Compute 2D human pose and angles from a video or a webcam.
C-Rank Grade: D (Risky) - 27/100
External PR Merge Rate: -
Response Time: <1h
First Timer Success: -
davidpagnon/Sports2D has a recorded first-timer success rate of 0.0%. Repositories ranked D typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in davidpagnon/Sports2D respond to incoming external pull requests in approximately 0.0 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 26.9 places davidpagnon/Sports2D in the D tier.
The external contributor pull request merge rate for davidpagnon/Sports2D is 0.0%, based on public PR activity from non-core contributors.
davidpagnon/Sports2D currently has 1 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".
Active maintainer team in davidpagnon/Sports2D welcoming community pull requests and bug fixes.
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External Acceptance Rate
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First PR Conversion
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Historical health & responsiveness evolution
External PR acceptance
First PR success rate
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90% receive response in
Maintainer review activity heatmap & prime window prediction
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Detected: UTC
Maintainers are most responsive around 16:00 UTC (16:00 UTC in your timezone). Recommended submission window is Monday - Wednesday from 13:00 to 17:00 UTC (13:00 - 17:00 UTC local).
Maintainer Strategy: Maintainer Sweet Spot: PRs under 150 lines merge in ~4 hours (81% approval). Large PRs (>500 lines) take ~0 hours (29% approval). Keep your diff compact for rapid review.
Your OS Windows Your Python version Python 3.11 What is your library version? Pose2sim v0.10.49; sports2d 0.8.32 Your problem Hey there, I know this has already been addressed in #35, but wanted to share our case in case it's useful for narrowing down the cause. We're part of a research team doing postural analysis of running on a treadmill. We're seeing joint angles switch back and forth mid-run. mode: performance reduces it noticeably, but it's quite bad on balanced. A couple of things on our end: Video is captured in sagittal view, as parallel to the motion plane as possible, per the docs. Camera: Panasonic HV-V7700, 1080p @ 50fps. Questions: Is this switching mode-dependent or is there something else going on? Would you expect framerate to meaningfully help here, or is this purely a pose-model-accuracy issue? Params: { "time_range": "", "nb_persons_to_detect": "all", "person_ordering_method": "first_detected", "first_person_height": "1.65", "pose_model": "body_with_feet", "mode":
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When evaluating whether to contribute to davidpagnon/Sports2D, 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 davidpagnon/Sports2D acknowledge new external contributions in approximately <1 hour. Out of all submitted pull requests from non-core authors in the last 180-day window, 0.0% were successfully merged into the primary branch.
davidpagnon/Sports2D has a recorded first-timer success rate of 0.0%. Repositories ranked Risky typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~<1 hour. 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 26.9 places davidpagnon/Sports2D in the Risky tier.
The external pull request merge rate is 0.0%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
Yes, davidpagnon/Sports2D 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 davidpagnon/Sports2D 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.