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xgqfrms · 2026-04-13 · via 博客园 - xgqfrms

如何使用 FFmpeg 提取 GoPro 视频中保存的原始 telemetry 数据

FFmpeg

# reinstall
$ brew reinstall ffmpeg

$ ffmpeg -version
ffmpeg version 8.1 Copyright (c) 2000-2026 the FFmpeg developers
built with Apple clang version 16.0.0 (clang-1600.0.26.6)
configuration: --prefix=/usr/local/Cellar/ffmpeg/8.1 --enable-shared --enable-pthreads --enable-version3 --cc=clang --host-cflags= --host-ldflags= --enable-ffplay --enable-gpl --enable-libsvtav1 --enable-libopus --enable-libx264 --enable-libmp3lame --enable-libdav1d --enable-libvmaf --enable-libvpx --enable-libx265 --enable-openssl --enable-videotoolbox --enable-audiotoolbox
libavutil      60. 26.100 / 60. 26.100
libavcodec     62. 28.100 / 62. 28.100
libavformat    62. 12.100 / 62. 12.100
libavdevice    62.  3.100 / 62.  3.100
libavfilter    11. 14.100 / 11. 14.100
libswscale      9.  5.100 /  9.  5.100
libswresample   6.  3.100 /  6.  3.100

Exiting with exit code 0

https://ffmpeg.org/

https://github.com/ffmpeg/ffmpeg

demos

如何使用 ffmpeg 提取 GoPro 视频中保存的原始 telemetry 数据，并且根据数据中的速度，生成一个展示实时速度的仪表盘 overlay

# 1. 查看 GoPro 原始视频中的 telemetry metadata 数据位置
$ ffmpeg -i /Users/xgqfrms-mm/Movies/goPro/GX010918_Trim_06.11.MP4
ffmpeg version 8.1 Copyright (c) 2000-2026 the FFmpeg developers
  built with Apple clang version 16.0.0 (clang-1600.0.26.6)
  configuration: --prefix=/usr/local/Cellar/ffmpeg/8.1 --enable-shared --enable-pthreads --enable-version3 --cc=clang --host-cflags= --host-ldflags= --enable-ffplay --enable-gpl --enable-libsvtav1 --enable-libopus --enable-libx264 --enable-libmp3lame --enable-libdav1d --enable-libvmaf --enable-libvpx --enable-libx265 --enable-openssl --enable-videotoolbox --enable-audiotoolbox
  libavutil      60. 26.100 / 60. 26.100
  libavcodec     62. 28.100 / 62. 28.100
  libavformat    62. 12.100 / 62. 12.100
  libavdevice    62.  3.100 / 62.  3.100
  libavfilter    11. 14.100 / 11. 14.100
  libswscale      9.  5.100 /  9.  5.100
  libswresample   6.  3.100 /  6.  3.100
Input #0, mov,mp4,m4a,3gp,3g2,mj2, from '/Users/xgqfrms-mm/Movies/goPro/GX010918_Trim_06.11.MP4':
  Metadata:
    major_brand     : mp41
    minor_version   : 538120216
    compatible_brands: mp41
    creation_time   : 2026-04-12T14:59:23.000000Z
    firmware        : H24.01.02.10.70
    location        : +31.0419+121.2282/
    location-eng    : +31.0419+121.2282/
  Duration: 00:01:22.82, start: 0.000000, bitrate: 8193 kb/s
  Stream #0:0[0x1](eng): Video: hevc (Main) (hvc1 / 0x31637668), yuvj420p(pc, bt709), 1920x1080 [SAR 1:1 DAR 16:9], 7912 kb/s, 59.94 fps, 59.94 tbr, 60k tbn (default)
    Metadata:
      creation_time   : 2026-04-12T14:59:23.000000Z
      handler_name    : GoPro H.265
      encoder         : GoPro H.265 encoder
      timecode        : 22:35:05:23
  Stream #0:1[0x2](eng): Audio: aac (LC) (mp4a / 0x6134706D), 48000 Hz, stereo, fltp, 189 kb/s (default)
    Metadata:
      creation_time   : 2026-04-12T14:59:23.000000Z
      handler_name    : GoPro AAC
  Stream #0:2[0x3](eng): Data: bin_data (gpmd / 0x646D7067), 64 kb/s (default)
    Metadata:
      creation_time   : 2026-04-12T14:59:23.000000Z
      handler_name    : GoPro MET
  Stream #0:3[0x4](eng): Data: none (tmcd / 0x64636D74)
    Metadata:
      creation_time   : 2026-04-12T14:59:23.000000Z
      timecode        : 22:35:05:23
At least one output file must be specified

