nvidia-holoscan/holohub
Mar 2026 – Mar 2026
1 Month active
Languages Used
CMakeDockerfilePython
Technical Skills
AI DevelopmentCUDAComputer VisionDeep LearningDockerHoloscan SDK
Javier Gamazo
PROFILE
Javier Gamazo
Developed the Tracks2Endo4D application within the nvidia-holoscan/holohub repository, delivering real-time 3D point tracking and camera estimation from video for advanced analytics workflows. Leveraged deep learning and computer vision techniques, integrating a TensorRT-powered inference operator to accelerate tracking performance. Established a robust deployment pipeline using Docker and CMake, enabling seamless model conversion to ONNX and streamlined engine generation. Enhanced the end-to-end 4D tracking workflow with comprehensive documentation, automated tests, and VS Code debug configurations. These efforts provided a scalable, production-ready foundation for real-time 4D tracking, improving both performance and developer experience through clear documentation and reliable deployment processes.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
7,033
Activity Months1
Your Network
1666 peopleSame Organization
@nvidia.com1624
Shared Repositories
42
Work History
March 2026
1 Commits • 1 Features
Mar 1, 2026March 2026 monthly summary focused on delivering a high-value real-time analytics capability and establishing a robust deployment workflow for real-time 3D tracking. Key outcomes include the Tracks2Endo4D app enabling end-to-end 3D point tracking and camera estimation from video, accelerated via TensorRT and integrated within Holoscan. The month also established deployment pipelines through Docker-based ONNX export/engine generation and holohub build/run, supported by comprehensive documentation and tests. These efforts lay the groundwork for scalable, production-ready 4D tracking workflows with improved performance, visualization, and developer experience.
1 Commits • 1 Features
Mar 1, 2026March 2026 monthly summary focused on delivering a high-value real-time analytics capability and establishing a robust deployment workflow for real-time 3D tracking. Key outcomes include the Tracks2Endo4D app enabling end-to-end 3D point tracking and camera estimation from video, accelerated via TensorRT and integrated within Holoscan. The month also established deployment pipelines through Docker-based ONNX export/engine generation and holohub build/run, supported by comprehensive documentation and tests. These efforts lay the groundwork for scalable, production-ready 4D tracking workflows with improved performance, visualization, and developer experience.
March 2026
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage80.0%
Skills & Technologies
Programming Languages
CMakeDockerfilePython
Technical Skills
AI DevelopmentCUDAComputer VisionDeep LearningDockerHoloscan SDK
Repositories Contributed To
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