BenchmarkDotNet
OpenCvSharp
Our great sponsors
BenchmarkDotNet | OpenCvSharp | |
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67 | 9 | |
9,990 | 5,095 | |
1.2% | - | |
9.3 | 7.8 | |
5 days ago | about 2 months ago | |
C# | C# | |
MIT License | 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.
BenchmarkDotNet
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Stop Guessing, Start Measuring: Transform Your Code with BenchmarkDotnet!
Let’s look at the first example you see, when you open up BenchmarkDotnet’s website, or Github page.
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Benchmarking 20 programming languages on N-queens and matrix multiplication
Or use BenchmarkDotNet which, among other things to get an accurate benchmark, does JIT warmup outside of measurement.
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How to improve C# performance on matrix multiplication example?
You can also do proper statistically correct benchmarking by using - https://github.com/dotnet/BenchmarkDotNet. This will run warmup the jit, gauge the overheads, and run your function many times to give you proper data.
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C# Memory Profiler on VSCode
take a look at: https://benchmarkdotnet.org/
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standard events vs MVVM Reference Messenger
Yes, weak references are slower than direct calls. How much slower? Heck if I know offhand. But it's usually pretty easy to set up something with Benchmark .NET and find out if it hurts your use case.
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Mechanisms and Performance when querying data to SQLServer from C#
For this purpose we are going to use our beloved BenchmarkDotNet tool.
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Object Mapping in .NET
To quantify and compare the performance of the object mapping strategies discussed earlier, we can employ BenchmarkDotNet.
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Exploring Code Performance Testing in C# with BenchmarkDotNet
BenchmarkDotNet is a popular open-source library that, as stated in the repo's README.md, helps us to transform methods into benchmarks, track their performance, and share reproducible measurement experiments. Using BenchmarkDotNet feels similar to writing unit tests. It's very important to note that the library only works with console apps. Finally, we can visualize the results in the terminal where the benchmark ran or in user-friendly formats such as markdown, HTML and CSV. We will explore examples of there formats later in the article.
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Is it okay to lock on a StringBuilder, on which StringBuilrer I perform some operations on?
However, obviously this prevents parallelism within the lock, so this only makes sense if you do some other expensive operation in the parallel loop and the string builder is only a small part of it. Performance wise, it may be better to concatenate the results together after the parallel operation, instead of locking inside the loop. You'll have to benchmark it to know for sure.
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Iterator Benchmarks That Shocked With Unexpected Results!
We’re of course going to be using BenchmarkDotNet for our benchmarks, and you can find all of the code for these over at GitHub. To start, we need an entry point hook for our single Benchmark class that will be defining the permutations of scenarios that we’d like to run. This will be relatively basic as follows:
OpenCvSharp
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Image Feature Detection and Matching using OpenCvSharp - First Steps Towards VinylEye
In a previous post, I have gone through the process for building a Docker Image for OpenCVSharp that supports multiple processor architectures.
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Does there exist an API accessible from C# that detects faces in images?
Alternatively, you can get into the nitty gritty of face detection yourself. OpenCV is a massive, open source project for all kinds computer vision tasks. Without jumping into the proprietary world, this is one of the most popular and capable computer vision libraries available. While powerful, OpenCV is comparatively low level; giving you the tools you need to accomplish your task, rather than a direct, single method to call. This tutorial goes into depth on how you'd go about training facial models to create your own detection methods. You'll notice that the example is written in C++. The con with this option (aside from it being more complex) is that OpenCV is largely used in the context of C++ or Python. However, it does have C# wrappers. Emgu CV is probably the most popular .NET wrapper for OpenCV, though there are other wrappers available. Here is a nice tutorial using OpenCVSharp, which is a bit closer to the native C++ API OpenCV uses.
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Compress/resize images
Another option for more advanced image manipulation - use OpenCV wrapper like opencvsharp. I haven't done much benchmarking, but from my understanding this is considerably faster option than anything made in managed code (like ImageSharp), but coming at the cost of native dependency and a bit more C++-style API and other quirks of OpenCV.
- Creating a NuGet package with static dependencies AND a native assembly wrapper?
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Universal UI testing based on image and text recognition
In order to do so, I had to learn about the basics of image processing. I was able to find an image within another with a technique called template matching, and I used an OpenCV wrapper made for .NET. I will not go through the technical details here, but you can find the relevant source code in my GitHub repository.
