telemetry-parser

telemetry-parser-py

Library to parse real-time metadata embedded in video files or telemetry from other sources.

Supported formats:

• GoPro (HERO 5 and later)
• Sony (a1, a7c, a7r IV, a7 IV, a7s III, a9 II, FX3, FX6, FX9, RX0 II, RX100 VII, ZV1, ZV-E10)
• Insta360 (OneR, OneRS, SMO 4k, Go, GO2, Caddx Peanut)
• DJI (Avata, O3 Air Unit, Action 2)
• Blackmagic RAW (*.braw)
• RED RAW (V-Raptor, KOMODO) (*.r3d)
• Betaflight blackbox (*.bfl, *.bbl, *.csv)
• ArduPilot logs (*.bin, *.log)
• Gyroflow .gcsv log
• iOS apps: Sensor Logger, G-Field Recorder, Gyro, GyroCam
• Android apps: Sensor Logger, Sensor Record, OpenCamera Sensors, MotionCam Pro
• Runcam CSV (Runcam 5 Orange, iFlight GOCam GR, Runcam Thumb, Mobius Maxi 4K)
• Hawkeye Firefly X Lite CSV
• XTU (S2Pro, S3Pro)
• WitMotion (WT901SDCL binary and *.txt)
• Vuze (VuzeXR)
• KanDao (Obisidian Pro)
• CAMM format
• TODO DJI flight logs (*.dat, *.txt)

Example usage:

import telemetry_parser

tp = telemetry_parser.Parser('sample.mp4')
print('Camera: ', tp.camera)
print('Model: ', tp.model)

# return all telemetry as an array of dicts
print('Telemetry', tp.telemetry())

# format the values with units etc
print('Telemetry formatted', tp.telemetry(human_readable = True))

# return only gyro and accel with timestamps, normalized to a single orientation and scaled to deg/s and m/s2
print('Normalized IMU', tp.normalized_imu())

Building

1. Setup virtual env: python -m venv .env ; source .env/bin/activate
2. Install maturin: pip install maturin
3. Build python wheels: maturin build --release
4. Resulting wheels will be in target/wheels/ directory
5. Install using pip: pip install telemetry_parser_py-0.1.0-cp39-none-win_amd64.whl