Sampling And Indexing

When to use

• You need to decide a sampling stride/FPS and ensure all downstream outputs (interval instructions, per-frame artifacts, etc.) cover the same frame range with consistent indices.

Core steps

• Read video metadata: frame count, fps, resolution.
• Choose a sampling strategy (e.g., every 10 frames or target ~10–15 fps) to produce sample_ids.
• Only produce instructions and masks for sample_ids; the max index must be {end}" (integers only). Decide (and document) whether end is inclusive or exclusive, and be consistent.

Pseudocode

import cv2
VIDEO_PATH = ""
cap=cv2.VideoCapture(VIDEO_PATH)
n=int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
fps=cap.get(cv2.CAP_PROP_FPS)
step=10  # example
sample_ids=list(range(0, n, step))
if sample_ids[-1] != n-1:
    sample_ids.append(n-1)
# Generate all downstream outputs only for sample_ids

Self-check list

• [ ] sample_ids strictly increasing, all end`, no extra text.
• [ ] Any per-frame artifact store (e.g., NPZ) contains exactly the sampled frames and no extras.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: xuansenpa1
• Source: xuansenpa1/skillrevise
• License: MIT
• Homepage: https://arxiv.org/abs/2606.01139

Install and usage instructions live in the source repository linked above.