NVIDIA DeepStream Monorepo: DeepStream SDK and reference apps for building GPU‑accelerated, real-time video and multi‑sensor analytics pipelines with GStreamer, TensorRT, and vision AI models across edge, on‑prem, and cloud deployments.
C-Rank Grade: B (Solid) - 54/100
External PR Merge Rate: 67%
Response Time: 10h
First Timer Success: 100%
NVIDIA/DeepStream has a recorded first-timer success rate of 100.0%. Repositories ranked B typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in NVIDIA/DeepStream respond to incoming external pull requests in approximately 10.1 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.
The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 54.2 places NVIDIA/DeepStream in the B tier.
The external contributor pull request merge rate for NVIDIA/DeepStream is 66.7%, based on public PR activity from non-core contributors.
NVIDIA/DeepStream currently has 1 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".
NVIDIA DeepStream Monorepo: DeepStream SDK and reference apps for building GPU‑accelerated, real-time video and multi‑sensor analytics pipelines with GStreamer, TensorRT, and vision AI models across edge, on‑prem, and cloud deployments.
Highly welcoming maintainers in NVIDIA/DeepStream. Prompt code reviews with positive guidance for new contributors.
Discussions in NVIDIA/DeepStream focus heavily on practical implementation feedback, code formatting standards, and issue reproduction details.
Unlinked PRs without issue context and changes that fail automated test suites face the highest review friction.
Average Response Latency
Tracks hours until a maintainer leaves a review, comment, or PR response.
External Acceptance Rate
Percentage of community pull requests successfully merged into main.
First PR Conversion
Rate at which developers submitting their first repository PR succeed.
Show contributors that your repository actively reviews and merges external pull requests.
[](https://getmerged.abhishekco.de/NVIDIA/DeepStream?utm_source=github&utm_medium=badge)
External PR acceptance
First PR success rate
50% receive response in
90% receive response in
Maintainer review activity heatmap & prime window prediction
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Detected: UTC
Maintainers are most responsive around 07:00 UTC (07:00 UTC in your timezone). Recommended submission window is Wednesday - Friday from 04:00 to 08:00 UTC (04:00 - 08:00 UTC local).
Maintainer Strategy: Maintainer Sweet Spot: PRs under 150 lines merge in ~7 hours (83% approval). Large PRs (>500 lines) take ~48 hours (30% approval). Keep your diff compact for rapid review.
Issue: nvstreammux SIGSEGV when reusing the same pipeline for a 2nd file after EOS (DS 9.1; works on DS 7.1) Summary We run a single DeepStream pipeline (filesrc → h265parse → nvv4l2decoder → nvstreammux → nvinfer → ... → encoder → filesink) and reuse it sequentially for multiple H.265 files: after a file reaches EOS we go GST_STATE_NULL → READY → PLAYING, change filesrc/filesink locations, and play the next file. This works fine on DeepStream 7.1 (validated with 11 files / 3 resolution groups). On DeepStream 9.1 the same program segfaults at the 2nd file of the first group, inside the closed nvstreammux (libnvdsgst_multistream.so) while the decoder re-negotiates caps into the mux. We believe nvstreammux cannot be safely reused after an EOS'd source in 9.1 (regression vs 7.1, or a behavior change). Since the nvstreammux source is now in this repo under src/gst-plugins/gst-nvmultistream2, we'd like to report it here. Environment Item Crashes (DS 9.1 — dev box) Wo
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When evaluating whether to contribute to NVIDIA/DeepStream, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.
Currently, maintainers of NVIDIA/DeepStream acknowledge new external contributions in approximately 10 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 66.7% were successfully merged into the primary branch.
NVIDIA/DeepStream has a recorded first-timer success rate of 100.0%. Repositories ranked Solid typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~10 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.
The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 54.2 places NVIDIA/DeepStream in the Solid tier.
The external pull request merge rate is 66.7%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
Yes, NVIDIA/DeepStream currently has 1 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.
All metrics displayed for NVIDIA/DeepStream are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.