OpenCvSharp VS dotnet-docker

In a previous post, I have gone through the process for building a Docker Image for OpenCVSharp that supports multiple processor architectures.

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.

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.

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.

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

Maybe opencv will be faster? https://github.com/shimat/opencvsharp

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

This cool method lets you whip up optimized apps that get along swimmingly with Docker. Neat, huh? --platform values. Take a peek at this sample to see the pattern in action!

You can also use the .NET Docker images to run (or build from source and then run) .NET applications.

Sadly, lots of dotnet apps still out there. Luckily, there's a container for that too!

A search of "alpine 3.17 ssl" brings up this link that shows the same error.

Actually, it looks like I am a bit out of the loop, and there is an official .NET runtime for Linux, so you can use it like any other Linux docker images. Looks like there are examples here: https://github.com/dotnet/dotnet-docker

It is good that you are thinking about security 😊. there is an issue in dotnet repo here https://github.com/dotnet/dotnet-docker/issues/1772 that have hardened examples.

You can use .NET without using ASP.NET Core (yes, the names are confusing right now, they dropped the "Core" suffix for the platform but did not drop the suffix for the web framework). Microsoft publishes a Docker image for .NET for when you just want to run some compiled CIL, but they also provide a Docker image where it includes .NET and ASP.NET Core for when you run a compiled ASP.NET Core web app. (https://hub.docker.com/_/microsoft-dotnet/)

Keeping the whole Maritime theme alive with Docker (and Kubernetes), I jumped into the sea of Docker Hub with millions of containers and found out that Microsoft hosts all the .NET related container images as .NET by Microsoft registry.

ARG OPENCV_SHARP_BUILD_TAG=2 ARG SDK_VERSION=6.0.202-bullseye-slim-amd64 ARG RUNTIME_VERSION=6.0.4-bullseye-slim FROM syamaner/opencvsharp-build:$OPENCV_SHARP_BUILD_TAG AS opencv # Given we are building a .Net application, the build does not have to be in the target architecture. # Reference: https://github.com/dotnet/dotnet-docker/issues/1537#issuecomment-755351628 FROM mcr.microsoft.com/dotnet/sdk:$SDK_VERSION as build ARG TARGETPLATFORM WORKDIR /src COPY . . # Select the correct RID for the target architecture. # run dotnet publish as usual and pass the RID. RUN if [ "$TARGETPLATFORM" = "linux/amd64" ]; then \ RID=linux-x64 ; \ elif [ "$TARGETPLATFORM" = "linux/arm64" ]; then \ RID=linux-arm64 ; \ elif [ "$TARGETPLATFORM" = "linux/arm/v7" ]; then \ RID=linux-arm ; \ fi && \ dotnet publish -c release -o /app -r $RID --self-contained false # Copy the application as well as native dependencies to the final stage and build the final image without any unnecessary files. FROM mcr.microsoft.com/dotnet/runtime:$RUNTIME_VERSION as final WORKDIR /app # Copy opencv sharp native binding and runtime dependencies. COPY --from=opencv /artifacts/ /usr/lib/ RUN ldconfig COPY --from=build /app/ /app/ ENTRYPOINT [ "dotnet", "/app/OpenCVSharpBenchmarkApp.dll" ]