TRANS-CODEX is a ffmpeg based hardware acceleration product for IPTV live stream transcoding solution. It’s not just a software, it’s a professional solution. compared to the traditional CPU based transcoding server. It can use much lower hardware cost to transcoding much more live stream. and even much lower power consumption.
After 10 months long term development, TRANS-CODEX is ready. Let me list the features it supports.
1. H.264 & H.265 supports for NVENC.
2. One-time decoding based multiple bitrate output for arbitrary protocols supports.
3. VideoJS based realtime web H.264 player to watching your stream via browser.
4. Realtime CPU, Memory, Network And GPU monitoring supports.
5. Offline package based upgrade supports.
6. Unlimited the live transcoding streams. It only limited by your hardware.
7. H.264 baseline, main and high profile supports.
8. H.265 main, main10 and rext profile supports.
9. CBR and VBR bitrate control supports.
10. 24, 25, 30, 50 and 60 fps frame rate supports.
11. Key frame interval 0~25 supports.
12. CPU and GPU based deinterlance supports.
13. HD1080, HD720, HD480, PAL576 and other output resolution supports.
14. Video overlay watermark supports.
15. Audio mp3 and aac codec supports.
16. HTTP Living Streaming with Adaptive Bitrate Streaming supports.
17. RTMP, RTSP, RTP and UDP output protocol supports.
18. Login password and burst force crack protection.
17. 24 x 7 hours long time stable and uninterruptedly transcoding supports.
If you want to build a data center level transcoding servers. we recommend you using Nvidia NVENC technology. compared to the QuickSync, you can plugin multiple Nvidia GPU card to maximum the server performance. If you want to transcoding SD or HD720-HD1080 streams. we recommend using GTX 1060 6GB or GTX 1070 8GB. because when you transcoding these SD or HD720-HD1080 streams, the bottleneck is come from GPU RAM. so more GPU RAM is better in this situation. But if you need to transcoding HD1080 streams, We recommend you using the GTX 1050 4GB or GTX 1060 6GB. now the bottleneck is GPU performance.