![Introducing Enhanced Alert Actions and Triage Functionality](https://cdn.sanity.io/images/cgdhsj6q/production/fe71306d515f85de6139b46745ea7180362324f0-2530x946.png?w=800&fit=max&auto=format)
Product
Introducing Enhanced Alert Actions and Triage Functionality
Socket now supports four distinct alert actions instead of the previous two, and alert triaging allows users to override the actions taken for all individual alerts.
dji_srt_parser
Advanced tools
Readme
Parses and interprets some data from DJI's Drones SRT metadata files. Mostly tested with Mavic Pro SRT files. You can send me yours if you want it implemented. Please let me know if you create something with this :).
Using npm:
$ npm install dji_srt_parser
//Load module
let DJISRTParser = require('dji_srt_parser');
//Specify data source name
let fileName = 'filePath';
//And load the data in a string (with your preferred method)
let dataString = readTextFile(fileName);
//You can create multiple instances, one for reading each SRT file. Specify data as a string and filename for future reference
let DJIData = DJISRTParser(dataString, fileName);
//toGeoJSON(raw, waypoints, elevationOffset) exports the current interpretation of data to the geoJSON format. The optional value raw exports the raw data instead. The second parameter, waypoints, specifies whether to include a single feature with all the data for each waypoint. The third parameter, elevationOffset, offset the elevation values by the specified meters. You can then use tokml or togpx modules to convert to those formats
let geoJSON = DJIData.toGeoJSON();
//rawMetadata() returns an array of objects with labels and the unmodified SRT data in the form of strings
console.log(DJIData.rawMetadata());
//metadata() returns an object with 2 elements
//(1) a packets array similar to rawMetadata() but with smoothing applied to GPS locations (see below why smoothing is used), distances and with computed speeds in 2d, 3d and vertical
//(2) a stats object containing stats like minimum, average and maximum speeds based on the interpreted data
console.log(DJIData.metadata());
//getSmoothing() returns the current smoothing value (how many data packets to average with, in each array direction)
console.log(DJIData.getSmoothing());
//setSmoothing() modifies the current smoothing value, 0 for no smoothing
console.log(DJIData.setSmoothing(0));
//getMillisecondsPerSamples() returns the current millisecondsPerSamples value. This delimits how many milliseconds have to pass between data packets, useful for scenarios that imply long files, and/or for drones that record in excesive sample rate, like mavic 2 pro (every 40ms.)
console.log(DJIData.getMillisecondsPerSamples());
//setMillisecondsPerSamples() modifies the current sample rate value, 0 for no resample. NOTE: if is used in conjuntion with setSmoothing, must be in last position. The discarded packets will not affect the stats and the computed smooth.
console.log(DJIData.setMillisecondsPerSamples(0));
//getFileName() returns the filename, useful if you loaded multiple files in multiple instances
console.log(DJIData.getFileName());
//toCSV() exports the current interpretation of data to CSV format. The optional value raw exports the raw data instead
let csvData = DJIData.toCSV();
//toMGJSON(elevationOffset) exports the current interpretation of data to Adobe's mgJSON format for use in After Effects (see more info below). An elevation offset can be specified in meters.
let mgjsonData = DJIData.toMGJSON();
//Now you can also load a GeoJSON (or JSON) file directly into the rawMetadata field. This can be useful if you want to import data from other sources into the system,
let DJIData = DJISRTParser(JSONDataString, JSONfileName, true);
//These data must follow the same structure as rawMetadata() usually has:
// {
// "TIMECODE":"00:00:01,000",
// "HOME":[
// "149.0251",
// "-20.2532"
// ],
// "DATE":"2017.08.05 14:11:51",
// "GPS":[
// "149.0251",
// "-20.2533",
// "16"
// ],
// "BAROMETER":"1.9",
// "ISO":"100",
// "Shutter":"60",
// "Fnum":"2.2"
// }
Smoothing is applied when interpreting the data because the GPS values provided by DJI are not accurate enough. They don't have enough digits. We average them with the surrounding values to create more pleasant paths and to be able to compute somewhat meaningful speeds. The interpreted values are not necessarily more accurate.
(As far as we know)
I gathered some information on the mgJSON format in this repo: mgJSON
Please make your changes to the dev branch, so that automated tests can be run before merging to master. Also, if possible, provide tests for new functionality.
FAQs
Parses and interprets DJI's drones SRT metadata
The npm package dji_srt_parser receives a total of 74 weekly downloads. As such, dji_srt_parser popularity was classified as not popular.
We found that dji_srt_parser demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Product
Socket now supports four distinct alert actions instead of the previous two, and alert triaging allows users to override the actions taken for all individual alerts.
Security News
Polyfill.io has been serving malware for months via its CDN, after the project's open source maintainer sold the service to a company based in China.
Security News
OpenSSF is warning open source maintainers to stay vigilant against reputation farming on GitHub, where users artificially inflate their status by manipulating interactions on closed issues and PRs.