run2-object-counting

name	run2_object-counting
description	Count the number of object occurrences in an image using OpenCV template matching in Python.

Object Counting

Count the number of objects in an image using computer vision, specifically Normalized Cross-Correlation (Template Matching).

Usage

The count_objects.py script provided in the environment performs template matching and outputs the number of matches found.

python3 /root/.agents/skills/object_counter/scripts/count_objects.py \
    --tool count \
    --input_image <image_file> \
    --object_image <object_template_file> \
    --threshold <threshold_value> \
    --dedup_min_dist <distance>

Arguments Explained:

• --input_image: The target image where objects should be counted.
• --object_image: The template image of the object you are searching for.
• --threshold: The matching confidence threshold (e.g., 0.9 for high fidelity).
• --dedup_min_dist: Minimum pixel distance to deduplicate overlapping matches (e.g., 3).

Example

python3 /root/.agents/skills/object_counter/scripts/count_objects.py \
    --tool count \
    --input_image frame_001.png \
    --object_image coin.png \
    --threshold 0.9 \
    --dedup_min_dist 3

Parsing Output

The script prints the result in the following format to standard output: There are X objects (\<template_path>`) in file: `<image_path>``

You can parse this programmatically using regular expressions in a Python wrapper script:

import re, subprocess

result = subprocess.run(cmd, stdout=subprocess.PIPE, text=True)
match = re.search(r'There are (\d+) objects', result.stdout)
if match:
    count = int(match.group(1))