# OpenCV Open GSOC 2026

**URL:** <https://forum.opencv.org/t/opencv-open-gsoc-2026/24363>\
**Category:** Uncategorized\
**Tags:** gsoc\
**Created:** [February 10, 2026, 10:39am UTC](https://forum.opencv.org/t/opencv-open-gsoc-2026/24363 "2026-02-10T10:39:20Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![Purushottam\_Jha](https://sea2.discourse-cdn.com/flex020/user_avatar/forum.opencv.org/purushottam_jha/32/14107_2.png) [@Purushottam\_Jha](https://forum.opencv.org/u/Purushottam_Jha)\
**Post date:** [February 10, 2026, 10:39am UTC](https://forum.opencv.org/t/opencv-open-gsoc-2026/24363/1 "2026-02-10T10:39:20Z")

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I have hands-on experience in building and deploying real-time Computer Vision pipelines using OpenCV, NVIDIA DeepStream, TensorRT, and Docker.

I have worked with Ultralytics-based Docker environments, explored their deployment workflows, and contributed to open-source projects through debugging, testing, and improving existing pipelines. I also have experience creating my own custom Docker images for GPU-based inference setups, ensuring reproducibility across systems with CUDA, TensorRT, and OpenCV dependencies. My work includes optimizing deep learning models using FP16/INT8 acceleration, converting models into TensorRT engines, and integrating them into DeepStream/GStreamer multi-stream video analytics pipelines.

Along with this, I am comfortable with Linux-based development, performance benchmarking, and edge deployment. I am highly motivated to contribute to OpenCV GSoC, and I am ready to work on the idea: **Expanding kornia-vlm with ONNX and TensorRT backends** for efficient, production-ready inference.