General Purpose Metadata Format (GPMF)
GoPro Metadata (GPMD)

# 2. 提取 telemetry metadata，并保存到 telemetry.bin
$ cd /Users/xgqfrms-mm/Movies/goPro/
$ ffmpeg -y -i GX010918_Trim_06.11.MP4 -codec copy -map 0:2 -f rawvideo telemetry.bin

# 等价于
$ ffmpeg -y -i /Users/xgqfrms-mm/Movies/goPro/GX010918_Trim_06.11.MP4 -codec copy -map 0:2 -f rawvideo /Users/xgqfrms-mm/Movies/goPro/telemetry.bin

0:2 是 telemetry stream（可能不同，按实际调整）
0:2 就是 gpmd

# 3. 解析 GPS speed
$ npm install gopro-telemetry

$ node extract.js

// extract.js
const fs = require('fs');
const goproTelemetry = require('gopro-telemetry');

const rawData = fs.readFileSync('telemetry.bin');

goproTelemetry({ rawData }, (err, data) => {
  if (err) throw err;

  const gps = data['1'].streams.GPS5.samples;

  const result = gps.map(s => ({
    t: s.date,
    speed: (s.value[3] || 0) * 3.6 // m/s → km/h
  }));

  fs.writeFileSync('speed.json', JSON.stringify(result, null, 2));
});

生成 speed.json 速度数据

# 4. 生成仪表盘： 赛车 HUD（右上角）
$ python render.py

// render.py
import cv2
import json
import numpy as np

video = "GX010918_Trim_06.11.MP4"

with open("speed.json") as f:
    data = json.load(f)

cap = cv2.VideoCapture(video)

fps = cap.get(cv2.CAP_PROP_FPS)
w = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
h = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))

out = cv2.VideoWriter(
    "overlay.mp4",
    cv2.VideoWriter_fourcc(*"mp4v"),
    fps,
    (w, h)
)

max_speed = 140

i = 0

while True:
    ret, frame = cap.read()
    if not ret:
        break

    speed = data[min(i, len(data)-1)]["speed"]

    # HUD区域（右上角）
    hud = np.zeros((200, 300, 3), dtype=np.uint8)

    center = (150, 140)
    radius = 90

    # 外圈
    cv2.circle(hud, center, radius, (0,255,255), 2)

    # 指针
    angle = int((speed / max_speed) * 270 - 135)

    x = int(center[0] + radius * np.cos(np.radians(angle)))
    y = int(center[1] + radius * np.sin(np.radians(angle)))

    cv2.line(hud, center, (x,y), (0,0,255), 3)

    # 数字速度
    cv2.putText(hud, f"{speed:.0f} km/h",
                (60, 180),
                cv2.FONT_HERSHEY_SIMPLEX,
                0.8,
                (255,255,255), 2)

    # 叠加到右上角
    frame[10:210, w-310:w-10] = hud

    out.write(frame)
    i += 1

cap.release()
out.release()

# 5. 叠加仪表盘
$ ffmpeg -i GX010918_Trim_06.11.MP4 -i overlay.mp4 \
-filter_complex "[1:v]format=rgba[ov];[0:v][ov]overlay=W-w-20:20" \
-c:a copy final.mp4

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