> For the complete documentation index, see [llms.txt](https://docs.openmind.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.openmind.com/release-notes/video-processor/beta.md). # beta ### What's included First beta release for OM1 video processor. This release introduces major foundational features that enable developers and integrators to build advanced streaming and analytics solutions with ease. ### **v1.0.1-beta.3** * Introduced a new variable called ENABLE\_CLOUD\_STREAMING, which can be used to disable the online streaming feature. ### **v1.0.1-beta.2** * The raw video stream is published to the local media MTX server at the URL /top\_camera\_raw for local usage. ### **v1.0.1-beta.1** * Switched the base Docker image from JetPack to CUDA 13.0.0 with Ubuntu 24.04 * Updated the Python version from 3.10 to 3.12 * CUDA driver mismatch issue fixed * Fixed TensorRT version ### **v1.0.0-beta.1** * Face Detection and Anonymization: Added advanced face detection capabilities with real-time anonymization. Faces can now be automatically blurred or masked to protect privacy in live or recorded streams. This process takes place on the edge device of the robot. * RTSP for Audio and Video Streaming: Introduced full RTSP (Real-Time Streaming Protocol) support, enabling seamless transmission of both audio and video data. This allows integration with a wider range of cameras, streaming servers, and third-party applications. RTSP manages streaming sessions but does not typically transport the media data itself * Support Multiple Video streams: Enhanced the system to support multiple concurrent video streams. Users can now view, process, and manage several input sources simultaneously without performance degradation. * Support the Local and Remote Video Stream: Added the ability to handle both local camera feeds and remote video sources. This provides greater flexibility for hybrid setups that combine on-premise and cloud-based video inputs. * Reduced Microphone Latency: Optimized the audio pipeline to significantly reduce microphone input latency. This ensures more natural and synchronized communication in real-time applications. * Dynamic FPS Support: Implemented dynamic frame rate adjustment to optimize performance and bandwidth usage. The system now automatically adapts FPS based on network conditions and processing load. * Noise Cancellation and Echo Reduction: Integrated advanced audio processing algorithms for noise suppression and echo reduction. This results in clearer, higher-quality sound for both streaming and recording scenarios. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.openmind.com/release-notes/video-processor/beta.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.