OpenCvSharp
marionette
OpenCvSharp | marionette | |
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9 | 5 | |
5,116 | 44 | |
- | - | |
7.8 | 0.0 | |
2 months ago | over 1 year ago | |
C# | C# | |
Apache License 2.0 | GNU General Public License v3.0 only |
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.
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
marionette
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How to get feedback and promote an open source .NET test automation framework that I created?
I've been doing some promoting of my side project by responding to posts/comments that are relevant with details about my project, but I don't know how often questions about what kind of automation frameworks there are come up. I told my coworker about your project after tracking it down, it sounds like it may be somewhat similar to something we homebrewed and we can possibly make use of https://github.com/asimmon/askaiser-marionette instead.
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Asking for help/feedback about a test automation framework that I created. It is based on image and text recognition.
About a year ago, I started writing this test automation framework which is based on image and text recognition. Now that I've done quite a lot of testing and polishing, I've reached the point where I'd like to receive feedback from QA and software engineers. This is why I am asking for your help today:
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Universal UI testing based on image and text recognition
So, give it a try, and take a look at the sample project! It only works on Windows, because screen capture, mouse and keyboard interaction are only implemented for that OS so far.
- I created an open-source UI testing framework based on image and text recognition!
- Askaiser.Marionette is a test automation framework based on image and text recognition with a C# source generator to increase your productivity. Automate anything within minutes! Video in README. Automation engineer feedback would be particularly appreciated!
What are some alternatives?
Emgu CV - Emgu CV is a cross platform .Net wrapper to the OpenCV image processing library.
Versioning.NET - A dotnet tool that automatically increments versions in csproj files based on git commit hints.
ImageSharp - :camera: A modern, cross-platform, 2D Graphics library for .NET
dotnet-testcontainers - 🐋 A library to support tests with throwaway instances of Docker containers for all compatible .NET Standard versions. [Moved to: https://github.com/testcontainers/testcontainers-dotnet]
ML.NET - ML.NET is an open source and cross-platform machine learning framework for .NET.
CoronaDeployments - This project is created to make versioned deployments behind IIS easy! This project main focus is on Dot Net (Windows Server & IIS) & SVN SCM / Git deployments.
Magick.NET - The .NET library for ImageMagick
WexFlow - An easy and fast way to build automation and workflows on Windows, Linux, macOS, and the cloud.
ImageProcessor - :camera: A fluent wrapper around System.Drawing for the processing of image files.
WinAppDriver - Windows Application Driver
MetadataExtractor - Extracts Exif, IPTC, XMP, ICC and other metadata from image, video and audio files
Lidarr - Looks and smells like Sonarr but made for music.