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The app is preset to automatically start streaming\n- click the volume button\n- tap the screen\n- try any other button you may have.... it may work\n\nMore options to enjoy in the settings :)\n\n## Build\nThe app uses OpenCV. There are 2 options to build the app\n\n### Standard build\nOpenCV will be linked through the OpenCV Manager app. You will be prompted to install it if you don't have it.\n\n### Native build\nIf you don´t want to bother installing more stuff, in this case you will need to ship the correct native libraries together with OpenCV module. To do this just uncomment the `ndk` section in the app `build.gradle`\n```gradle\nndk {\n    moduleName \"sensor-logger\"\n    abiFilters 'armeabi-v7a', 'arm64-v8a'\n}\n```\nand the `sourceSets` section in the openCVLibrary module:\n```gradle\nsourceSets {\n    main {\n        jniLibs.srcDirs \"sdk/native/libs\"\n    }\n}\n```\nwhere the path of `jniLibs.srcDirs` is where you will need to put the OpenCV static libraries (not included here) of your choice.\n\n## Python client\nA simple python client is provided to capture the streaming of both sensors and images (because with a browser you can only access a video stream).\nThis is actually pretty slow, being implemented with matplolib, but is a good starting point for collecting and make use of \"real-time\" data within a data science python application\n\n[![Open on Youtube](https://img.youtube.com/vi/NInkmRc0F0s/1.jpg)](https://youtu.be/NInkmRc0F0s)\n\n## Licenses\n- [OpenCV](https://opencv.org/) - BSD\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffrancescogabbrielli%2Fsensor-logger","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffrancescogabbrielli%2Fsensor-logger","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffrancescogabbrielli%2Fsensor-logger/lists"}