dji_srt_parser

DJI_SRT_Parser

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 :).

• Used for creating this SRT log viewer in https://djitelemetryoverlay.com
• Example video using the data in After Effects: https://youtu.be/zAkUTOLmdmQ

Installation

Using npm:

$ npm install dji_srt_parser

Usage

//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() exports the current interpretation of data to a CSV spreadsheet format. The optional value raw exports the raw data instead. 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));
//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() exports the current interpretation of data to Adobe's mgJSON format for use in After Effects (see more info below).
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.

Units of interpreted data

(As far as we know)

• Timecode: HH:MM:SS,FFF
• GPS: degrees (and meters for third value, altitude)
• Date: timestamp in milliseconds (note that the time zone is not specified, could be local where the drone was registered, or flown...)
• Barometer: meters (more accurate than GPS altitude)
• Speed: km/h
• Duration: milliseconds
• Distance: meters
• ISO, shutter and EV (not always present)

How to use mgJSON files

I gathered some information on the mgJSON format in this repo: mgJSON

Contribution

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.

Acknowledgements/credits

• Juan Irache - Main developer
• Gastón Zalba - Contributor

To-Do

• Add tests for export formats