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Docker multi-architecture, .NET 6.0 and OpenCVSharp
FROM debian:bullseye-slim AS build-native-env ARG TARGETPLATFORM ENV DEBIAN_FRONTEND=noninteractive # 4.5.5: released 25 Dec 2021 ENV OPENCV_VERSION=4.5.5 # 4.5.3.20211228: released 28 Dec 2021 ENV OPENCVSHARP_VERSION=4.5.3.20211228 WORKDIR / # install dependencies required for building OpenCV and OpenCvSharpExtern RUN apt-get update && apt-get -y install --no-install-recommends \ # details omitted \ libgdiplus # Get OpenCV and opencv-contrib sources using the specified release. RUN wget https://github.com/opencv/opencv/archive/${OPENCV_VERSION}.zip && \ unzip ${OPENCV_VERSION}.zip && \ rm ${OPENCV_VERSION}.zip && \ mv opencv-${OPENCV_VERSION} opencv RUN wget https://github.com/opencv/opencv_contrib/archive/${OPENCV_VERSION}.zip && \ unzip ${OPENCV_VERSION}.zip && \ rm ${OPENCV_VERSION}.zip && \ mv opencv_contrib-${OPENCV_VERSION} opencv_contrib # configure and build OpenCV optionally specifying architecture related cmake options. RUN if [ "$TARGETPLATFORM" = "linux/amd64" ]; then \ ADDITIONAL_FLAGS='' ; \ elif [ "$TARGETPLATFORM" = "linux/arm64" ]; then \ ADDITIONAL_FLAGS='-D ENABLE_NEON=ON -D CPU_BASELINE=NEON ' ; \ elif [ "$TARGETPLATFORM" = "linux/arm/v7" ]; then \ ADDITIONAL_FLAGS='-D CPU_BASELINE=NEON -D ENABLE_NEON=ON ' ; \ fi && cd opencv && mkdir build && cd build && \ cmake $ADDITIONAL_FLAGS \ # additional flags omitted for clarity \ && make -j$(nproc) \ && make install \ && ldconfig # Download OpenCvSharp to build OpenCvSharpExtern native library RUN git clone https://github.com/shimat/opencvsharp.git RUN cd opencvsharp && git fetch --all --tags --prune && git checkout ${OPENCVSHARP_VERSION} WORKDIR /opencvsharp/src RUN mkdir /opencvsharp/make \ && cd /opencvsharp/make \ && cmake -D CMAKE_INSTALL_PREFIX=/opencvsharp/make /opencvsharp/src \ && make -j$(nproc) \ && make install \ && cp /opencvsharp/make/OpenCvSharpExtern/libOpenCvSharpExtern.so /usr/lib/ \ && ldconfig # Copy the library and dependencies to /artifacts (to be used by images consuming this build) # cpld.sh will copy the library we specify (./libOpenCvSharpExtern.so) and any dependencies # to the /artifacts directory. This is useful for sharing the library with other images # consuming this build. # credits: Hemanth.HM -> https://h3manth.com/content/copying-shared-library-dependencies WORKDIR /opencvsharp/make/OpenCvSharpExtern COPY cpld.sh . RUN chmod +x cpld.sh && \ mkdir /artifacts && \ ./cpld.sh ./libOpenCvSharpExtern.so /artifacts/ RUN cp ./libOpenCvSharpExtern.so /artifacts/ # Publish the artefacts using a clean image FROM debian:bullseye-slim AS final RUN mkdir /artifacts COPY --from=build-native-env /artifacts/ /artifacts WORKDIR /artifacts
- Why we can’t use C++ in WPF?
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What's the fastest way to get pixel data from a Bitmap?
Maybe opencv will be faster? https://github.com/shimat/opencvsharp
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image classification in .net with webcam
hello. the quickest way to access webcam in .NET would be use this package shimat/opencvsharp: OpenCV wrapper for .NET (github.com) and give feedback about using the lobe.OpenCVSharp binding to help you classify the images
What are some alternatives?
App.Metrics - App Metrics is an open-source and cross-platform .NET library used to record and report metrics within an application.
Emgu CV - Emgu CV is a cross platform .Net wrapper to the OpenCV image processing library.
CodeMaid - CodeMaid is an open source Visual Studio extension to cleanup and simplify our C#, C++, F#, VB, PHP, PowerShell, JSON, XAML, XML, ASP, HTML, CSS, LESS, SCSS, JavaScript and TypeScript coding.
ImageSharp - :camera: A modern, cross-platform, 2D Graphics library for .NET
Metrics-Net - The Metrics.NET library provides a way of instrumenting applications with custom metrics (timers, histograms, counters etc) that can be reported in various ways and can provide insights on what is happening inside a running application.
ML.NET - ML.NET is an open source and cross-platform machine learning framework for .NET.
StyleCop - Analyzes C# source code to enforce a set of style and consistency rules.
Magick.NET - The .NET library for ImageMagick
Bogus - :card_index: A simple fake data generator for C#, F#, and VB.NET. Based on and ported from the famed faker.js.
ImageProcessor - :camera: A fluent wrapper around System.Drawing for the processing of image files.
.NET Compiler Platform ("Roslyn") Analyzers
MetadataExtractor - Extracts Exif, IPTC, XMP, ICC and other metadata from image, video and audio files