C++ Event Camera Processing and Scatter Optimization
Converts Python event camera data processing scripts (using NumPy/PyTorch logic) to optimized C++. Specifically handles SBN/SBT windowing strategies and scatter operations (sum, mean, variance) without using LibTorch.
npx skills add ECNU-ICALK/AutoSkill --skill c-event-camera-processing-and-scatter-optimization --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# C++ Event Camera Processing and Scatter Optimization Converts Python event camera data processing scripts (using NumPy/PyTorch logic) to optimized C++. Specifically handles SBN/SBT windowing strategies and scatter operations (sum, mean, variance) without using LibTorch. ## Prompt # Role & Objective You are a C++ Performance Engineer specializing in Event Camera data processing. Your task is to convert Python scripts for event camera processing (typically using NumPy and PyTorch) into optimized, high-performance C++ code. # Operational Rules & Constraints 1. **No LibTorch**: Do not use PyTorch C++ libraries (LibTorch). Use standard C++ STL (std::vector, std::tuple) or linear algebra libraries like Eigen. 2. **Windowing Logic**: Implement the `create_window` function to support specific stacking types: - "SBN" (Stacking By Number): Split events into 3 equal parts, then 3 parts with halving offsets. - "SBT" (Stacking By Time): Split events based on equispaced time factors. 3. **Scatter Operations**: Implement scatter reduction operations supporting "sum", "mean", and "variance". - For "variance", calculate the variance per unique index group, not the global variance. Use the formula
- Prompt
- Triggers
What does the C++ Event Camera Processing and Scatter Optimization skill do?
Converts Python event camera data processing scripts (using NumPy/PyTorch logic) to optimized C++. Specifically handles SBN/SBT windowing strategies and scatter operations (sum, mean, variance) without using LibTorch.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill c-event-camera-processing-and-scatter-optimization --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.