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Halaman ini menjelaskan cara memberi anotasi pada streaming video dari protokol live streaming standar.
Streaming API Video Intelligence API memungkinkan analisis streaming real-time untuk media live. Fitur yang didukung meliputi:
Deteksi Label Live
Deteksi Perubahan Bidikan Live
Deteksi Konten Vulgar Live
Deteksi dan Pelacakan Objek Live
Library penyerapan AIStreamer menyediakan serangkaian antarmuka open source dan contoh kode untuk terhubung ke Streaming API Video Intelligence API. Library
mendukung:
HTTP Live Streaming (HLS): protokol streaming dan komunikasi media berbasis HTTP.
Real Time Streaming Protocol (RTSP): protokol kontrol jaringan untuk server media streaming. Protokol ini digunakan bersama dengan
Real Time Protocol (RTP) dan Real Time Control Protocol (RTCP).
Real Time Messaging Protocol (RTMP): protokol untuk streaming audio, video, dan data melalui Internet.
Untuk mulai menggunakan AIStreamer
Library penyerapan AIStreamer mencakup contoh berikut (termasuk
contoh Docker).
Live Streaming:
Petunjuk untuk mendukung protokol live streaming
(HLS, RTSP, dan RTMP) di Video Intelligence API.
Docker & Kubernetes:
Petunjuk untuk menggunakan contoh docker dan deployment kubernetes kami.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-09-04 UTC."],[],[],null,["# Stream live videos\n\n| **Beta**\n|\n|\n| This feature is subject to the \"Pre-GA Offerings Terms\" in the General Service Terms section\n| of the [Service Specific Terms](/terms/service-terms#1).\n|\n| Pre-GA features are available \"as is\" and might have limited support.\n|\n| For more information, see the\n| [launch stage descriptions](/products#product-launch-stages).\n\nThis page describes how to annotate a video stream from standard live\nstreaming protocols.\n\nThe Video Intelligence API Streaming API enables real-time streaming\nanalysis for live media. Supported features include:\n\n- Live Label Detection\n\n- Live Shot Change Detection\n\n- Live Explicit Content Detection\n\n- Live Object Detection and Tracking\n\nThe [AIStreamer](https://github.com/google/aistreamer/tree/master/ingestion)\ningestion library provides a set of open source interfaces and\nexample code to connect to the Video Intelligence API Streaming API. The\nlibrary supports:\n\n- HTTP Live Streaming (HLS): an HTTP based media streaming and communication\n protocol.\n\n- Real Time Streaming Protocol (RTSP): a network control protocol for\n streaming media servers. It is used in conjunction with\n Real Time Protocol (RTP) and Real Time Control Protocol (RTCP).\n\n- Real Time Messaging Protocol (RTMP): a protocol for streaming audio,\n video, and data over the Internet.\n\nTo start using AIStreamer\n-------------------------\n\nThe AIStreamer ingestion library includes the following examples (incuding\na Docker example).\n\n- [Live Streaming](/video-intelligence/docs/streaming/live-streaming):\n Instructions for supporting live streaming protocols\n (HLS, RTSP and RTMP) in Video Intelligence API.\n\n- [Docker \\& Kubernetes](/video-intelligence/docs/streaming/docker-kubernetes):\n Instructions for using our docker example and kubernetes deployment.\n\n- [Live Label Detection](/video-intelligence/docs/streaming/live-label-detection):\n Instructions for streaming label analysis.\n\n- [Live Shot Change Detection](/video-intelligence/docs/streaming/live-shot-change-detection):\n Instructions for streaming shot change analysis.\n\n- [Live Explicit Content Detection](/video-intelligence/docs/streaming/live-explicit-content):\n Instructions for streaming explicit content analysis.\n\n- [Live Object Detection and Tracking](/video-intelligence/docs/streaming/live-object-tracking):\n Instructions for streaming object detection and tracking analysis.\n\nCode architecture\n-----------------\n\nThe AIStreamer ingestion library includes the following three directories:\n\n- [client](https://github.com/google/aistreamer/tree/master/ingestion/client):\n Python \\& C++ client libraries for connecting to Video Intelligence.\n\n- [env](https://github.com/google/aistreamer/tree/master/ingestion/env):\n Docker example for AIStreamer ingestion.\n\n- [proto](https://github.com/google/aistreamer/tree/master/ingestion/proto):\n Proto definitions and gRPC interface for Video Intelligence.\n\nThird-party dependencies\n------------------------\n\nThe open source AIStreamer ingestion library is based on the following\nGoogle-owned and third-party open source libraries.\n\n- [Bazel](https://bazel.build/): A build and test tool with multi-language support.\n\n- [gRPC](https://grpc.io/): A high performance, open-source universal RPC framework.\n\n- [Protobuf](https://developers.google.com/protocol-buffers): Google's\n language-neutral, platform-neutral, extensible mechanism for serializing structured data.\n\n- [rules_protobuf](https://github.com/pubref/rules_protobuf): Bazel rules for building protocol buffers and gRPC services.\n\n- [glog](https://github.com/google/glog): C++ implementation of the Google logging module.\n\n- [gflags](https://github.com/gflags/gflags): C++ library that implements command-line flags processing.\n\n- [ffmpeg](https://www.ffmpeg.org/): A complete, cross-platform solution to\n record, convert and stream audio and video.\n\n- [gStreamer](https://gstreamer.freedesktop.org/): Another cross-platform multimedia processing and streaming framework."]]
