. Etheruem has a permissionless ledger type and is open for public use. Its consensus mechanism is proof of work, which is known to be quite slow.
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Scout APM
Scout APM: A developer's best friend. Try free for 14-days. Scout APM uses tracing logic that ties bottlenecks to source code so you know the exact line of code causing performance issues and can get back to building a great product faster.
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Tink
Tink is a multi-language, cross-platform, open source library that provides cryptographic APIs that are secure, easy to use correctly, and hard(er) to misuse.
Project mention: Selenite: A Post-Quantum Cryptography Library For Digital Certificates Written In Rust | reddit.com/r/crypto | 2021-10-09Google has also started to add post-quantum algorithms to their Tink library. https://github.com/google/tink
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Project mention: How do I get into graphics programming/computer graphics? | reddit.com/r/GraphicsProgramming | 2021-10-02
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BackgroundMusic
Background Music, a macOS audio utility: automatically pause your music, set individual apps' volumes and record system audio.
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Project mention: Underpriced On-Ride Photos lead to Income/Profit appearing massive? | reddit.com/r/rct | 2021-10-15
You should probably report it at OpenRCT2's github.
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Project mention: Want to Learn Electronic and Flight computer building | reddit.com/r/microcontrollers | 2021-10-15
https://cfs.gsfc.nasa.gov/ https://nasa.github.io/fprime/
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By Educating others:- Another way is to educate others. There are many ways to do this, Like creating tutorials on youtube, writing blogs, or making Github repositories for storing and sharing learning material like IoT Course from Microsoft (which I am learning IoT from).
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Typesense
Fast, typo tolerant, fuzzy search engine for building delightful search experiences ⚡ 🔍 ✨ An Open Source alternative to Algolia and an Easier-to-Use alternative to ElasticSearch.
Project mention: Scaling Indexing and Search – Algolia New Search Architecture | news.ycombinator.com | 2021-10-15Disclaimer: I work on an open source alternative to Algolia called Typesense [1]
If I had a dollar for every time I've heard Algolia is expensive! And if I had a dollar for every time I've said that statement!
If cost is an issue, definitely checkout Typesense. You can self-host it for free, or use the hosted Cloud version. In either case, I've seen savings of up to 96% in some cases compared to Algolia's pricing.
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dolphin
Dolphin is a GameCube / Wii emulator, allowing you to play games for these two platforms on PC with improvements.
If you want to play vocals on PC, your best bet will be emulating the Wii version of Rock Band 3 on Dolphin.
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vowpal_wabbit
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
Project mention: [Table] We are Microsoft researchers working on machine learning and reinforcement learning. Ask Dr. John Langford and Dr. Akshay Krishnamurthy anything about contextual bandits, RL agents, RL algorithms, Real-World RL, and more! | reddit.com/r/tabled | 2021-07-03Questions Answers AFAIK most model-based reinforcement learning algorithms are more data efficient than model-free (that don't create an explicit model of the environment). However, all the model-based techniques I've seen eventually "throw away" data and stop using it for model training. Could we do better (lower sample complexity) if we didn't throw away old data? I imagine an algorithm that keeps track of all past observations as "paths" through perception space, and can use something akin to nearest neighbor to identify when it is seeing a similar "path" again in the future. I.e., what if the model learned a compression from perception space into a lower dimension representation (like the first 10 principle components), could we then record all data and make predictions about future states with nearest neighbor? This method would benefit from "immediate learning". Does this direction sound promising? Definitely. This is highly related to the latent space discovery research direction of which we've had several recent papers at ICLR, NeurIPs, ICML. There are several challenging elements here. You need to learn nonlinear maps, you need to use partial learning to gather information for more learning, and it all needs to be scalable. -John Hello, do you have any events in New York? I've been teaching myself for the last couple years on ML and AI theory and practice but would love accelerate my learning by working on stuff (could be for free). I have 7 years of professional programming experience and work as a lead for a large financial company. Well, we have "Reinforcement Learning day" each year. I'm really looking forward to the pandemic being over because we have a beautiful new office at 300 Lafayette---more might start happening when we can open up. -John RL seems to more strategy oriented/original than the papers I observe in other areas of ML and Deep Learning, which seems to be more about adding layers upon layers to get slightly better metrics. What is your opinion about it ? Secondly I would love to know the role RL in real world applications. By strategy I guess you mean "algorithmic." I think both areas are fairly algorithmic nature. There have been some very cool computational advancements involved in getting certain architectures (like transformers) to scale and similarly there are many algorithmic advancements in domain adaptation, robustness, etc. RL is definitely fairly algorithmically focused, which I like =) RL problems are kind of ubiquitous, since optimizing for some value is a basic primitive. The question is whether ""standard RL"" methods should be used to solve these problems or not. I think this requires some trial-and-error and, at least with current capabilities, some deeper understand of the specific problem you are interested in. -Akshay Dr. Langford & Dr. Krishnamurthy, Thank you for this AMA. My question: From what I understand about RL, there are trade offs one must consider between computational complexity and sample efficiency for given RL algorithms. What do you both prioritize when developing your algorithms? I tend to think first about statistical/sample efficiency. The basic observation is that computational complexity is gated by sample complexity because minimally you have to read in all of your samples. Additionally, understanding what is possible statistically seems quite a bit easier than understanding this computationally (e.g., computational lower bounds are much harder to prove that statistical ones). Obviously