Developer Guide#
- Advanced Installation Guide
- Metadata
- Model Preparation
- Model Info Section
- Python Bindings
- Custom Processing
- 1. Consume tensor data and parse/convert it on application side
- 2. Set C/Python callback in the middle of GStreamer pipeline
- 3. Insert gvapython element and provide Python callback function
- 4. Insert new GStreamer element implemented on C/C++
- 5. Modify source code of post-processors for gvadetect/gvaclassify elements
- Object Tracking
- GPU device selection
- Performance Guide
- 1. Media and AI processing (single stream)
- 2. Multi-stage pipeline with gvadetect and gvaclassify
- 3. Multi-stream pipelines with single AI stage
- 4. Multi-stream pipelines with multiple AI stages
- 5. GPU device selection
- 6. Using GStreamer framework compositor element for merging many video displays into single view
- 7. The Intel® DL Streamer Pipeline Framework performance benchmark results
- Profiling with Intel VTune™
- Converting NVIDIA DeepStream Pipelines to Intel® Deep Learning Streamer (Intel® DL Streamer) Pipeline Framework
- How to Contribute
- Latency Tracer
- Model-proc File (legacy)