generate-counting-csv

name	generate-counting-csv
description	Use this skill to generate the final CSV file at /root/counting_results.csv with columns frame_id, coins, enemies, turtles. Frame IDs must be in the format /root/keyframes_%03d.png.

CSV format specification

The output CSV file must be at /root/counting_results.csv with the following structure:

frame_id,coins,enemies,turtles
/root/keyframes_001.png,3,1,0
/root/keyframes_002.png,2,0,1
...

Requirements

• Columns: frame_id, coins, enemies, turtles (exactly these names, in this order)
• frame_id format: /root/keyframes_%03d.png — zero-padded 3-digit numbers starting from 001
• Rows: One per keyframe, sorted in timeline order (001, 002, 003, ...)
• Values: Non-negative integers for coins, enemies, turtles

Writing the CSV

import csv

# results is a list of dicts with keys: frame_id, coins, enemies, turtles
with open('/root/counting_results.csv', 'w', newline='') as f:
    writer = csv.DictWriter(f, fieldnames=['frame_id', 'coins', 'enemies', 'turtles'])
    writer.writeheader()
    writer.writerows(results)

Verification

import csv

with open('/root/counting_results.csv', 'r') as f:
    reader = csv.DictReader(f)
    rows = list(reader)
    print(f"Number of rows: {len(rows)}")
    print(f"Columns: {reader.fieldnames}")
    for row in rows:
        print(row)

Check that:

1. The number of rows matches the number of extracted keyframes
2. All frame_id values follow the /root/keyframes_%03d.png format
3. All count values are valid integers >= 0