both are important, but you can't have a computationally efficient algorithm that requires exponentially many samples to achieve near-optimality, while you can have the converse (statistically efficient algorithm that requires exponential time to achieve near-optimality). This suggests you should go after the statistics first. -Akshay Can you share some real examples of how your work has made its way into MS products? Is this a requirement for any work that happens at MSR or is it more like an independent entity and is not always required to tie back into something within Microsoft? A simple answer is that Vowpal Wabbit (http://vowpalwabbit.org ) is used by the personalizer service (http://aka.ms/personalizer ). Many individual research projects have impacted Microsoft in various ways as well. However, many research projects have not. In general, Microsoft Research exists to explore possibilities. Inherent in the exploration of possibilities is the discovery that many possibilities do not work. - John What are some of the obstacles getting in the way of wide-spread applications of online and offline RL learning for real-world scenarios, and what research avenues look promising to you that could chip away at, or sidestep, the obstacles? I suppose there are many obstacles and the most notable one is that we don't have sample efficient algorithms that can operate at scale. There are other issues like safety, stability, etc., that will matter depending on the application. The community is working on all of these issues, but in the meantime, I like all of the side-stepping ideas people are trying. Leveraging strong inductive bias (via pre-trained representation or state abstraction or prior), sim-to-real, imitation learning. These all seem very worthwhile to pursue. I am in favor of the trying everything and seeing what sticks, because different problems might admit different structures, so it's important to have a suite of tools at our disposal. On sample efficiency, I like the model based approach as it has many advantages (obvious supervision signal, offline planning, zero-shot transfer to a new reward function, etc.). So (a) fitting accurate dynamics models, (b) efficient planning in such models, and (c) using them to explore, all seem like good questions to study. We have some recent work on this approach (https://arxiv.org/abs/2006.10814) -Akshay Hi! Thanks for doing this AMA. What is the status of Real World RL? What are the practical areas that RL is being applied to in the real world right now? There are certainly many deployments of real world RL. This blog post: https://blogs.microsoft.com/ai/reinforcement-learning/ covers a number related to work at Microsoft. In terms of where we are, I'd say "at the beginning". There are many applications that haven't even been tried, a few that have, and lots of room for improvement. -John With the xbox series X having hardware for machine learning, what kind of applications of this apply to gaming? An immediate answer is to use RL to control non-player-characters. -Akshay How can I prepare in order to be part of Microsoft Researcher in Reinforcement Learning? This depends on the role you are interested in. We try to post new reqs here (http://aka.ms/rl_hiring ) and have hired in researcher, engineer, and applied/data scientist roles. For a researcher role, a phd is typically required. The other roles each have their own reqs. -John What is latent state discovery and why do you think it is important in real world RL ? Latent state discovery is an approach for getting reinforcement learning to provably scale to complex domains. The basic idea is to decouple of the dynamics which are determined by a simple latent state space, from an observation process, which could be arbitrarily complex. The natural example is a visual navigation task: there are far fewer locations in the world, than visual inputs you might see at those locations. The ""discovery"" aspect is that we don't want to know this latent state space in advance, so we need to learn how to map observations to latent states if we want to plan and explore. Essentially this is a latent dynamics modeling approach, where we use the latent state to drive exploration (such ideas are also gaining favor in the Deep-RL literature). The latent state approach has enabled us to develop essentially the only provably efficient exploration methods for such complex environments (using arbitrary nonlinear function approximation). In this sense, it seems like a promising approach for real world settings where exploration is essential. -Akshay
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Project mention: Nintendo 64 Emulation/Port Guide for SteamDeck (Road to December) | reddit.com/r/SteamDeck | 2021-10-13
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Are you aware of the tutorials on https://pointclouds.org ?
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C++ REST SDK
The C++ REST SDK is a Microsoft project for cloud-based client-server communication in native code using a modern asynchronous C++ API design. This project aims to help C++ developers connect to and interact with services.
Assuming you want to make a REST API check this out: https://github.com/Microsoft/cpprestsdk
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MuseScore
MuseScore is an open source and free music notation software. For support, contribution, bug reports, visit MuseScore.org. Fork and make pull requests!
Musescore. The app is free and awesome. But pay the token cost to join, because the library of scores is worth it, and it's a non-profit, so much of the money goes to the artists.
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DearPyGui
Dear PyGui: A fast and powerful Graphical User Interface Toolkit for Python with minimal dependencies
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So I am trying to make a little homescreen app that displays date, time, weather, etc. I'm working on the weather component right now and I'm trying to do it through an api call to the national weather service's api. I found this library for making http requests in C++ and im having some trouble with it. Im making the request with these two lines in my code
Index
What are some of the best open-source CPP projects in C++? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | x64dbg | 37,477 |
| 2 | calculator | 22,887 |
| 3 | openpose | 22,240 |
| 4 | yuzu | 16,495 |
| 5 | modern-cpp-tutorial | 15,226 |
| 6 | spdlog | 12,780 |
| 7 | solidity | 12,355 |
| 8 | Sourcetrail | 12,063 |
| 9 | Tink | 11,654 |
| 10 | tinyrenderer | 11,409 |
| 11 | BackgroundMusic | 10,268 |
| 12 | OpenRCT2 | 9,953 |
| 13 | fprime | 8,533 |
| 14 | IoT-For-Beginners | 8,239 |
| 15 | Typesense | 8,091 |
| 16 | dolphin | 7,831 |
| 17 | vowpal_wabbit | 7,736 |
| 18 | citra | 6,848 |
| 19 | PCL | 6,656 |
| 20 | C++ REST SDK | 6,536 |
| 21 | MuseScore | 6,388 |
| 22 | DearPyGui | 6,002 |
| 23 | cpp-httplib | 5,837 |
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