In earlier posts (like here and here) I mentioned GoCV. GoCV allows you to use the popular OpenCV library from your Go programs. To avoid installing OpenCV and having to compile it from source, a container that runs your GoCV app can be beneficial. This post provides information about doing just that.
The following GitHub repository, https://github.com/denismakogon/gocv-alpine, contains all you need to get started. It’s for OpenCV 3.4.2 so you will run into issues when you want to use OpenCV 4.0. The pull request, https://github.com/denismakogon/gocv-alpine/pull/7, contains the update to 4.0 but it has not been merged yet. I used the proposed changes in the pull request to build two containers:
- the build container: gbaeke/gocv-4.0.0-build
- the run container: gbaeke/gocv-4.0.0-run
They are over on Docker Hub, ready for use. To actually use the above images in a typical two-step build, I used the following Dockerfile:
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FROM gbaeke/gocv-4.0.0-build as build <br>RUN go get -u -d gocv.io/x/gocv <br>RUN go get -u -d github.com/disintegration/imaging <br>RUN go get -u -d github.com/gbaeke/emotion <br>RUN cd $GOPATH/src/github.com/gbaeke/emotion && go build -o $GOPATH/bin/emo ./main.go <br> <br>FROM gbaeke/gocv-4.0.0-run <br>COPY --from=build /go/bin/emo /emo <br>ADD haarcascade_frontalface_default.xml / <br><br>ENTRYPOINT ["/emo"] |
The above Dockerfile uses the webcam emotion detection program from https://github.com/gbaeke/emotion. To run it on a Linux system, use the following command:
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docker run -it --rm --device=/dev/video0 --env SCOREURI="YOUR-SCORE-URI" --env VIDEO=0 gbaeke/emo |
The SCOREURI environment variable needs to refer to the score URI offered by the ONNX FER+ container as discussed in Detecting Emotions with FER+. With VIDEO=0 the GUI window that shows the webcam video stream is turned off (required). Detected emotions will be logged to the console.
To be able to use the actual webcam of the host, the –device flag is used to map /dev/video0 from the host to the container. That works well on a Linux host and was tested on a laptop running Ubuntu 16.04.