Practical overview
When it fits
Use VideoPipe when building a C++ application that needs configurable video input, model inference and downstream analysis or data output, especially when you want to compose those functions as independent nodes.
Who it is for
- C++ developers building video-analysis applications from computer-vision models.
- Teams structuring video or creating image-search and face-recognition workflows.
- Developers implementing tracking-based traffic or security behavior analysis.
Documented uses
- Connect video streams or images to decoding, inference and analysis stages.
- Integrate object detection, classification, feature extraction or image-generation models with a selected inference backend.
- Track objects and apply behavior logic such as line-crossing, parking or violation detection.
- Overlay results, record selected footage or frames, and export structured data to files, cloud services or third-party systems.
Requirements & limits
The repository is public and identifies its license as Apache-2.0. The README documents building from source.
- Core prerequisites are C++17, OpenCV 4.6 or later, GStreamer 1.14.5 and GCC 7.5 or later.
- The README says a plain CMake configuration builds for CPU; CUDA, TensorRT, Paddle, Kafka, LLM and advanced-sample options are separately enabled.
- The project supplies pipeline components and integration points; developers prepare the model and understand how to parse its output.
- Documented stream protocols include UDP, RTSP and RTMP, as well as files and applications.
- Platform examples in the README include specific Ubuntu and hardware configurations, and some accelerator entries say code is not provided.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Build VideoPipe with its default configuration
Compile the project using the README's documented default CMake setup.
Before you start
- C++17
- OpenCV 4.6 or later
- GStreamer 1.14.5
- GCC 7.5 or later
Steps
Clone the repository: git clone https://github.com/sherlockchou86/VideoPipe.git
Change into the VideoPipe directory.
Create and enter a build directory: mkdir build && cd build.
Run cmake .. and then make -j8.
Expected outcome
The README says compiled libraries are placed in build/libs and sample executables in build/bin.
Guide limitations
- The default configuration uses the CPU; optional backend and feature modules are not enabled by default.
Enable CUDA and TensorRT in the CMake build
Configure the build to include the documented CUDA and TensorRT modules.
Before you start
- The VideoPipe core build requirements: C++17, OpenCV 4.6 or later, GStreamer 1.14.5 and GCC 7.5 or later.
- CUDA and TensorRT installations for the optional modules.
Steps
Follow the repository's CUDA and TensorRT installation guidance.
From the build directory, configure with cmake -DVP_WITH_CUDA=ON -DVP_WITH_TRT=ON ..
Run make -j8.
Expected outcome
The build is configured to compile CUDA-related and TensorRT-related features and samples.
Guide limitations
- The README marks these options off by default.
- The documented configuration steps do not describe running a particular application or model.
Compare options for Model inference and serving
These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.
| Project | Documented purpose | Platform | Access and requirements |
|---|---|---|---|
| Videopipe | Connect video streams or images to decoding, inference and analysis stages. | The repository is public and identifies its license as Apache-2.0. The README documents building from source. | |
| Hyperpose | Customize pose-estimation architectures and datasets. | Docker, Linux, macOS, Windows | |
| Multi Task Nlp | Define multiple tasks and their data and model settings in a YAML file. | Linux, macOS, Windows | The project is an open-source library under the Apache-2.0 license, distributed through its public GitHub repository. |
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 10 October 2026
- Original website title
- sherlockchou86/VideoPipe · Official homepage title · retained in its source language